Awesome In-Context Learning

Key papers

• React: Synergizing Reasoning And Acting In Language Models (2022)
  Shunyu Yao, Jeffrey Zhao, Dian Yu, et al.
  36.63
• BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022)
  BigScience Workshop: Teven Le Scao, Angela Fan, Christopher Akiki, et al.
  33.79
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning (2025)
  DeepSeek-AI et al.
  31.23
• Deja Vu: Contextual Sparsity For Efficient Llms At Inference Time (2023)
  Zichang Liu, Jue Wang, Tri Dao, et al.
  29.70
• Adaptive-rag: Learning To Adapt Retrieval-augmented Large Language Models Through Question Complexity (2024)
  Soyeong Jeong, Jinheon Baek, Sukmin Cho, et al.
  29.58
• Emergent Abilities Of Large Language Models (2022)
  Jason Wei, Yi Tay, Rishi Bommasani, et al.
  29.54
• RLAIF Vs. RLHF: Scaling Reinforcement Learning From Human Feedback With AI Feedback (2023)
  Harrison Lee, Samrat Phatale, Hassan Mansoor, et al.
  29.41
• Scaling Synthetic Data Creation With 1,000,000,000 Personas (2024)
  Tao Ge, Xin Chan, Xiaoyang Wang, et al.
  29.19
• Autogen: Enabling Next-gen LLM Applications Via Multi-agent Conversation (2023)
  Qingyun Wu, Gagan Bansal, Jieyu Zhang, et al.
  29.16
• Buffer Of Thoughts: Thought-augmented Reasoning With Large Language Models (2024)
  Ling Yang, Zhaochen Yu, Tianjun Zhang, et al.
  27.84
• Eureka: Human-level Reward Design Via Coding Large Language Models (2023)
  Yecheng Jason Ma, William Liang, Guanzhi Wang, et al.
  27.82
• Graph Of Thoughts: Solving Elaborate Problems With Large Language Models (2023)
  MacIej Besta, Nils Blach, Ales Kubicek, et al.
  27.79
• Chain-of-verification Reduces Hallucination In Large Language Models (2023)
  Shehzaad Dhuliawala, Mojtaba Komeili, Jing Xu, et al.
  27.71
• Duoattention: Efficient Long-context LLM Inference With Retrieval And Streaming Heads (2024)
  Guangxuan Xiao, Jiaming Tang, Jingwei Zuo, et al.
  27.44
• EASYTOOL: Enhancing Llm-based Agents With Concise Tool Instruction (2024)
  Siyu Yuan, Kaitao Song, Jiangjie Chen, et al.
  27.38
• The Reversal Curse: Llms Trained On "A Is B" Fail To Learn "B Is A" (2023)
  Lukas Berglund, Meg Tong, Max Kaufmann, et al.
  27.32
• Agentgym: Evolving Large Language Model-based Agents Across Diverse Environments (2024)
  Zhiheng Xi, Yiwen Ding, Wenxiang Chen, et al.
  27.20
• Gsm-symbolic: Understanding The Limitations Of Mathematical Reasoning In Large Language Models (2024)
  Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.
  27.04
• Lmsys-chat-1m: A Large-scale Real-world LLM Conversation Dataset (2023)
  Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.
  26.82
• Learning From Mistakes Makes LLM Better Reasoner (2023)
  Shengnan An, Zexiong Ma, Zeqi Lin, et al.
  26.19
• The Unlocking Spell On Base Llms: Rethinking Alignment Via In-context Learning (2023)
  Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, et al.
  26.03
• Memgpt: Towards Llms As Operating Systems (2023)
  Charles Packer, Sarah Wooders, Kevin Lin, et al.
  25.76
• Babilong: Testing The Limits Of Llms With Long Context Reasoning-in-a-haystack (2024)
  Yuri Kuratov, Aydar Bulatov, Petr Anokhin, et al.
  25.74
• Mindmap: Knowledge Graph Prompting Sparks Graph Of Thoughts In Large Language Models (2023)
  Yilin Wen, Zifeng Wang, Jimeng Sun
  25.51
• Teaching Large Language Models To Reason With Reinforcement Learning (2024)
  Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.
  25.08
• Reconcile: Round-table Conference Improves Reasoning Via Consensus Among Diverse Llms (2023)
  Justin Chih-Yao Chen, Swarnadeep Saha, Mohit Bansal
  24.61
• From Crowdsourced Data To High-quality Benchmarks: Arena-hard And Benchbuilder Pipeline (2024)
  Tianle Li, Wei-Lin Chiang, Evan Frick, et al.
  24.39
• Advancing Transformer Architecture In Long-context Large Language Models: A Comprehensive Survey (2023)
  Yunpeng Huang, Jingwei Xu, Junyu Lai, et al.
  24.27
• A Systematic Survey Of Prompt Engineering In Large Language Models: Techniques And Applications (2024)
  Pranab Sahoo, Ayush Kumar Singh, Sriparna Saha, et al.
  24.27
• Tell Your Model Where To Attend: Post-hoc Attention Steering For Llms (2023)
  Qingru Zhang, Chandan Singh, Liyuan Liu, et al.
