Awesome-AI-Papers

This repository is used to collect papers and code in the field of AI. The contents contain the following parts:

Table of Content

• NLP
  • Word2Vec
  • Seq2Seq
  • Pretraining
    • Large Language Model
    • LLM Application
    • LLM Technique
    • LLM Theory
    • Chinese Model
• CV
• Multimodal
  • Audio
  • BLIP
  • CLIP
  • Diffusion Model
  • Multimodal LLM
  • Text2Image
  • Text2Video
  • Survey for Multimodal
• Reinforcement Learning
• GNN
• Transformer Architecture

  ├─ NLP/  
  │  ├─ Word2Vec/  
  │  ├─ Seq2Seq/           
  │  └─ Pretraining/  
  │    ├─ Large Language Model/          
  │    ├─ LLM Application/ 
  │      ├─ AI Agent/          
  │      ├─ Academic/          
  │      ├─ Code/       
  │      ├─ Financial Application/
  │      ├─ Information Retrieval/  
  │      ├─ Math/     
  │      ├─ Medicine and Law/   
  │      ├─ Recommend System/      
  │      └─ Tool Learning/             
  │    ├─ LLM Technique/ 
  │      ├─ Alignment/          
  │      ├─ Context Length/          
  │      ├─ Corpus/       
  │      ├─ Evaluation/
  │      ├─ Hallucination/  
  │      ├─ Inference/     
  │      ├─ MoE/   
  │      ├─ PEFT/     
  │      ├─ Prompt Learning/   
  │      ├─ RAG/       
  │      └─ Reasoning and Planning/       
  │    ├─ LLM Theory/       
  │    └─ Chinese Model/             
  ├─ CV/  
  │  ├─ CV Application/          
  │  ├─ Contrastive Learning/         
  │  ├─ Foundation Model/ 
  │  ├─ Generative Model (GAN and VAE)/          
  │  ├─ Image Editing/          
  │  ├─ Object Detection/          
  │  ├─ Semantic Segmentation/            
  │  └─ Video/          
  ├─ Multimodal/       
  │  ├─ Audio/          
  │  ├─ BLIP/         
  │  ├─ CLIP/        
  │  ├─ Diffusion Model/   
  │  ├─ Multimodal LLM/          
  │  ├─ Text2Image/          
  │  ├─ Text2Video/            
  │  └─ Survey/           
  │─ Reinforcement Learning/ 
  │─ GNN/ 
  └─ Transformer Architecture/          

NLP

1. Word2Vec

• Efficient Estimation of Word Representations in Vector Space, Mikolov et al., arxiv 2013. [paper]
• Distributed Representations of Words and Phrases and their Compositionality, Mikolov et al., NIPS 2013. [paper]
• Distributed representations of sentences and documents, Le and Mikolov, ICML 2014. [paper]
• Word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding method, Goldberg and Levy, arxiv 2014. [paper]
• word2vec Parameter Learning Explained, Rong, arxiv 2014. [paper]
• Glove: Global vectors for word representation.，Pennington et al., EMNLP 2014. [paper][code]
• fastText: Bag of Tricks for Efficient Text Classification, Joulin et al., arxiv 2016. [paper][code]
• ELMo: Deep Contextualized Word Representations, Peters et al., NAACL 2018. [paper]
• Distilling the Knowledge in a Neural Network, Hinton et al., arxiv 2015. [paper][FitNets][Universal Cross-Tokenizer Distillation]
• BPE: Neural Machine Translation of Rare Words with Subword Units, Sennrich et al., ACL 2016. [paper][code][Glitch Tokens][Say Anything but This]
• Byte-Level BPE: Neural Machine Translation with Byte-Level Subwords, Wang et al., arxiv 2019. [paper][code]

2. Seq2Seq

• Generating Sequences With Recurrent Neural Networks, Graves, arxiv 2013. [paper]
• Sequence to Sequence Learning with Neural Networks, Sutskever et al., NeruIPS 2014. [paper]
• Neural Machine Translation by Jointly Learning to Align and Translate, Bahdanau et al., ICLR 2015. [paper][code]
• On the Properties of Neural Machine Translation: Encoder-Decoder Approaches, Cho et al., arxiv 2014. [paper]
• Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation, Cho et al., arxiv 2014. [paper]
• [fairseq][fairseq2][fairscale][pytorch-seq2seq]

3. Pretraining

• Attention Is All You Need, Vaswani et al., NIPS 2017. [paper][code]

• GPT: Improving language understanding by generative pre-training, Radford et al., preprint 2018. [paper][code]

• GPT-2: Language Models are Unsupervised Multitask Learners, Radford et al., OpenAI blog 2019. [paper][code][llm.c]

• GPT-3: Language Models are Few-Shot Learners, Brown et al., NeurIPS 2020. [paper][code][nanoGPT][build-nanogpt][gpt-fast][modded-nanogpt][Beyond NanoGPT][nanotron]

• InstructGPT: Training language models to follow instructions with human feedback, Ouyang et al., NeurIPS 2022. [paper][MOSS-RLHF][nanochat]

• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, Devlin et al., NAACL 2019 Best Paper. [paper][code][BERT-pytorch][bert4torch][bert4keras][ModernBERT][What Should We Learn From ModernBERT]

• RoBERTa: A Robustly Optimized BERT Pretraining Approach, Liu et al., arxiv 2019. [paper][code][Chinese-BERT-wwm]

• What Does BERT Look At: An Analysis of BERT's Attention, Clark et al., arxiv 2019. [paper][code]

• DeBERTa: Decoding-enhanced BERT with Disentangled Attention, He et al., ICLR 2021. [paper][code]

• DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter Sanh et al., arxiv 2019. [paper][code][albert_pytorch]

• BERT Rediscovers the Classical NLP Pipeline, Tenney et al., arxiv 2019. [paper][code]

• How to Fine-Tune BERT for Text Classification?, Sun et al., arxiv 2019. [paper][code]

• TinyStories: How Small Can Language Models Be and Still Speak Coherent English, Eldan and Li, arxiv 2023. [paper][dataset][phi-4][SmolLM][SmolLM2][SmolVLM][Computational Bottlenecks of Training Small-scale Large Language Models][SLMs-Survey][MiniLLM][aligning_tinystories][The Smol Training Playbook][Introducing talkie][NanoJev][RLCR][laya][Kev][Jev's Architecture Unmasked][Scaling JEV-like Decision Models with SGLang]

• [LLM101n][EurekaLabsAI][llm-course][intro-llm][llm-cookbook][hugging-llm][generative-ai-for-beginners][awesome-generative-ai-guide][LLMs-from-scratch][llm-action][llms_idx][tiny-universe][AISystem][LLM Architecture Gallery]

• [cs230-code-examples][victoresque/pytorch-template][songquanpeng/pytorch-template][Academic-project-page-template][WritingAIPaper]

• [tokenizer_summary][minbpe][tokenizers][tiktoken][OpenAI Harmony][SentencePiece][Cosmos-Tokenizer][tiktokenizer][tokenizer hub][chat-template-playground]

