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.
  31.18
• 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
• 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
• 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
• Learning From Mistakes Makes LLM Better Reasoner (2023)
  Shengnan An, Zexiong Ma, Zeqi Lin, et al.
  26.19
• Memgpt: Towards Llms As Operating Systems (2023)
  Charles Packer, Sarah Wooders, Kevin Lin, et al.
  25.76
• 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
• From Crowdsourced Data To High-quality Benchmarks: Arena-hard And Benchbuilder Pipeline (2024)
  Tianle Li, Wei-Lin Chiang, Evan Frick, et al.
  24.39
• 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
• 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
• 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
• 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.
  22.76
• 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
• From RAG To Memory: Non-parametric Continual Learning For Large Language Models (2025)
  Bernal Jiménez Gutiérrez, Yiheng Shu, Weijian Qi, 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
• Text-to-sql Empowered By Large Language Models: A Benchmark Evaluation (2023)
  Dawei Gao, Haibin Wang, Yaliang Li, et al.
  20.77
• Everything Of Thoughts: Defying The Law Of Penrose Triangle For Thought Generation (2023)
  Ruomeng Ding, Chaoyun Zhang, Lu Wang, et al.
  20.65
• Musr: Testing The Limits Of Chain-of-thought With Multistep Soft Reasoning (2023)
  Zayne Sprague, Xi Ye, Kaj Bostrom, et al.
  20.64
• Premise Order Matters In Reasoning With Large Language Models (2024)
  Xinyun Chen, Ryan A. Chi, Xuezhi Wang, et al.
  20.58
• Can Language Models Perform Robust Reasoning In Chain-of-thought Prompting With Noisy Rationales? (2024)
  Zhanke Zhou, Rong Tao, Jianing Zhu, et al.
  20.25
• Promptagent: Strategic Planning With Language Models Enables Expert-level Prompt Optimization (2023)
  Xinyuan Wang, Chenxi Li, Zhen Wang, et al.
  20.00
• Llms Achieve Adult Human Performance On Higher-order Theory Of Mind Tasks (2024)
  Winnie Street, John Oliver Siy, Geoff Keeling, et al.
  19.96
• Can Large Language Models Understand Real-world Complex Instructions? (2023)
  Qianyu He, Jie Zeng, Wenhao Huang, et al.
  19.91
• Extract, Define, Canonicalize: An Llm-based Framework For Knowledge Graph Construction (2024)
  Bowen Zhang, Harold Soh
  19.87
• Promptbreeder: Self-referential Self-improvement Via Prompt Evolution (2023)
  Chrisantha Fernando, Dylan Banarse, Henryk Michalewski, et al.
  19.77
• RAIN: Your Language Models Can Align Themselves Without Finetuning (2023)
  Yuhui Li, Fangyun Wei, Jinjing Zhao, et al.
  19.73
• Steering Knowledge Selection Behaviours In Llms Via Sae-based Representation Engineering (2024)
  Yu Zhao, Alessio Devoto, Giwon Hong, et al.
  19.66
• Remax: A Simple, Effective, And Efficient Reinforcement Learning Method For Aligning Large Language Models (2023)
  Ziniu Li, Tian Xu, Yushun Zhang, et al.
  19.63
• Followir: Evaluating And Teaching Information Retrieval Models To Follow Instructions (2024)
  Orion Weller, Benjamin Chang, Sean MacAvaney, et al.
  19.57
• Graph Neural Prompting With Large Language Models (2023)
  Yijun Tian, Huan Song, Zichen Wang, et al.
  19.56
• Improved Few-shot Jailbreaking Can Circumvent Aligned Language Models And Their Defenses (2024)
  Xiaosen Zheng, Tianyu Pang, Chao Du, et al.
  19.40
• Who Validates The Validators? Aligning Llm-assisted Evaluation Of LLM Outputs With Human Preferences (2024)
  Shreya Shankar, J. D. Zamfirescu-Pereira, Björn Hartmann, et al.
  19.31
• Meta Prompting For AI Systems (2023)
  Yifan Zhang, Yang Yuan, Andrew Chi-Chih Yao
  19.25
• Graphtranslator: Aligning Graph Model To Large Language Model For Open-ended Tasks (2024)
  Mengmei Zhang, Mingwei Sun, Peng Wang, et al.
  19.17
• From Persona To Personalization: A Survey On Role-playing Language Agents (2024)
  Jiangjie Chen, Xintao Wang, Rui Xu, et al.
  19.12
• DISTFLASHATTN: Distributed Memory-efficient Attention For Long-context Llms Training (2023)
  Dacheng Li, Rulin Shao, Anze Xie, et al.
  18.90
• Making Llama SEE And Draw With SEED Tokenizer (2023)
  Yuying Ge, Sijie Zhao, Ziyun Zeng, et al.
  18.81
• Codi-2: In-context, Interleaved, And Interactive Any-to-any Generation (2023)
  Zineng Tang, Ziyi Yang, Mahmoud Khademi, et al.
  18.73
• Alphamath Almost Zero: Process Supervision Without Process (2024)
  Guoxin Chen, Minpeng Liao, Chengxi Li, et al.
  18.61