  24.26
• Simulating Classroom Education With Llm-empowered Agents (2024)
  Zheyuan Zhang, Daniel Zhang-Li, Jifan Yu, et al.
  24.11
• Same Task, More Tokens: The Impact Of Input Length On The Reasoning Performance Of Large Language Models (2024)
  Mosh Levy, Alon Jacoby, Yoav Goldberg
  23.56
• Tool Learning With Large Language Models: A Survey (2024)
  Changle Qu, Sunhao Dai, Xiaochi Wei, et al.
  23.52
• Faithful Logical Reasoning Via Symbolic Chain-of-thought (2024)
  Jundong Xu, Hao Fei, Liangming Pan, et al.
  23.51
• Adapting Large Language Models By Integrating Collaborative Semantics For Recommendation (2023)
  Bowen Zheng, Yupeng Hou, Hongyu Lu, et al.
  23.45
• You Only Look At Screens: Multimodal Chain-of-action Agents (2023)
  Zhuosheng Zhang, Aston Zhang
  23.42
• Graph Chain-of-thought: Augmenting Large Language Models By Reasoning On Graphs (2024)
  Bowen Jin, Chulin Xie, Jiawei Zhang, et al.
  23.21
• Dyval: Dynamic Evaluation Of Large Language Models For Reasoning Tasks (2023)
  Kaijie Zhu, Jiaao Chen, Jindong Wang, et al.
  23.15
• Expel: LLM Agents Are Experiential Learners (2023)
  Andrew Zhao, Daniel Huang, Quentin Xu, et al.
  23.10
• Longllmlingua: Accelerating And Enhancing Llms In Long Context Scenarios Via Prompt Compression (2023)
  Huiqiang Jiang, Qianhui Wu, Xufang Luo, et al.
  23.08
• Fact, Fetch, And Reason: A Unified Evaluation Of Retrieval-augmented Generation (2024)
  Satyapriya Krishna, Kalpesh Krishna, Anhad Mohananey, et al.
  22.96
• Stepcoder: Improve Code Generation With Reinforcement Learning From Compiler Feedback (2024)
  Shihan Dou, Yan Liu, Haoxiang Jia, et al.
  22.83
• Cumulative Reasoning With Large Language Models (2023)
  Yifan Zhang, Jingqin Yang, Yang Yuan, et al.
  22.83
• Llms Can Easily Learn To Reason From Demonstrations Structure, Not Content, Is What Matters! (2025)
  Dacheng Li, Shiyi Cao, Tyler Griggs, et al.
  22.81
• Prompt Engineering A Prompt Engineer (2023)
  Qinyuan Ye, Maxamed Axmed, Reid Pryzant, et al.
  22.48
• Pose: Efficient Context Window Extension Of Llms Via Positional Skip-wise Training (2023)
  Dawei Zhu, Nan Yang, Liang Wang, et al.
  22.43
• How Do Large Language Models Acquire Factual Knowledge During Pretraining? (2024)
  Hoyeon Chang, Jinho Park, Seonghyeon Ye, et al.
  22.35
• MINT: Evaluating Llms In Multi-turn Interaction With Tools And Language Feedback (2023)
  Xingyao Wang, Zihan Wang, Jiateng Liu, et al.
  22.11
• Leave No Document Behind: Benchmarking Long-context Llms With Extended Multi-doc QA (2024)
  Minzheng Wang, Longze Chen, Cheng Fu, et al.
  22.07
• Large Language Model Cascades With Mixture Of Thoughts Representations For Cost-efficient Reasoning (2023)
  Murong Yue, Jie Zhao, Min Zhang, et al.
  22.06
• In-context Pretraining: Language Modeling Beyond Document Boundaries (2023)
  Weijia Shi, Sewon Min, Maria Lomeli, et al.
  21.97
• Rankrag: Unifying Context Ranking With Retrieval-augmented Generation In Llms (2024)
  Yue Yu, Wei Ping, Zihan Liu, et al.
  21.80
• In-context Vectors: Making In Context Learning More Effective And Controllable Through Latent Space Steering (2023)
  Sheng Liu, Haotian Ye, Lei Xing, et al.
  21.77
• List Items One By One: A New Data Source And Learning Paradigm For Multimodal Llms (2024)
  An Yan, Zhengyuan Yang, Junda Wu, et al.
  21.63
• Self-reflection In LLM Agents: Effects On Problem-solving Performance (2024)
  Matthew Renze, Erhan Guven
  21.59
• Link-context Learning For Multimodal Llms (2023)
  Yan Tai, Weichen Fan, Zhao Zhang, et al.
  21.31
• From RAG To Memory: Non-parametric Continual Learning For Large Language Models (2025)
  Bernal Jiménez Gutiérrez, Yiheng Shu, Weijian Qi, et al.
  21.27
• Llmlingua: Compressing Prompts For Accelerated Inference Of Large Language Models (2023)
  Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, et al.
  21.22
• PPTC Benchmark: Evaluating Large Language Models For Powerpoint Task Completion (2023)
  Yiduo Guo, Zekai Zhang, Yaobo Liang, et al.
  21.19
• RLEF: Grounding Code Llms In Execution Feedback With Reinforcement Learning (2024)
  Jonas Gehring, Kunhao Zheng, Jade Copet, et al.
  21.18