3.1 Large Language Model

• A Survey of Large Language Models, Zhao etal., arxiv 2023. [paper][code][LLMBox][LLMBook-zh][LLMsPracticalGuide][Foundations-of-LLMs]
• Efficient Large Language Models: A Survey, Wan et al., arxiv 2023. [paper][code]
• Challenges and Applications of Large Language Models, Kaddour et al., arxiv 2023. [paper]
• A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT, Zhou et al., arxiv 2023. [paper]
• From Google Gemini to OpenAI Q (Q-Star): A Survey of Reshaping the Generative Artificial Intelligence (AI) Research Landscape*, Mclntosh et al., arxiv 2023. [paper][AGI-survey]
• A Survey of Resource-efficient LLM and Multimodal Foundation Models, Xu et al., arxiv 2024. [paper][code]
• Large Language Models: A Survey, Minaee et al., arxiv 2024. [paper][Foundations of Large Language Models]
• Anthropic: Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback, Bai et al., arxiv 2022. [paper][code]
• Anthropic: Constitutional AI: Harmlessness from AI Feedback, Bai et al., arxiv 2022. [paper][code]
• Anthropic: Model Card and Evaluations for Claude Models, Anthropic, 2023. [paper]
• Anthropic: The Claude 3 Model Family: Opus, Sonnet, Haiku, Anthropic, 2024. [paper][Claude 3.5][Introducing Claude 4][OpenMythos]
• BLOOM: A 176B-Parameter Open-Access Multilingual Language Model, BigScience Workshop, arxiv 2022. [paper][code][model]
• OPT: Open Pre-trained Transformer Language Models, Zhang et al., arxiv 2022. [paper][code]
• Chinchilla: Training Compute-Optimal Large Language Models, Hoffmann et al., arxiv 2022. [paper]
• Gopher: Scaling Language Models: Methods, Analysis & Insights from Training Gopher, Rae et al., arxiv 2021. [paper]
• GPT-NeoX-20B: An Open-Source Autoregressive Language Model, Black et al., arxiv 2022. [paper][code]
• Gemini: A Family of Highly Capable Multimodal Models, Gemini Team, Google, arxiv 2023. [paper][Gemini 1.0][Gemini 1.5][Gemini 2.5][Unofficial Implementation][MiniGemini][Gemini Fullstack LangGraph Quickstart][GenAI Processors][Computer Use Preview][gemini-web2api][Gemini Omni]
• Gemma: Open Models Based on Gemini Research and Technology, Google DeepMind, arxiv 2024. [paper][code][google-deepmind/gemma][gemma.cpp][model][paligemma][gemma-cookbook]
• Gemma 2: Improving Open Language Models at a Practical Size, Google Team, 2024. [paper][blog][Advancing Responsible AI with Gemma][Gemma Scope][ShieldGemma][Gemma-2-9B-Chinese-Chat]
• Gemma 3 Technical Report, Gemma Team, 2025. [blog][paper][Gemma 3n][Gemma 4][Gemma 4 Technical Report][DiffusionGemma][DiffusionGemma Technical Report]
• GPT-4 Technical Report, OpenAI, arxiv 2023. [blog][paper]
• GPT-4V(ision) System Card, OpenAI, OpenAI blog 2023. [paper][GPT-4o][GPT-4o System Card]
• gpt-oss-120b & gpt-oss-20b Model Card, OpenAI, arxiv 2025. [paper][gpt-oss][OpenAI Harmony][Deliberative Alignment][From GPT-2 to gpt-oss]
• Sparks of Artificial General Intelligence_Early experiments with GPT-4, Bubeck et al., arxiv 2023. [paper]
• The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision), Yang et al., arxiv 2023. [paper][guidance]
• LaMDA: Language Models for Dialog Applications, Thoppilan et al., arxiv 2022. [paper][LaMDA-rlhf-pytorch]
• LLaMA: Open and Efficient Foundation Language Models, Touvron et al., arxiv 2023. [paper][code][llama.cpp][ollama][llamafile]
• Llama 2: Open Foundation and Fine-Tuned Chat Models, Touvron et al., arxiv 2023. [paper][code][llama2.c][lit-llama][litgpt]
• The Llama 3 Herd of Models, Llama Team, AI @ Meta, 2024. [blog][paper][code][llama-models][llama-recipes][LLM Adaptation][Llama-Nemotron: Efficient Reasoning Models][llama3-from-scratch][nano-llama31][minimind][felafax][5-Dollar LLM]
• Llama 3.2: Revolutionizing edge AI and vision with open, customizable models, 2024. [blog][model][llama-stack][llama-stack-apps][lingua][llama-assistant][minimind-v][nanoVLM][Llama3.2-Vision-Finetune]
• The Llama 4 herd: The beginning of a new era of natively multimodal AI innovation, Llama Team, AI @ Meta, 2025. [blog][llama-models][J1][The Llama 4 Herd][Muse Spark][Introducing Muse Glimmer]
• TinyLlama: An Open-Source Small Language Model, Zhang et al., arxiv 2024. [paper][code][LiteLlama][MobiLlama][Steel-LLM][minimind][From Minimind to More][Train LLM From Scratch][The Smol Training Playbook][Cortex][tiny-llm-zh][SkyLadder]
• Stanford Alpaca: An Instruction-following LLaMA Model, Taori et al., Stanford blog 2023. [paper][code][Alpaca-Lora][OpenAlpaca]
• Mistral 7B, Jiang et al., arxiv 2023. [paper][code][model][mistral-finetune]
• OLMo: Accelerating the Science of Language Models, Groeneveld et al., ACL 2024. [paper][code][OLMo2 blog][OLMo2 paper][Olmo 3][Dolma Dataset][Molmo and PixMo][Molmo][Molmo2][Pangea][Marin][ZGCM-1]
• TÜLU 3: Pushing Frontiers in Open Language Model Post-Training, Lambert et al., arxiv 2024. [paper][code]
• Minerva: Solving Quantitative Reasoning Problems with Language Models, Lewkowycz et al., arxiv 2022. [paper]
• PaLM: Scaling Language Modeling with Pathways, Chowdhery et al., arxiv 2022. [paper][PaLM-pytorch][PaLM-rlhf-pytorch][PaLM]
• PaLM 2 Technical Report, Anil et al., arxiv 2023. [paper][AudioPaLM]
• PaLM-E: An Embodied Multimodal Language Model, Driess et al., arxiv 2023. [paper][code]
• T5: Exploring the limits of transfer learning with a unified text-to-text transformer, Raffel et al., Journal of Machine Learning Research 2020. [paper][code][t5-pytorch][t5-pegasus-pytorch][nanoT5][T5Gemma][T5Gemma 2]
• BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension, Lewis et al., ACL 2020. [paper][code]
• FLAN: Finetuned Language Models Are Zero-Shot Learners, Wei et al., ICLR 2022. [paper][code]
• Scaling Flan: Scaling Instruction-Finetuned Language Models, Chung et al., arxiv 2022. [paper][model][The Flan Collection]
• Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context, Dai et al., ACL 2019. [paper][code]
• XLNet: Generalized Autoregressive Pretraining for Language Understanding, Yang et al., NeurIPS 2019. [paper][code]
• WebGPT: Browser-assisted question-answering with human feedback, Nakano et al., arxiv 2021. [paper][MS-MARCO-Web-Search][WebAgent]
• Open Release of Grok-1, xAI, 2024. [blog][code][model][grok-prompts][modelscope][hpcai-tech/grok-1][dbrx][Command R+][Command A][snowflake-arctic]
• LLaDA: Large Language Diffusion Models, Nie et al., arxiv 2025. [paper][code][LLaDA 1.5][LLaDA2.X][LLaDA2.0-Uni][LLaDA-V][LLaDA-o][LLaDA MoE v2][SMDM][Diffusion-LLM-Papers][Diffusion-LM][BD3-LM][mdlm][Dream][DiffuLLaMA][d1][Gemini Diffusion][MMaDA][dLLM-RL][LaViDa][Diffusion vs. Autoregressive Language Models][DLLM-Survey][dKV-Cache][dLLM-cache][Fast-dLLM][dInfer][Seed Diffusion][SDAR][Open-dLLM][LLaDA Pretraining][dllm][SDLM][DiRL][WeDLM][d3LLM][DLLM-Searcher][Cola DLM][Embedded Language Flows]
• Jet-Nemotron: Efficient Language Model with Post Neural Architecture Search, Gu et al., arxiv 2025. [paper][code][NVIDIA Nemotron Nano 2][Nemotron Nano][Small Language Models are the Future of Agentic AI][Nemotron-Flash][Jet-RL]
• NVIDIA Nemotron 3: Efficient and Open Intelligenc, NVIDIA, arxiv 2025. [blog][paper][code][Nemotron 3 Nano][Nemotron 3 Super][Nemotron 3 Nano Omni][Nemotron 3 Ultra][NeMo][Nemotron-Cascade 2][Nemotron-Labs-Diffusion][ProRL-Agent-Server][NVIDIA Nemotron Model Reasoning Challenge][Progress Prize winning submission]

3.2 LLM Application

• A Watermark for Large Language Models, Kirchenbauer et al., arxiv 2023. [paper][code][MarkLLM][Watermarked_LLM_Identification][Awesome-LLM-Watermark][watermarks-remover]

• SynthID-Text: Scalable watermarking for identifying large language model outputs, Dathathri et al., Nature 2024. [paper][code][watermark-anything][VideoSeal][Image/Video Detection][Remove-AI-Watermarks]

• SeqXGPT: Sentence-Level AI-Generated Text Detection, Wang et al., EMNLP 2023. [paper][code][llm-detect-ai][detect-gpt][fast-detect-gpt][ImBD][MAGE]

• AlpaGasus: Training A Better Alpaca with Fewer Data, Chen et al., ICLR 2024. [paper][code]

• AutoMix: Automatically Mixing Language Models, Madaan et al., arxiv 2023. [paper][code]

• ChipNeMo: Domain-Adapted LLMs for Chip Design, Liu et al., arxiv 2023. [paper][semikong][circuit_training][semikong][Automating GPU Kernel Generation][CUDA-L1][VibeTensor][KernelGYM][CUDA Agent][Auto GPU Kernel][Kernel Design Agents]

• HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face, Shen et al., NeurIPS 2023. [paper][code]

• MemGPT: Towards LLMs as Operating Systems, Packer et al., arxiv 2023. [paper][code][Zep][zep-python][graphiti]

• UFO: A UI-Focused Agent for Windows OS Interaction, Zhang et al., arxiv 2024. [paper][code][UFO2][OSWorld][aguvis][Large Action Models]

• OS-Copilot: Towards Generalist Computer Agents with Self-Improvement, Wu et al., ICLR 2024. [paper][code][OS-Atlas][OS-Genesis][OSReward][SeeClick][WindowsAgentArena]

• AIOS: LLM Agent Operating System, Mei et al., arxiv 2024. [paper][code]

• DB-GPT: Empowering Database Interactions with Private Large Language Models, Xue et al., arxiv 2023. [paper][code][DocsGPT][privateGPT][localGPT]

• OpenChat: Advancing Open-source Language Models with Mixed-Quality Data, Wang et al., ICLR 2024. [paper][code]

• OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement, Zheng et al., arxiv 2024. [paper][code][code-interpreter][open-interpreter]

• Orca: Progressive Learning from Complex Explanation Traces of GPT-4, Mukherjee et al., arxiv 2023. [paper]

• PDFTriage: Question Answering over Long, Structured Documents, Saad-Falcon et al., arxiv 2023. [paper][[code]]

• Prompt2Model: Generating Deployable Models from Natural Language Instructions, Viswanathan et al., EMNLP 2023. [paper][code]

• Shepherd: A Critic for Language Model Generation, Wang et al., arxiv 2023. [paper][code]

• Alpaca: A Strong, Replicable Instruction-Following Model, Taori et al., Stanford Blog 2023. [paper][code]

• Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90% ChatGPT Quality*, Chiang et al., 2023. [blog][Chinese-Vicuna]

• WizardLM: Empowering Large Language Models to Follow Complex Instructions, Xu et al., ICLR 2024. [paper][code]

• WebCPM: Interactive Web Search for Chinese Long-form Question Answering, Qin et al., ACL 2023. [paper][code]

• WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences, Liu et al., KDD 2023. [paper][code][AutoWebGLM][WebRL][OpenWebRL][AutoCrawler][gpt-crawler][webllama][gpt-researcher][skyvern][Scrapegraph-ai][Crawl4AI][Firecrawl][crawlee-python][Agent-E][CyberScraper-2077][browser-use][agent-browser][BrowserOS][nova-act][ReaderLM-v2][Scrapling][Webwright]

• LLM4Decompile: Decompiling Binary Code with Large Language Models, Tan et al., arxiv 2024. [paper] [code]

• MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases, Liu et al., ICML 2024. [paper][code][MobileMoE][Awesome-LLMs-on-device]

• MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices, Chu et al., arxiv 2023. [paper][code][MobileVLM V2][BlueLM-V-3B][XiaoMi/mobilevlm]

• The Oscars of AI Theater: A Survey on Role-Playing with Language Models, Chen et al., arxiv 2024. [paper][code][RPBench-Auto][Hermes 3 Technical Report][From Persona to Personalization: A Survey on Role-Playing Language Agents][MMRole][OpenCharacter]

• Apple Intelligence Foundation Language Models, Gunter et al., arxiv 2024. [blog][paper][Gemini Intelligence]

• Controllable Text Generation for Large Language Models: A Survey, Liang et al., arxiv 2024. [paper][code][guidance][outlines][instructor][marvin][json_repair]

• [ray][dify][Coze Studio][academy][ant-ray][dask][TaskingAI][gpt4all][ollama][llama.cpp][mindsdb][bisheng][phidata][guidance][outlines][jsonformer][fabric][mem0][taipy][langflow]

• [awesome-llm-apps][fastc][Awesome-Domain-LLM][agents][ai-app-lab][llm-for-zotero]

• [chatgpt-on-wechat][dify-on-wechat][WeClone][LLM-As-Chatbot][NextChat][chatbox][cherry-studio][Odysseus][ChatWise][khoj][HuixiangDou][Streamer-Sales][Tianji][metahuman-stream][aiavatarkit][ai-getting-started][chatnio][VideoChat][livetalking]

• [OpenClaw][NanoClaw][nanobot][ClawTeam][ClawWork][CLI-Anything][OpenCLI][QwenPaw][NemoClaw][OpenShell][Hermes Agent][hermes-docs][Pi Agent Harness][Multica][Paperclip][Paseo][nanoMuse]

3.2.1 AI Agent

• LLM Powered Autonomous Agents, Lilian Weng, 2023. [blog][The Second Half][Language Agents][AI Agents for Beginners][LLMAgentPapers][LLM-Agents-Papers][awesome-language-agents][Awesome-Papers-Autonomous-Agent][GUI-Agents-Paper-List][ai-agent-white-paper][EMNLP 2024 Tutorial: Language Agents]

• A Survey on Large Language Model based Autonomous Agents, Wang et al., [paper][code][LLM-Agent-Paper-Digest][awesome-lifelong-llm-agent][Agentic Web]

• The Rise and Potential of Large Language Model Based Agents: A Survey, Xi et al., arxiv 2023. [paper][code][Advances and Challenges in Foundation Agents][Awesome-Foundation-Agents]

• Agent AI: Surveying the Horizons of Multimodal Interaction, Durante et al., arxiv 2024. [paper]

• Position Paper: Agent AI Towards a Holistic Intelligence, Huang et al., arxiv 2024. [paper]

• Adaptation of Agentic AI, Jiang et al., arxiv 2025. [paper][code][Toward Efficient Agents][Externalization in LLM Agents][Dive into Claude Code]

• AgentBench: Evaluating LLMs as Agents, Liu et al., ICLR 2024. [paper][code][VisualAgentBench][OSWorld][AgentGym][Agent-as-a-Judge][intellagent][Survey on Evaluation of LLM-based Agents][AgentRewardBench][TaskCraft][OAgents]

• Agents: An Open-source Framework for Autonomous Language Agents, Zhou et al., arxiv 2023. [paper][code][Symbolic Learning Enables Self-Evolving Agents]

• AutoAgents: A Framework for Automatic Agent Generation, Chen et al., IJCAI 2024. [paper][code]

• AgentTuning: Enabling Generalized Agent Abilities for LLMs, Zeng et al., ACL 2024. [paper][code]

• AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors, Chen et al., ICLR 2024. [paper][code]

• AppAgent: Multimodal Agents as Smartphone Users, Zhang et al., arxiv 2023. [paper][code][digirl][Android-Lab][AppAgentX][AgentCPM-GUI][AgentCPM]

• Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception, Wang et al., arxiv 2024. [paper][code][Mobile-Agent-v2][Mobile-Agent-v3][Mobile-Agent-v3.5][LiMAC][Mobile-Agent-E][Mobile-Agent-V][PC-Agent][UI-S1][mobile-use][X-OmniClaw][MobileGym]

• OmniParser for Pure Vision Based GUI Agent, Lu et al., arxiv 2024. [paper][code][GUI-Actor][Phi-Ground Tech Report][Agent-S][The Dawn of GUI Agent][ShowUI][ShowUI-π][ShowUI-Aloha][Aria-UI][aguvis][TinyClick][InfiGUIAgent][autoMate][Fara-7B][GELab-Zero][ClawGUI][Phi-Ground][KnowAct-GUIClaw]

• AutoGLM: Autonomous Foundation Agents for GUIs, Liu et al., arxiv 2024. [paper][code][CogAgent][Android-Lab][MobileRL][SCALECUA]

• UI-TARS: Pioneering Automated GUI Interaction with Native Agents, Qin et al., arxiv 2025. [paper][code][UI-TARS-desktop][UI-TARS-2][Game-TARS][midscene][browser-use][BrowserOS][computer_use_ootb][Agent-S][open-operator][STEVE-R1][UI-R1][InfiGUI-R1][r1-computer-use][cua][GUI-G1][ZeroGUI][OpenCUA][ScaleCUA][TuriX-CUA][Computer Use Preview][EvoCUA][ToolCUA][Code2World][UI-Mate]

• Qwen-UI-Agent Technical Report: Toward Next-Generation Real-World Centric Foundation GUI Agents, MAI-UI Team, arxiv 2026. [paper][code][MobileWorld][Qwen-Planner-Agent][RecreationWorld][UI-Venus][Page Agent]

• PC Agent: While You Sleep, AI Works -- A Cognitive Journey into Digital World, He et al., arxiv 2024. [paper][code][PC-Agent-E][PPTAgent][PPT Master][PosterAgent][MultiAgentPPT][PresentAgent][GenericAgent]

• Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security, Li et al., arxiv 2024. [paper][code][OS-Agent-Survey][ACU][Large Language Model-Brained GUI Agents: A Survey][LLM-Powered GUI Agents in Phone Automation][Aguvis][awesome-computer-use]

• AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation, Wu et al., arxiv 2023. [paper][code][AG2][RD-Agent][TinyTroupe][TaskWeaver][NLWeb][Magentic-UI][Microsoft Agent Framework]

• CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society, Li et al., NeurIPS 2023. [paper][code][crab][OASIS]

• OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation, Hu et al., arxiv 2025. [paper][code][AgentOrchestra][Eigent][Agent World]

• ChatDev: Communicative Agents for Software Development, Qian et al., ACL 2024. [paper][code][gpt-pilot][Scaling Large-Language-Model-based Multi-Agent Collaboration][ProactiveAgent][VideoClaw]

• MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework, Hong et al., ICLR 2024 Oral. [paper][code][OpenManus][OpenManus-RL][ReCode]

• ProAgent: From Robotic Process Automation to Agentic Process Automation, Ye et al., arxiv 2023. [paper][code]

• RepoAgent: An LLM-Powered Open-Source Framework for Repository-level Code Documentation Generation, Luo et al., arxiv 2024. [paper][code]

• Generative Agents: Interactive Simulacra of Human Behavior, Park et al., arxiv 2023. [paper][code][genagents][GPTeam][AI Town][WorldX][OneManCompany]

• CogAgent: A Visual Language Model for GUI Agents, Hong et al., CVPR 2024 Highlight. [paper][code][CogAgent][blog][AgentCPM-GUI]

• OpenAgents: An Open Platform for Language Agents in the Wild, Xie et al., arxiv 2023. [paper][code][OpenAgents]

• AutoAgent: A Fully-Automated and Zero-Code Framework for LLM Agents, Tang et al., arxiv 2025. [paper][code][Auto-Deep-Research]

• MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge, Fan et al., NeurIPS 2022 Outstanding Paper. [paper][code]

• Voyager: An Open-Ended Embodied Agent with Large Language Models, Wang et al., arxiv 2023. [paper][code][WebVoyager][OpenWebVoyager][PAE]

• Eureka: Human-Level Reward Design via Coding Large Language Models, Ma et al., ICLR 2024. [paper][code][DrEureka][MM-EUREKA]

• LEGENT: Open Platform for Embodied Agents, Cheng et al., ACL 2024. [paper][code][EmbodiedEval]

• Mind2Web: Towards a Generalist Agent for the Web, Deng et al., NeurIPS 2023. [paper][code][Mind2Web 2][AutoWebGLM]

• WebArena: A Realistic Web Environment for Building Autonomous Agents, Zhou et al., ICLR 2024. [paper][code][visualwebarena][agent-workflow-memory][WindowsAgentArena]

• SeeAct: GPT-4V(ision) is a Generalist Web Agent, if Grounded, Zheng et al., arxiv 2024. [paper][code][WebDreamer]

• Learning to Model the World with Language, Lin et al., ICML 2024. [paper][code]

• Cradle: Empowering Foundation Agents Towards General Computer Control, Tan et al., arxiv 2024. [paper][code]

• AgentScope: A Flexible yet Robust Multi-Agent Platform, Gao et al., arxiv 2024. [paper][code][AgentScope Runtime][AgentScope Java][agentscope-typescript][QwenPaw][MS-Agent][Ultron]

• AgentGym: Evolving Large Language Model-based Agents across Diverse Environments, Xi et al., arxiv 2024. [paper][code]

• Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence, Chen et al., arxiv 2024. [paper][code][iAgents][cooragent]

• CLASI: Towards Achieving Human Parity on End-to-end Simultaneous Speech Translation via LLM Agent, ByteDance Research, 2024. [paper][translation-agent]

• Automated Design of Agentic Systems, Hu et al., arxiv 2024. [paper][code][MaAS][Agent Zero][AgentK][AFlow][syftr][ASI-Arch]

• New tools for building agents, OpenAI, 2025. [blog][OpenAI Agents SDK][Agent Development Kit][Claude Agent SDK][openai-cua-sample-app][swarm][A practical guide to building agents][Customer Service Agents Demo][adk-python][agents-deep-research][Building effective agents][Writing effective tools for agents][How we built our multi-agent research system][Building multi-agent systems][Multi-agent coordination patterns][Don't Build Multi-Agents][Choosing the Right Multi-Agent Architecture][Context Engineering for AI Agents][Context Engineering][Dynamic context discovery][Self-summarization][Effective context engineering for AI agents][Building agents with the Claude Agent SDK][Advanced tool use][Unrolling the Codex agent loop][Harness engineering][Harness design][Awesome Harness Engineering][Learn Harness Engineering][Scaling Managed Agents]

• Equipping agents for the real world with Agent Skills, Anthropic, 2025. [blog][code][anthropics/skills][openai/skills][huggingface/skills][Building agents with Skills][A complete guide to building skills for Claude][Improving skill-creator][Awesome OpenClaw Skills]

• Agent Teams: Orchestrate teams of Claude Code sessions, Anthropic, 2026. [Claude Code Docs]

• SkillNet: Create, Evaluate, and Connect AI Skills, Liang et al., arxiv 2026. [paper][code][SkillRL][MemSkill][AutoSkill][XSkill][MagicSkills][Trace2Skill][Skill Self-Play][EvoSkill][SkillCraft][SkillClaw][SkillZero][Skill1][SkillOpt][SkillLens][Resource2Skill][SkillOpt-Lite][Meta-Harness][Agentic Harness Engineering]

• Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory, Chhikara et al., arxiv 2025. [paper][code][MemGPT][Agent Workflow Memory][A-mem][Rethinking Memory in AI][Memvid][Memory OS][Awesome AI Memory][MemAgent][MemOS][MIRIX][memU][LangMem][memori][A-MEM][LongMemEval][LightMem][Memory in the Age of AI Agents][Awesome-Memory-for-Agents][EverMemOS][SimpleMem][OpenViking][Claude-Mem][Supermemory][MemPalace][MemBrain][EverOS][TencentDB Agent Memory][memsearch][HMS][MindMemOS]

• Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution, Qiu et al., arxiv 2025. [paper][code][OpenAlita][DataRater][MCP-Zero][Self-Evolving-Agents][GEM][AgentEvolver][EvoMap Evolver][Hermes Agent][HyperAgents][GenericAgent][auto-harness][JIT-Agent]

• Seeing, Listening, Remembering, and Reasoning: A Multimodal Agent with Long-Term Memory, Long et al., arxiv 2025. [paper][code][WebExplorer][TeleMem][Gated Recurrent Memory for Long-Context Reasoning][Memory Intelligence Agent][Pask]

• Youtu-Agent: Scaling Agent Productivity with Automated Generation and Hybrid Policy Optimization, Shi et al., arxiv 2025. [paper][code][Training-Free GRPO][Youtu-VL][Youtu-Parsing][ContextPilot]

• MetaClaw: Just Talk -- An Agent That Meta-Learns and Evolves in the Wild, Xia et al., arxiv 2026. [paper][code][AutoResearchClaw][Agent0][SkillRL][MemSkill][SkillClaw][Memento-Skills]

• Qwen-AgentWorld: Language World Models for General Agents, Qwen Team, arxiv 2026. [paper][code][Terminal-Universe][Agent-World][True Agents Model the World][Environment-free Synthetic Data Generation for API-Calling Agents][EnvHarness]

• T1: Terminal Agent Reinforcement Learning for Long-Horizon Tasks, Yang et al., arxiv 2026. [paper][The Bitter Lesson Behind Building Agentic RL in Terminal Environments]

• Foundation Models in Robotics: Applications, Challenges, and the Future, Firoozi et al., arxiv 2023. [paper][code][Awesome-Implicit-NeRF-Robotics]

• Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI, Liu et al., arxiv 2024. [paper][code]

• RT-1: Robotics Transformer for Real-World Control at Scale, Brohan et al., arxiv 2022. [paper][code][IRASim]

• RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control, Brohan et al., arxiv 2023. [paper][Unofficial Implementation][RT-H: Action Hierarchies Using Language][RoboMamba]

• Open X-Embodiment: Robotic Learning Datasets and RT-X Models, Open X-Embodiment Collaboration, arxiv 2023. [paper][code][Safari SDK]

• Shaping the future of advanced robotics, Google DeepMind 2024. [blog][Gemini Robotics][Evaluating Gemini Robotics Policies in a Veo World Simulator][Gemini Robotics-ER 1.6]

• RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation, Wang et al., ICML 2024. [paper][code][Genesis World][RoboTwin]

• Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation, Wu et al., ICLR 2024. [paper][code][Moto][BridgeVLA]

• RL-GPT: Integrating Reinforcement Learning and Code-as-policy, Liu et al., arxiv 2024. [paper]

• Genie: Generative Interactive Environments, Bruce et al., ICML 2024 Best Paper. [paper][Genie 2][Genie 3][genie2-pytorch][TinyWorlds][GameNGen][GameGen-X][GameFactory][Unbounded][open-oasis][DIAMOND][WHAM][dreamerv3][AssistanceZero][MineWorld][Multiverse][Matrix-Game][Hunyuan-GameCraft-1.0][Game-TARS][NitroGen][solaris][GameWorld][PlayCoder][AI for Games]

• Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation, Fu et al., arxiv 2024. [paper][code][Hardware Code][Learning Code][UMI][humanplus][TeleVision][Surgical Robot Transformer][lifelike-agility-and-play][ReKep][Open_Duck_Mini][Learning Visual Parkour from Generated Images][ASAP][UniAct][CogACT][Berkeley-Humanoid-Lite]

• RoboVerse: Towards a Unified Platform, Dataset and Benchmark for Scalable and Generalizable Robot Learning, Geng et al., arxiv 2025. [paper][code][ViTacFormer]

• RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation, Liu et al., arxiv 2024. [paper][code][Video Prediction Policy][Humanoid-Gym][RoboMaster][OpenWBT][Humanoid-GPT][BridgeVLA][3D Diffusion Policy][MolmoB0T][tau-0-wm]

• Octo: An Open-Source Generalist Robot Policy, Ghosh et al., arxiv 2024. [paper][code][BodyTransformer][crossformer][VideoMimic]

• GRUtopia: Dream General Robots in a City at Scale, Wang et al., arxiv 2024. [paper][code][InternVLA-A-series][InternDataEngine]

• HPT: Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformers, Wang et al., NeurIPS 2024 Spotlight. [paper][code][GenSim][EmbodiedOneVision]

• MLLM as Retriever: Interactively Learning Multimodal Retrieval for Embodied Agents, Yue et al., arxiv 2024. [paper][SpatialLM][3D-R1][RynnEC]

• GR00T N1: An Open Foundation Model for Generalist Humanoid Robots, NVIDIA, arxiv 2025. [paper][code][IsaacLab][IsaacGymEnvs][OmniIsaacGymEnvs][MuJoCo Playground][DreamGen][MimicGen][Spirit-v1.5][TextOp][JDT Embodied Intelligence Infrastructure]

• RoboBrain 2.0 Technical Report, BAAI RoboBrain Team, arxiv 2025. [paper][code][RoboBrain][RoboBrain 2.5][RoboBrain-X0][RoboOS][GR-3 Technical Report][GR-RL][Robix][RLinf][RPent][UniLab][Wall-X][RoboOmni][GigaBrain-0][GigaWorld-0][GigaWorld-1][GigaWorld-Policy][RynnBrain][Ctrl-World][HY-Embodied][Hy-Embodied-0.5-VLA][Hy-Embodied-RxBrain-1.0][HumanEgo][RoboDojo][OpenDM][PhyAgentOS][GPT 6 Astra as an Embodied Policy][PhysBrain 1.5]

• Robot Learning: A Tutorial, Capuano et al., arxiv 2025. [paper][code][XLeRobot][Every-Embodied][World Model for Robot Learning]

• [LeRobot][Genesis World][DORA][awesome-ai-agents][IsaacLab][IsaacGymEnvs][OmniIsaacGymEnvs][Isaac-GR00T][Awesome-Robotics-3D][AimRT][agibot_x1_train][Agibot-World][unitree_IL_lerobot][unitree_rl_gym][UnifoLM-WMA-0][openpi]

• [AutoGPT][GPT-Engineer][AgentGPT][OpenManus][owl][AgenticSeek][langmanus][DeerFlow][JoyAgent-JDGenie][Open Claude Cowork][openwork][OpenWork]

• [BabyAGI][SuperAGI][OpenAGI]

• [open-interpreter][Homepage][rawdog][OpenCodeInterpreter]

• XAgent: An Autonomous Agent for Complex Task Solving, [blog][code]

• [crewAI][phidata][PraisonAI][llama_deploy][gpt-computer-assistant][agentic_patterns][pydantic-ai][PocketFlow][suna]

• [swarm][swarms][AgentStack][multi-agent-orchestrator][smolagents][agent-service-toolkit][agno][ANUS][AutoAgent][AgentIQ][Agent-Reach]

• [translation-agent][agent-zero][AgentK][evolving-agents][EvoAgentX][DGM][Twitter Personality][RD-Agent][TinyTroupe][Hello-Agents][Hermes Agent]

3.2.2 Academic

• Pangu Weather: Accurate medium-range global weather forecasting with 3D neural networks, Bi et al., Nature 2023. [paper][code][arxiv]

• Skilful nowcasting of extreme precipitation with NowcastNet, Zhang et al., Nature 2023. [paper][code][graphcast][OpenCastKit][GenCast][PhiFlow][cBottle][PhysicsNeMo][Earth2Studio]

• MatterGen: A generative model for inorganic materials design, Zeni et al., Nature 2025. [paper][code][mattersim]

• Galactica: A Large Language Model for Science, Taylor et al., arxiv 2022. [paper][code]

• K2: A Foundation Language Model for Geoscience Knowledge Understanding and Utilization, Deng et al., arxiv 2023. [paper][code][pdf_parser]

• GeoGalactica: A Scientific Large Language Model in Geoscience, Lin et al., arxiv 2024. [paper][code][sciparser][GeoGPT][Earth-Agent]

• BatteryML:An Open-source platform for Machine Learning on Battery Degradation, Zhang et al., ICLR 2024. [paper][code]

• EconAgent: Large Language Model-Empowered Agents for Simulating Macroeconomic Activities, Li et al., ACL 2024. [paper][code][Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives]

• Scientific Large Language Models: A Survey on Biological & Chemical Domains, Zhang et al., arxiv 2024. [paper][code][sciknoweval]

• SciGLM: Training Scientific Language Models with Self-Reflective Instruction Annotation and Tuning, Zhang et al., arxiv 2024. [paper][code]

• ChemLLM: A Chemical Large Language Model, Zhang et al., arxiv 2024. [paper][model]

• LangCell: Language-Cell Pre-training for Cell Identity Understanding, Zhao et al., ICML 2024. [paper][code][scFoundation]

• SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers, Pramanick et al., arxiv 2024. [paper][code]

• STORM: Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models, Shao et al., NAACL 2024. [paper][code][Co-STORM EMNLP 2024][WikiChat][kiroku][gpt-researcher][OmniThink]

• Automated Peer Reviewing in Paper SEA: Standardization, Evaluation, and Analysis, Yu et al., arxiv 2024. [paper][code][AgentReview][Researcher]

• AutoSurvey: Large Language Models Can Automatically Write Surveys, Wang et al., NeurIPS 2024. [paper][code][SurveyX][SurveyForge]

• OpenResearcher: Unleashing AI for Accelerated Scientific Research, Zheng et al., arxiv 2024. [paper][code][Paper Copilot][SciAgentsDiscovery][paper-qa][GraphReasoning]

• OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs, Asai et al., Nature 2026. [nature paper][arxiv paper][code][ollama-deep-researcher][PaSa][ScholarCopilot][Ai2 ScholarQA][ScholarSearch][DeepXiv-SDK]

• The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery, Lu et al., arxiv 2024. [nature][paper][code][AI-Scientist-v2][AI-Scientist-ICLR2025-Workshop-Experiment][Zochi Technical Report][hypothesis-generation][Towards an AI co-scientist][CodeScientist][TinyScientist][research-town][CMBAgent][Robin][NovelSeek][ToolUniverse][FARS][ARIS][Academic Research Skills][LabClaw][AutoResearchClaw][EurekaClaw][autoresearch][AI-Build-AI][DeepScientist][Claw AI Lab][Claude Scholar][ML Intern][EvoScientist][NanoResearch]

• Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers, Si et al., arxiv 2024. [paper][code][DeepInnovator]

• CoI-Agent: Chain of Ideas: Revolutionizing Research Via Novel Idea Development with LLM Agents, Li et al., arxiv 2024. [paper][code][AI-Researcher][Researcher]

• Agent Laboratory: Using LLM Agents as Research Assistants, Schmidgall et al., arxiv 2025. [paper][code][AgentRxiv][Curie][PaperGuru][Paper2Code][Paper2Poster][PosterGen][Paper2Agent][Paper2Video][Auto-Slides][Memslides][Paper2Slides][Paper2Any][Idea2Paper][Edit-Banana][AutoFigure-Edit][PaperBanana][paper-framework-figure-studio-pro][drawio-skill][Research Draw.io Diagram Skill][ResearchStudio]

• YuLan-OneSim: Towards the Next Generation of Social Simulator with Large Language Models, Wang et al., arxiv 2025. [paper][code][Social_Science][SocialAgent][game_theory][LLM-Economist][Scaling social science research][AgentSociety][MatrAIx]

• Intern-S1: A Scientific Multimodal Foundation Model, Intern-S1 Team, Shanghai AI Laboratory, arxiv 2025. [paper][code][Intern-S2-Mobius][Intern-S2-Preview][SciReason][InternAgent][Agents-A1][Chem-R][SciEvalKit][Awesome-Agent-Scientists][Awesome-Scientific-Datasets-and-LLMs][TTT-Discover][Innovator-VL][UniScientist][MLEvolve][AI Can Learn Scientific Taste][OpenAI4S][Accelerating Scientific Research with Gemini in the Real-World][Discovery Foundation Models]

• AI for Auto-Research: Roadmap & User Guide, Kong et al., arxiv 2026. [paper][code][autoresearch][uditgoenka/autoresearch][ARIS][Academic Research Skills][AutoResearchClaw][Arbor][spark-to-paper-skills][Measuring Autonomous AI Research][AutoDesign][AREX-Skill][Argus][ArgusAgent][SoL-Pi][ScienceBuddy]

• [Awesome-Scientific-Language-Models][gpt_academic][ChatPaper][scispacy][awesome-ai4s][xVal]

• [OpenDeepResearcher][node-DeepResearch][open-deep-research][open-deep-research blog][open_deep_research][deep-research][deep-research][Auto-Deep-Research][deep-searcher][local-deep-research][local-deep-researcher][open_deep_research][Agentic-Reasoning][Awesome-Deep-Research][DeepResearchAgent][Universal Deep Research]

3.2.3 Code

• Neural code generation, CMU 2024 Spring. [link]

• Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code, Zhang et al., arxiv 2023. [paper][Awesome-Code-LLM][MFTCoder][Awesome-Code-LLM][CodeFuse-muAgent][Awesome-Code-Intelligence]

• Source Code Data Augmentation for Deep Learning: A Survey, Zhuo et al., arxiv 2023. [paper][code]

• Large Language Model-Based Agents for Software Engineering: A Survey, Liu et al., arxiv 2024. [paper][code][Challenges and Paths Towards AI for Software Engineering]

• Codex: Evaluating Large Language Models Trained on Code, Chen et al., arxiv 2021. [paper][human-eval][CriticGPT][On scalable oversight with weak LLMs judging strong LLMs][OpenAI Codex CLI][AGENTS.md][Claude Code][Gemini CLI][Grok Build][GitHub Copilot][GitHub Copilot][OpenCode][Claude Code Proxy][Anthropic API][Learn Claude Code][nanocode][CC Switch][Claude HUD][Claw Code][claude-code-sourcemap][Claude Code Best][zread claude code][claude-howto][OpenHarness][Everything Claude Code][happy][OpenSpec][herdr]

• Code Llama: Open Foundation Models for Code, Rozière et al., arxiv 2023. [paper][code][model][Code World Model][llamacoder][CodeBERT]

• CodeGemma: Open Code Models Based on Gemma, CodeGemma Team, arxiv 2024. [blog][paper]

• AlphaCode: Competition-Level Code Generation with AlphaCode, Li et al., arxiv 2022. [paper][dataset][AlphaCode2_Tech_Report]

• CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Evaluations on HumanEval-X, Zheng et al., KDD 2023. [paper][code][CodeGeeX2][CodeGeeX4]

• CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis, Nijkamp et al., ICLR 2022. [paper][code]

• CodeGen2: Lessons for Training LLMs on Programming and Natural Languages, Nijkamp et al., ICLR 2023. [paper][code]

• CodeChain: Towards Modular Code Generation Through Chain of Self-revisions with Representative Sub-modules, Le et al., arxiv 2023. [paper][code]

• StarCoder: may the source be with you, Li et al., arxiv 2023. [paper][code][bigcode-project][model]

• StarCoder 2 and The Stack v2: The Next Generation, Lozhkov et al., 2024. [paper][code][starcoder.cpp]

• SelfCodeAlign: Self-Alignment for Code Generation, Wei et al., NeurIPS 2024. [paper][code]

• WizardCoder: Empowering Code Large Language Models with Evol-Instruct, Luo et al., ICLR 2024. [paper][code][WarriorCoder]

• Magicoder: Source Code Is All You Need, Wei et al., arxiv 2023. [paper][code]

• Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering, Ridnik et al., arxiv 2024. [paper][code][pr-agent][cover-agent]

• DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence, Guo et al., arxiv 2024. [paper][code]

• DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence, Zhu et al., CoRR 2024. [paper][code][DeepSeek-V2.5][Ling-Coder-lite]

• Qwen2.5-Coder Technical Report, Hui et al., arxiv 2024. [paper][code][CodeArena][CodeElo]

• Qwen3-Coder-Next Technical Report, Qwen Team, arxiv 2026. [blog][paper][code][Qwen Code][qwen-code-action][Qwen-MM-Plugins][iFlow cli][Kimi CLI][Kimi Code CLI][MiniMax CLI][MiniMax Code][ZCode]

• Seed-Coder: Let the Code Model Curate Data for Itself, ByteDance Seed, arxiv 2025. [paper][code][CURE][CodeContests+][Kimi-Dev][KAT-Coder-V2.5]

• OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models, Huang et al., ICLR 2025. [paper][code][dataset][opc_data_filtering][OpenCodeEval]

• If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents, Yang et al., arxiv 2024. [paper]

• Design2Code: How Far Are We From Automating Front-End Engineering?, Si et al., arxiv 2024. [paper][code][ScreenCoder]

• AutoCoder: Enhancing Code Large Language Model with AIEV-Instruct, Lei et al., arxiv 2024. [paper][code]

• XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL, Gao et al., arxiv 2024. [paper][code][XiYanSQL-QwenCoder][vanna][NL2SQL_Handbook][Spider2][WrenAI]

• SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering, Yang et al., arxiv 2024. [paper][code][mini SWE-agent][swe-bench-technical-report][CursorBench][SWE-smith][CodeR][Lingma-SWE-GPT][SWE-Gym][MarsCode Agent][SWE-Fixer][SWE-RL][SWE-Lancer][multi-swe-bench][SWE-bench-Live][CodeFuse-CGM][DeepSWE][DeepSWE][Skywork-SWE][SWE-Swiss][SWE-Bench Pro][SWE-Pruner][SWE-Universe][SWE-Master][Artificial Analysis Coding Agent Benchmarks]

• Agentless: Demystifying LLM-based Software Engineering Agents, Xia et al., arxiv 2024. [paper][code]

• BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions, Zhuo et al., arxiv 2024. [paper][code][BigCodeArena][LiveCodeBench][evalplus][BigOBench]

• OpenDevin: An Open Platform for AI Software Developers as Generalist Agents, Wang et al., arxiv 2024. [paper][code][open-operator][potpie][Code Graph Model]

• Kevin-32B: Multi-Turn RL for Writing CUDA Kernels, Baronio et al., Cognition AI blog. [blog][model][deepwiki][deepwiki-open][AI Documentation Generator]

• Planning In Natural Language Improves LLM Search For Code Generation, Wang et al., arxiv 2024. [paper][SRA-MCTS]

• HyperAgent: Generalist Software Engineering Agents to Solve Coding Tasks at Scale, Phan et al., arxiv 2024. [paper][code][Seeker][AutoKaggle][Large Language Models Orchestrating Structured Reasoning Achieve Kaggle Grandmaster Level][ML-Agent][MLE-Dojo][DeepAnalyze][ML-Master][DataMaster][tinyKaggleClaw]

• CodeDPO: Aligning Code Models with Self Generated and Verified Source Code, Zhang et al., arxiv 2024. [paper]

• FullStack Bench: Evaluating LLMs as Full Stack Coders, Liu et al., arxiv 2024. [paper][code][SandboxFusion][microsandbox][AIO Sandbox][LLM-in-Sandbox][trae-agent][BitsAI-CR][OpenSandbox][CubeSandbox][Agent Sandbox][EvoClaw]

• o1-Coder: an o1 Replication for Coding, Zhang et al., arxiv 2024. [paper][code]

• S*: Test Time Scaling for Code Generation, Li et al., arxiv 2025. [paper][code][DeepCoder][DeepSWE]

• Competitive Programming with Large Reasoning Models, OpenAI, arxiv 2025. [paper][SWE-Lancer][OpenCodeReasoning][OpenCodeReasoning-II][AceReason-Nemotron][AceReason-Nemotron 1.1]

• LocAgent: Graph-Guided LLM Agents for Code Localization, Chen et al., ACL 2025. [paper][code]

• DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation, Gong et al., arxiv 2025. [paper][code][Mercury][Stable-DiffCoder]

• DeepCode: Open Agentic Coding, Li et al., arxiv 2025. [paper][code][Open Coding Agents][CodeTracer][FastContext]

• Training a coding model to paint watercolours with TRL and OpenEnv, Sergio Paniego, 2026. [blog][Editable Visual Design]

• [Yi-Coder][aiXcoder-7B][codealpaca]

• [OpenDevin][devika][auto-code-rover][developer][aider][claude-engineer][SuperCoder][AIDE][vulnhuntr][devin.cursorrules][DeepSeek Engineer][Online RL for Cursor Tab][Easy-Vibe][Vibe Vibe]

• [screenshot-to-code][vanna][NL2SQL_Handbook][TAG-Bench][Spider2][WrenAI]

3.2.4 Financial Application

• DocLLM: A layout-aware generative language model for multimodal document understanding, Wang et al., arxiv 2024. [paper]

• DocGraphLM: Documental Graph Language Model for Information Extraction, Wang et al., arxiv 2023. [paper]

• FinBERT: A Pretrained Language Model for Financial Communications, Yang et al., arxiv 2020. [paper][Wiley paper][code][finBERT][valuesimplex/FinBERT]

• FinGPT: Open-Source Financial Large Language Models, Yang et al., IJCAI 2023. [paper][code]

• FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models, Yang et al., arxiv 2024. [paper][code]

• FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasets, Wang et al., arxiv 2023. [paper][code]

• Instruct-FinGPT: Financial Sentiment Analysis by Instruction Tuning of General-Purpose Large Language Models, Zhang et al., arxiv 2023. [paper][code]

• FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance, Liu et al., arxiv 2020. [paper][code]

• FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning, Liu et al., NeurIPS 2022. [paper][code]

• DISC-FinLLM: A Chinese Financial Large Language Model based on Multiple Experts Fine-tuning, Chen et al., arxiv 2023. [paper][code]

• A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalist, Zhang et al., arxiv 2024. [paper]

• XuanYuan 2.0: A Large Chinese Financial Chat Model with Hundreds of Billions Parameters, Zhang et al., arxiv 2023. [paper][code]

• Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications, Xie et al., arxiv 2024. [paper][code]

• StructGPT: A General Framework for Large Language Model to Reason over Structured Data, Jiang et al., arxiv 2023. [paper][code]

• Large Language Model for Table Processing: A Survey, Lu et al., arxiv 2024. [paper][llm-table-survey][table-transformer][Awesome-Tabular-LLMs][Awesome-LLM-Tabular][Tabular-Survey][Table-LLaVA][tablegpt-agent][TabSTAR][TableLLM][Table-R1][OmniSQL][ChartVLM][OmniCaptioner][LimiX]

• TabPFN: Accurate predictions on small data with a tabular foundation model, Hollmann et al., Nature 2024. [paper][code][TabPFN-TS][TabFM][Xiaomi-TabLDM]

• rLLM: Relational Table Learning with LLMs, Li et al., arxiv 2024. [paper][code]

• Data-Copilot: Bridging Billions of Data and Humans with Autonomous Workflow, Zhang et al., arxiv 2023. [paper][code]

• Data Interpreter: An LLM Agent For Data Science, Hong et al., arxiv 2024. [paper][code]

• AlphaFin: Benchmarking Financial Analysis with Retrieval-Augmented Stock-Chain Framework, Li et al., COLING 2024. [paper][code]

• LLMFactor: Extracting Profitable Factors through Prompts for Explainable Stock Movement Prediction, Wang et al., arxiv 2024. [paper][MIGA][QuantaAlpha][CogAlpha][AlphaLab][xalpha][AlphaCrafter]

• A Survey of Large Language Models in Finance (FinLLMs), Lee et al., arxiv 2024. [paper][code][Revolutionizing Finance with LLMs: An Overview of Applications and Insights]

• A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges, Nie et al., arxiv 2024. [paper][financial-datasets][LLMs-in-Finance]

• PEER: Expertizing Domain-Specific Tasks with a Multi-Agent Framework and Tuning Methods, Wang et al., arxiv 2024. [paper][code][Stockagent]

• Benchmarking Large Language Models on CFLUE -- A Chinese Financial Language Understanding Evaluation Dataset, Zhu et al., ACL 2024. [paper][code][Golden-Touchstone][financebench][OmniEval][FLAME][FinEval][CFBenchmark][MME-Finance][BizFinBench][MultiFinBen][FinSearchComp][StockBench][LiveTradeBench]

• MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model, Li et al., arxiv 2024. [paper][code][TwinMarket][HedgeAgents][MASS][DeepFund][R&D-Agent-Quant][TwinMarket]

• TradingAgents: Multi-Agents LLM Financial Trading Framework, Xiao et al., arxiv 2024. [paper][code][Trading-R1][FinanceHarness][Qlib][RD-Agent][AI Hedge Fund][TradingAgents-CN][QuantAgent][ValueCell][Alpha Arena][ROCKFLOW RockAlpha][AI-Trader][Vibe-Trading][AI AGENTS FOR TRADING][TradeTrap][Awesome Trading Agents][FinanceHarness Homepage][AI Berkshire][DojoAgents]

• Fino1: On the Transferability of Reasoning Enhanced LLMs to Finance, Qian et al., arxiv 2025. [paper][code][PIXIU][FLAG-Trader][FinAudio]

• Fin-R1: A Large Language Model for Financial Reasoning through Reinforcement Learning, Liu et al., arxiv 2025. [paper][code][FinRL-DeepSeek][Qwen DianJin][Recon][FinChain][Agentar-Fin-R1][FinSight]

• Kronos: A Foundation Model for the Language of Financial Markets, Shi et al., arxiv 2025. [paper][code][OpenBB][TradeFM]

• [gpt-investor][FinGLM][agentUniverse][gs-quant][stockbot-on-groq][Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN][openbb-agents][ai-hedge-fund][A_Share_investment_Agent][ai-financial-agent][Finance][AlphaLab][daily_stock_analysis]

3.2.5 Information Retrieval

• ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT, Khattab et al., SIGIR 2020. [paper][simbert][roformer-sim]

• ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction, Santhanam et al., NAACL 2022. [paper][code][RAGatouille][rerankers][SPLADE][Rankify][A Reproducibility Study of PLAID][Jina-ColBERT-v2][SearchLM]

• ColBERT-XM: A Modular Multi-Vector Representation Model for Zero-Shot Multilingual Information Retrieval, Louis et al., arxiv 2024. [paper][code][model]

• NCI: A Neural Corpus Indexer for Document Retrieval, Wang et al., NeurIPS 2022 Outstanding Paper. [paper][code][DSI-transformers][GDR EACL 2024 Oral]

• HyDE: Precise Zero-Shot Dense Retrieval without Relevance Labels, Gao et al., ACL 2023. [paper][code]

• Query2doc: Query Expansion with Large Language Models, Wang et al., EMNLP 2023. [paper][Query Expansion by Prompting Large Language Models]

• RankGPT: Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents, Sun et al., EMNLP 2023 Outstanding Paper. [paper][code][direct-rag-learning][GenRank]

• Large Language Models for Information Retrieval: A Survey, Zhu et al., arxiv 2023. [paper][code][YuLan-IR][A Survey of Conversational Search][A Survey of Model Architectures in Information Retrieval][A Survey of Query Optimization in Large Language Models][Improving Generalization in Intent Detection]

• Large Language Models for Generative Information Extraction: A Survey, Xu et al., arxiv 2023. [paper][code][UIE][NERRE][uie_pytorch]

• LLaRA: Making Large Language Models A Better Foundation For Dense Retrieval, Li et al., arxiv 2023. [paper][code]

• UniGen: A Unified Generative Framework for Retrieval and Question Answering with Large Language Models, Li et al., AAAI 2024. [paper]

• INTERS: Unlocking the Power of Large Language Models in Search with Instruction Tuning, Zhu et al., ACL 2024. [paper][code][ChatRetriever][fullrank]

• GenIR: From Matching to Generation: A Survey on Generative Information Retrieval, Li et al., arxiv 2024. [paper][code][Alipay Search]

• D2LLM: Decomposed and Distilled Large Language Models for Semantic Search, Liao et al., ACL 2024. [paper][code][CodeFuse-Embeddings]

• Preference Discerning with LLM-Enhanced Generative Retrieval, Paischer et al., arxiv 2024. [paper][Unifying Generative and Dense Retrieval for Sequential Recommendation]

• BM25S: Orders of magnitude faster lexical search via eager sparse scoring, Xing Han Lù, arxiv 2024. [paper][code][rank_bm25][Pyserini][Flash-KMeans]

• MindSearch: Mimicking Human Minds Elicits Deep AI Searcher, Chen et al., arxiv 2024. [paper][code][Search Engines in an AI Era][WebWalker][OpenSearch-VL]

• Vision Search Assistant: Empower Vision-Language Models as Multimodal Search Engines, Zhang et al., arxiv 2024. [paper][code][Smart Multi-Modal Search][M3DocRAG][Visualized BGE][OmniSearch][StreamRAG][VisRAG][LamRA][Towards Long-horizon Agentic Multimodal Search]

• MMSearch: Benchmarking the Potential of Large Models as Multi-modal Search Engines, Jiang et al., ICLR 2025. [paper][code][CoLLM]

• MLGym: A New Framework and Benchmark for Advancing AI Research Agents, Nathani et al., arxiv 2025. [paper][code]

• R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning, Song et al., arxiv 2025. [paper][code][R1-Searcher++][SimpleDeepSearcher][FORT-Searcher][Search-o1][WebThinker][LaSER][ReSearch][Auto-Deep-Research][deep-searcher]

• Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning, Jin et al., arxiv 2025. [paper][code][DeepRetrieval][s3][DeepResearcher][ZeroSearch][IKEA][LeReT][MMSearch-R1][SenseNova-MARS][ASearcher][MiroThinker][PokeeResearchOSS][Search Self-Play][SearchAgent-Zero][LongTraceRL]

• Open Deep Search: Democratizing Search with Open-source Reasoning Agents, Alzubi et al., arxiv 2025. [paper][code][Recursive Open Meta-Agents][DeepSearchAgent-Demo][OpenSeeker][ABSeeker][SearchOS][OpenSearch-VL][deep-searcher]

• WebThinker: Empowering Large Reasoning Models with Deep Research Capability, Li et al., NeurIPS 2025. [paper][code][DeepAgent][AgentFamily][SearchClaw][Chain-of-Agents]

• Tongyi DeepResearch: A New Era of Open-Source AI Researchers, DeepResearch Team, Tongyi Lab, 2025. [blog][paper][code][MiroThinker][DeerFlow][Co-Sight][Youtu-Agent][Agent Lightning][Deep Agents][Mini-Agent][Step-DeepResearch][REDSearcher][Iris][Marco-DeepResearch][LongCat-DeepResearch][IterResearch][QUEST][SearchSwarm]

• MiroThinker-1.7 & H1: Towards Heavy-Duty Research Agents via Verification, MiroMind Team, arxiv 2026. [paper][code][MiroFlow][MiroThinker][MiroEval][AgenticQwen]

• AgentCPM-Report: Interleaving Drafting and Deepening for Open-Ended Deep Research, Li et al., arxiv 2026. [paper][code][AgentCPM-GUI][Beyond Semantic Similarity]

• ZeroSearch: Incentivize the Search Capability of LLMs without Searching, Sun et al., arxiv 2025. [paper][code][MaskSearch][OmniSearch][WebAgent][VRAG-RL][SSRL][Dr. Zero]

• ReasonIR: Training Retrievers for Reasoning Tasks, Shao et al., arxiv 2025. [paper][code][Rank-R1][Rearank][TongSearch-QR][ReasonRank][Language Ranker][BGE_Reasoner][AgentIR]

• Vision-DeepResearch: Incentivizing DeepResearch Capability in Multimodal Large Language Models, Huang et al.,arxiv 2026. [paper][code][Vision-DeepResearch Benchmark][VideoDeepResearch][DeepImageSearch][HyperEyes]

• SIGIR-AP 2023 Tutorial: Recent Advances in Generative Information Retrieval [link]

• SIGIR 2024 Tutorial: Large Language Model Powered Agents for Information Retrieval [link]

• [search_with_lepton][LLocalSearch][FreeAskInternet][storm][searxng][Perplexica][rag-search][sensei][azure-search-openai-demo][Gemini-Search][deep-searcher]

• [similarities][text2vec][FlagEmbedding][leettools]

• [SearchEngine][elasticsearch][elasticsearch-labs][OpenSearch][HNSWLib][Tevatron][txtai][AutoGEO]

3.2.6 Math

• ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving, Gou et al., ICLR 2024. [paper][code]

• MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models, Yu et al., ICLR 2024. [paper][code][MathCoder]

• MathVista: Evaluating Math Reasoning in Visual Contexts with GPT-4V, Bard, and Other Large Multimodal Models, Lu et al., ICLR 2024 Oral. [paper][code][MathBench][OlympiadBench][Math-Verify][MathPile][DeepMath-103K][VCBench]

• InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning, Ying et al., arxiv 2024. [paper][code]

• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models, Shao et al., arxiv 2024. [paper][code][DeepSeek-Math-V2][Math-Shepherd][DeepSeek-Prover-V1.5][DeepSeek-Prover-V2][Kimina-Prover Preview][Goedel-Prover-V2][BFS-Prover][MPS-Prover][DeepTheorem][CriticLean][StepFun-Prover-Preview][Seed-Prover][OProver]

• Common 7B Language Models Already Possess Strong Math Capabilities, Li et al., arxiv 2024. [paper][code]

• ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline, Xu et al., arxiv 2024. [paper][code]

• AlphaMath Almost Zero: process Supervision without process, Chen et al., arxiv 2024. [paper][code]

• JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models, Zhou et al., NeurIPS 2024. [paper][code]

• Accessing GPT-4 level Mathematical Olympiad Solutions via Monte Carlo Tree Self-refine with LLaMa-3 8B, Zhang et al., arxiv 2024. [paper][code][LLaMA-Berry]

• Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models, Shi et al., arxiv 2024. [paper][code]

• We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?, Qiao et al., arxiv 2024. [paper][code][We-Math2.0][V-Thinker][URSA]

• MAVIS: Mathematical Visual Instruction Tuning, Zhang et al., arxiv 2024. [paper][code]

• Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement, Yang et al., arxiv 2024. [paper][code][Qwen2.5-Math-Demo][ProcessBench][SuperCorrect-llm][The Lessons of Developing Process Reward Models in Mathematical Reasoning][Confucius3-Math]

• R-CoT: Reverse Chain-of-Thought Problem Generation for Geometric Reasoning in Large Multimodal Models, Deng et al., arxiv 2024. [paper][code][alphageometry][AlphaGeometry2][AlphaEvolve][OpenEvolve][Gemini with Deep Think][MathCritique][PromptCoT][ShinkaEvolve]

• rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking, Guan et al., arxiv 2025. [paper][code][rStar-Coder][rStar2-Agent][PRIME]

• *Self-rewarding correction for mathematical reasoning, Xiong et al., arxiv 2025. [paper][code]

• AI Mathematical Olympiad - Progress Prize 1, Kaggle Competition 2024. [Numina 1st Place Solution][project-numina/aimo-progress-prize][How NuminaMath Won the 1st AIMO Progress Prize][NuminaMath-7B-TIR][AI achieves silver-medal standard solving International Mathematical Olympiad problems][Gemini with Deep Think][Gemini 2.5 Deep Think][IMO 2025 Problem Solver][AWorld]

• AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset, Moshkov et al., arxiv 2025. [paper][code][AI Mathematical Olympiad-Progress Prize 2][9th Place Solution][An Open Recipe for IMO Gold]

3.2.7 Medicine and Law

• A Survey of Large Language Models in Medicine: Progress, Application, and Challenge, Zhou et al., arxiv 2023. [paper][code][LLM-for-Healthcare][GMAI-MMBench]

• A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law, Chen et al., arxiv 2024. [paper][code]

• PMC-LLaMA: Towards Building Open-source Language Models for Medicine, Wu et al., arxiv 2024. [paper][code][MMedLM]

• HuatuoGPT, towards Taming Language Model to Be a Doctor, Zhang et al., arxiv 2023. [paper][code][HuatuoGPT-II][Medical_NLP][Zhongjing][MedicalGPT][huatuogpt-vision][Chain-of-Diagnosis][BianCang][Llama3-OpenBioLLM-70B][CareGPT][HealthGPT]

• HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs, Chen et al., arxiv 2024. [paper][code][MedVLM-R1][m1][MedReason][X-Reasoner][AlphaMed][Lingshu][Hulu-Med][ReasonMed][MedResearcher-R1][ReasonMed][DeepRare]

• Chatlaw: A Multi-Agent Collaborative Legal Assistant with Knowledge Graph Enhanced Mixture-of-Experts Large Language Model, Cui et al., arxiv 2023. [paper][code][HK-O1aw]

• DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services, Yue et al., arxiv 2023. [paper][code]

• DISC-MedLLM: Bridging General Large Language Models and Real-World Medical Consultation, Bao et al., arxiv 2023. [paper][code]

• BianQue: Balancing the Questioning and Suggestion Ability of Health LLMs with Multi-turn Health Conversations Polished by ChatGPT, Chen et al., arxiv 2023. [paper][code][SoulChat2.0][smile]

• MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning, Tang et al., arxiv 2023. [paper][code][MedRAG][TxAgent][MedAgent-Pro]

• MEDITRON-70B: Scaling Medical Pretraining for Large Language Models, Chen et al., arxiv 2023. [paper][meditron]

• Med-PaLM: Large language models encode clinical knowledge, Singhal et al., Nature 2023. [paper][Unofficial Implementation]

• Capabilities of Gemini Models in Medicine, Saab et al., arxiv 2024. [paper]

• AMIE: Towards Conversational Diagnostic AI, Tu et al., arxiv 2024. [paper][AMIE-pytorch]

• Apollo: Lightweight Multilingual Medical LLMs towards Democratizing Medical AI to 6B People, Wang et al., arxiv 2024. [paper][code][Medical_NLP]

• AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction Simulator, Fan et al., COLING 2025. [paper][code][Agent Hospital][MentalArena][MING][EmoLLM]

• AI-Press: A Multi-Agent News Generating and Feedback Simulation System Powered by Large Language Models, Liu et al., COLING 2025. [paper][code]

• AgentCourt: Simulating Court with Adversarial Evolvable Lawyer Agents, Chen et al., arxiv 2024. [paper][code]

• On Domain-Specific Post-Training for Multimodal Large Language Models, Cheng et al., ICLR 2024. [paper][model]

• Efficient Medical VIE via Reinforcement Learning, Liu et al., arxiv 2025. [paper][Baichuan-M1][Baichuan-M2-32B][Baichuan-M3-235B][MedGemma][MedGemma 1.5][MedASR]

• PLawBench: A Rubric-Based Benchmark for Evaluating LLMs in Real-World Legal Practice, Shi et al., arxiv 2026. [paper][code]

• LawThinker: A Deep Research Legal Agent in Dynamic Environments, Yang et al., arxiv 2026. [paper][code][Legal-world]

• [Awesome-LegalAI-Resources][LexiLaw][LexEval][LawBench]

• [alphafold3][alphafold][RoseTTAFold][RFdiffusion][AlphaGenome][GPT‑Rosalind][claude-protein-binder-design][uplifting biomolecular modeling]

• [openfold][alphafold3-pytorch][alphagenome][Protenix][AlphaFold3][Ligo-Biosciences/AlphaFold3][LucaOne][esm][AlphaPPImd][visual-med-alpaca][chai-lab][evo][evo2][AIRS][OpenBioMed][BioEmu][Accelerating life sciences research][SimpleFold][IntelliFold]

3.2.8 Recommend System

• DIN: Deep Interest Network for Click-Through Rate Prediction, Zhou et al., KDD 2018. [paper][code][DIEN][x-deeplearning]

• MMoE: Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts, Ma et al., KDD 2018. [paper][DeepCTR-Torch][pytorch-mmoe]

• Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5), Geng et al., arxiv 2022. [paper][unofficial code][OpenP5]

• TIGER: Recommender Systems with Generative Retrieval, Rajput et al., NeurIPS 2023. [paper][Methodologies for Improving Modern Industrial Recommender Systems][Sparse Meets Dense][RQ-VAE-Recommender]

• Unifying Large Language Models and Knowledge Graphs: A Roadmap, Pan et al., arxiv 2023. [paper]

• YuLan-Rec: User Behavior Simulation with Large Language Model based Agents, Wang et al., arxiv 2023. [paper][code][Scaling Law of Large Sequential Recommendation Models]

• SSLRec: A Self-Supervised Learning Framework for Recommendation, Ren et al., WSDM 2024 Oral. [paper][code][Awesome-SSLRec-Papers]

• RLMRec: Representation Learning with Large Language Models for Recommendation, Ren et al., WWW 2024. [paper][code]

• LLMRec: Large Language Models with Graph Augmentation for Recommendation, Wei et al., WSDM 2024 Oral. [paper][code][EasyRec][SLMRec]

• XRec: Large Language Models for Explainable Recommendation, Ma et al., arxiv 2024. [paper][code][SelfGNN]

• Agent4Rec_On Generative Agents in Recommendation, Zhang et al., SIGIR 2024. [paper][code][AlphaRec]

• LLM-KERec: Breaking the Barrier: Utilizing Large Language Models for Industrial Recommendation Systems through an Inferential Knowledge Graph, Zhao et al., arxiv 2024. [paper]

• Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations, Zhai et al., ICML 2024. [paper][code][ExFM][Bending the Scaling Law Curve][CORAL][KuaiFormer][Transformers4Rec][TorchRec][LlamaRec][RecIS][Generative Reasoning Re-ranker]

• OneRec Technical Report, OneRec Team, arxiv 2025. [OneRec Technical Report][OneRec-V2 Technical Report][OpenOneRec][OneRec][OneRec-Think][OneReason][OneSearch][OneSearch Family][OneSug][UniSearch][UniDex][MTGR][MTGR blog][HierGR][MiniOneRec][GR4AD][AgentX]

• Wukong: Towards a Scaling Law for Large-Scale Recommendation, Zhang et al., ICML 2024. [paper][unofficial code][Towards An Efficient LLM Training Paradigm for CTR Prediction]

• RecAI: Leveraging Large Language Models for Next-Generation Recommender Systems, Lian et al., arxiv 2024. [paper][code][AdNanny]

• IDGenRec: LLM-RecSys Alignment with Textual ID Learning, Tan et al., SIGIR 2024. [paper][code]

• Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Application, Jia et al., arxiv 2024. [paper][NAR4Rec][HoME][Long-Sequence Recommendation Models Need Decoupled Embeddings][OneRec][OneRec Technical Report][OneRec-V2 Technical Report][OneSearch][MTGR][MIM][URM][UniROM][RecGPT Technical Report][REG4Rec][OnePiece][RecGPT-V2 Technical Report][RecGPT-V3 Technical Report][TSGR][Prompt Generation]

• NoteLLM-2: Multimodal Large Representation Models for Recommendation, Zhang et al., NeurIPS 2024. [paper][code][NoteLLM][SSD][PaRT][GenRank][UniGRF][GAVE][QP-OneModel][UniNote]

• HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modeling, Chen et al., arxiv 2024. [paper][code][monolith][LONGER][Interest Clock][RankMixer][OneTrans][HyFormer][TokenMixer-Large]

• STAR: A Simple Training-free Approach for Recommendations using Large Language Models, Lee et al., arxiv 2024. [paper][ActionPiece]

• Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation, Tang et al., arxiv 2025. [paper]

• [recommenders][X For You Feed Algorithm][Twitter's Recommendation Algorithm][Awesome-RSPapers][RecBole][RecSysDatasets][LLM4Rec-Awesome-Papers][Awesome-LLM-for-RecSys][Awesome-LLM4RS-Papers][Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising][DA-CL-4Rec][ReChorus][Transformers4Rec][torchrec][EasyRec][TorchEasyRec]

• [fun-rec][Torch-RecHub][RecommenderSystem][AI-RecommenderSystem][RecSysPapers][Algorithm-Practice-in-Industry][AlgoNotes]

3.2.9 Tool Learning

• Tool Learning with Foundation Models, Qin et al., arxiv 2023. [paper][code]

• Tool Learning with Large Language Models: A Survey, Qu et al., arxiv 2024. [paper][code]

• Toolformer: Language Models Can Teach Themselves to Use Tools, Schick et al., arxiv 2023. [paper][toolformer-pytorch][conceptofmind/toolformer][xrsrke/toolformer][Graph_Toolformer]

• ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs, Qin et al., ICLR 2024 Spotlight. [paper][code][StableToolBench]

• Gorilla: Large Language Model Connected with Massive APIs, Patil et al., arxiv 2023. [paper][code][OpenAI function calling]

• HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face, Shen et al., NeurIPS 2023. [paper][code][EasyTool]

• GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction, Yang et al., arxiv 2023. [paper][code]

• RestGPT: Connecting Large Language Models with Real-World RESTful APIs, Song et al., arxiv 2023. [paper][code]

• LLMCompiler: An LLM Compiler for Parallel Function Calling, Kim et al., ICML 2024. [paper][code][TinyAgent]

• Large Language Models as Tool Makers, Cai et al, arxiv 2023. [paper][code][trove][CREATOR]

• ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases Tang et al., arxiv 2023. [paper][code][ToolQA][toolbench][MetaTool Benchmark]

• ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search, Zhuang et al., arxiv 2023. [paper][[code]]

• Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models, Lu et al., NeurIPS 2023. [paper][code]

• ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios, Ye et al., arxiv 2024. [paper][code]

• AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls, Du et al., arxiv 2024. [paper][code]

• LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error, Wang et al., arxiv 2024. [paper][code]

• What Are Tools Anyway? A Survey from the Language Model Perspective, Wang et al., arxiv 2024. [paper]

• ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilities, Lu et al., arxiv 2024. [paper][code][API-Bank][ToolHop][ComplexFuncBench][ToolRet][Toolathlon]

• Re-Invoke: Tool Invocation Rewriting for Zero-Shot Tool Retrieval, Chen et al., arxiv 2024. [paper][OctoTools]

• ToolACE: Winning the Points of LLM Function Calling, Liu et al., arxiv 2024. [paper][ToolGen]

• Hammer: Robust Function-Calling for On-Device Language Models via Function Masking, Lin et al., arxiv 2024. [paper][code][LoopTool]

• MCP: Introducing the Model Context Protocol, Anthropic 2024. [blog][code][Documentation][OpenAI Agents SDK][mcp-for-beginners][How I Finally Understood MCP][FastMCP][MCP.so][mcpagents][ModelScope MCP][mcp-agent][awesome-mcp-servers][Awesome-MCP-ZH][mcp][ScaleMCP][A2A][adk-python][MiniMax-MCP][MCP-Universe][MCP-Bench][MCPMark][Agent Skills Marketplace][Awesome LLM Skills][open-agent-skills][Superpowers][Planning with Files][Awesome Claude Skills][gstack][mattpocock/skills][Humanize][infra-skills][Awesome OpenClaw Skills][colleague-skill][nuwa-skill][wdkns-skills]

• MCP-Zero: Proactive Toolchain Construction for LLM Agents from Scratch, Fei et al., arxiv 2025. [paper][code]

• ToRL: Scaling Tool-Integrated RL, Li et al., arxiv 2025. [paper][code][ReCall][ReTool][ToolRL][OTC][Improving Multi-Turn Tool Use with RL][OpenThinkIMG][VTool-R1][Tool-Star][Tool-N1][ZeroTIR][VerlTool][ARPO][Tool-Star][Understanding Tool-Integrated Reasoning][SimpleTIR][AgentFlow][ToolOrchestra][FTRL][EnvFactory]

• [functionary][ToolLearningPapers][awesome-tool-llm][agents-json][langgraph-bigtool][octotools][Hermes-Function-Calling]

3.3 LLM Technique

• How to Train Really Large Models on Many GPUs, Lilian Weng, 2021. [blog][The Ultra-Scale Playbook]

• Training great LLMs entirely from ground zero in the wilderness as a startup, Yi Tay, 2024. [blog][What happened to BERT & T5? On Transformer Encoders, PrefixLM and Denoising Objectives][New LLM Pre-training and Post-training Paradigms]

• Understanding LLMs: A Comprehensive Overview from Training to Inference, Liu et al., arxiv 2024. [paper]

• [Awesome-LLM-System-Papers][awesome-production-llm][Awesome-MLSys-Blogger][Awesome-ML-SYS-Tutorial][how-to-learn-deep-learning-framework][PKU-DAIR/Starter-Guide][open-infra-index][CutlassAcademy][Triton-Puzzles][CUDA-Learn-Notes][AIInfra][AI-Infra-Auto-Driven-SKILLS][ai-infra-book]

• GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism, Huang et al., NeurIPS 2019. [paper][Parameter Server OSDI 2014][ps-lite][Zero Bubble Pipeline Parallelism][DualPipe]

• Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism, Shoeybi et al., arxiv 2019. [paper][code][Megatron-2][megatron sequence parallelism][Scaling Language Model Training to a Trillion Parameters Using Megatron][picotron][nanotron][DeepEP]

• ZeRO: Memory Optimizations Toward Training Trillion Parameter Models, Rajbhandari et al., arxiv 2019. [blog][paper][DeepSpeed][FSDP][pytorch-fsdp]

• Pathways: Asynchronous Distributed Dataflow for ML, Barham et al., MLSys 2022. [paper][blog]

• Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training, Li et al., ICPP 2023. [paper][code][Sequence Parallelism]

• MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs, Jiang et al., NSDI 2024. [paper][veScale][MegaScale-Infer][MegaScale-MoE][DistTrain][InfiniteHBD][blog][Parameter Server OSDI 2014][ps-lite][ByteCheckpoint][HybridFlow][ByteRobust][veScale-FSDP]

• Revisiting Parameter Server in LLM Post-Training, Wan et al., ICLR 2026. [paper][code][Parameter Server OSDI 2014][ps-lite]

• A Theory on Adam Instability in Large-Scale Machine Learning, Molybog et al., arxiv 2023. [paper][Moonlight][Practical Efficiency of Muon for Pretraining]

• Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer, Yang et al., arxiv 2022. [paper][code][blog][Scaling Diffusion Transformers Efficiently via μP][Spectral Condition for μP under Width-Depth Scaling][DataDecide][µP for MoE]

• Loss Spike in Training Neural Networks, Zhang et al., arxiv 2023. [paper]

• Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling, Biderman et al., arxiv 2023. [paper][code]

• Continual Pre-Training of Large Language Models: How to (re)warm your model, Gupta et al., [paper]

• FLM-101B: An Open LLM and How to Train It with $100K Budget, Li et al., arxiv 2023. [paper][model][Tele-FLM]

• Instruction Tuning with GPT-4, Peng et al., arxiv 2023. [paper][code]

• DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines, Khattab et al., arxiv 2023. [paper][code][textgrad][appl][okhat/blog][PromptWizard][SPO][TPO][Text2Grad][Llama Prompt Ops][Promptomatix][Promptify]

• Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training, Feng et al., ICML 2024. [paper][code][Natural-language-RL]

• OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning, Ye et al., arxiv 2024. [paper][code]

• Arcee's MergeKit: A Toolkit for Merging Large Language Models, Goddard et al., EMNLP 2024. [paper][code][DistillKit][A Survey on Collaborative Strategies in the Era of Large Language Models][Model Merging Survey][FuseAI][MergeLM][Long-to-Short-via-Model-Merging][Model Merging in Pre-training][LLM Souping][DELLA-Merging]

• A Survey on Self-Evolution of Large Language Models, Tao et al., arxiv 2024. [paper][code][Awesome-Self-Evolving-Agents]

• Adam-mini: Use Fewer Learning Rates To Gain More, Zhang et al., arxiv 2024. [paper][code][Adam][AdamW]

• Muon: An optimizer for hidden layers in neural networks, Keller Jordan, 2024. [blog][code][modded-nanogpt]

• RouteLLM: Learning to Route LLMs with Preference Data, Ong et al., arxiv 2024. [paper][code][RouterDC][masrouter][RouterEval][Arch-Router][AvengersPro][Router-R1][LLMRouter][ClawXRouter][SkillRouter][Introducing Cursor Router][TinyRouter]

• Instruction Pre-Training: Language Models are Supervised Multitask Learners, Cheng et al., arxiv 2024. [paper][code]

• OpenDiLoCo: An Open-Source Framework for Globally Distributed Low-Communication Training, Jaghouar et al., arxiv 2024. [paper][code][Prime][DiLoCo][DisTrO][Streaming DiLoCo][Eager Updates For Overlapped Communication and Computation in DiLoCo][Scaling Laws for DiLoCo][Decoupled DiLoCo]

• JailbreakZoo: Survey, Landscapes, and Horizons in Jailbreaking Large Language and Vision-Language Models, Jin et al., arxiv 2024. [paper][code][jailbreak_llms][llm-attacks][Awesome-Jailbreak-on-LLMs][Constitutional Classifiers]

• LLM-Pruner: On the Structural Pruning of Large Language Models, Ma et al. NeurIPS 2023. [paper][code][Awesome-Efficient-LLM]

• LLM Pruning and Distillation in Practice: The Minitron Approach, Sreenivas et al., arxiv 2024. [paper][code][distillm][llm_distillation_playbook][EasyDistill][RLT]

• Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning, An et al., arxiv 2024. [paper][code][open-infra-index][Parameter Server OSDI 2014][ps-lite]

• LLM Post-Training: A Deep Dive into Reasoning Large Language Models, Kumar et al., arxiv 2025. [paper][code][A Survey on Post-training of Large Language Models][Sailing AI by the Stars][Agentic Reinforcement Learning][Awesome-RL-for-LRMs][Unify-Post-Training][Post-training 101][Awesome-Rubrics][Rubrics_Survey][When Speed Kills Stability: Demystifying RL Collapse from the Training-Inference Mismatch]

• VeOmni: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo, Ma et al., arxiv 2025. [paper][code]

• [wandb][