LLM Reasoning

LLM: Large Language Model

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Overview

This field asks how language models can carry out multi-step inference across mathematics, coding, logic, science, and real-world tasks, and how to tell robust reasoning from pattern matching. Common approaches include chain-of-thought prompting, self-consistency and tree search at inference time, tool use and symbolic verification, and post-training with supervised traces, reinforcement learning from verifiable rewards, or process feedback. Researchers are also exploring latent and recurrent computation to reduce reliance on long written traces, alongside benchmarks that test compositionality, robustness, and long-horizon execution. A central tension is that more computation can improve accuracy but raise cost, while plausible explanations and correct final answers do not by themselves establish faithful, reliable reasoning.

Latest papers

CardsList

931 papers105 papers in the last four weeks, up 27% on the four weeks before. 0.6% of all new papers.

  1. From 50% to Mastery in 3 Days: A Low-Resource SOP for Localizing Graduate-Level AI Tutors via Shadow-RAG

    Mar 21, 2026Zonglin Yang, J. -H. Xie, Lining Zhang +2Generative AI in EducationIntelligent Tutoring Systems

    School of Mechanics and Engineering Science, Peking University, Beijing, 100871, China · Readraft Intelligent Technology Co., Ltd., China · Graduate School of Education, Peking University, Beijing, 100871, China +1

  2. Grounded Chess Reasoning in Language Models via Master Distillation

    Mar 20, 2026Zhenwei Tang, Qianfeng Wen, Seth Grief-Albert +4LLM GroundingCoT Distillation

    Department of Computer Science, University of Toronto · Queen’s University · Coolwei AI Lab

  3. Learning Dynamic Belief Graphs for Theory-of-mind Reasoning

    Mar 20, 2026Ruxiao Chen, Xilei Zhao, Thomas J. Cova +2Computational Cognitive ModelingLLM Reasoning with Graphs

    Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, USA · Civil and Coastal Engineering, University of Florida, Gainesville, FL, USA · School of the Environment, Society & Sustainability, University of Utah, Salt Lake City, UT, USA +1

  4. FIPO: Eliciting Deep Reasoning with Future-KL Influenced Policy Optimization

    Mar 20, 2026Chiyu Ma, Shuo Yang, Kexin Huang +7RL for Language Model ReasoningRL for Language Models

    Qwen Pilot Team, Alibaba Group

  5. One Model, Two Minds: Task-Conditioned Reasoning for Unified Image Quality and Aesthetic Assessment

    Mar 20, 2026Wen Yin, Cencen Liu, Dingrui Liu +3Image Quality AssessmentUnified Multimodal Models

    University of Electronic Science and Technology of China, Chengdu, Sichuan, China · Jiigan Technology, Chengdu, Sichuan, China · Faculty of Information Technology, Monash University, Melbourne, Australia +1

  6. Can LLMs Prove Robotic Path Planning Optimality? A Benchmark for Research-Level Algorithm Verification

    Mar 19, 2026Zhengbang Yang, Md. Tasin Tazwar, Minghan Wei +1Mathematical Reasoning BenchmarksAutomated Theorem Proving

    George Mason University · Florida Atlantic University

  7. Correct Chains, Wrong Answers: Dissociating Reasoning from Output in LLM Logic

    Mar 19, 2026Abinav Rao, Sujan Rachuri, Nikhil VemuriLLM ReasoningLLM Evaluation

  8. Entropy trajectory shape predicts LLM reasoning reliability: A diagnostic study of uncertainty dynamics in chain-of-thought

    Mar 19, 2026Xinghao ZhaoLLM Uncertainty EstimationLLM Reliability

    Huazhong University of Science and Technology

  9. ZEBRAARENA: A Diagnostic Simulation Environment for Studying Reasoning-Action Coupling in Tool-Augmented LLMs

    Mar 19, 2026Wanjia Zhao, Ludwig Schmidt, Yejin Choi +3LLM EvaluationAI Agent Benchmarks

    Stanford University · Microsoft Research

  10. TARo: Token-level Adaptive Routing for LLM Test-time Alignment

    Mar 19, 2026Arushi Rai, Qiang Zhang, Hanqing Zeng +5Inference-Time Language Model AlignmentLLM Reasoning

    Meta · University of Pittsburgh · University of California, Berkeley

  11. Synthetic Data Generation for Training Diversified Commonsense Reasoning Models

    Mar 18, 2026Tianhui Zhang, Bei Peng, Danushka BollegalaSynthetic Data Generation for Language ModelsSynthetic Data Generation for LLM Agents

    University of Liverpool · University of Sheffield · Amazon

  12. RAWR: Reward Assignment Without Rollouts in Verifiable Domains

    Mar 18, 2026Corentin Royer, Anna Hedström, Debarun Bhattacharjya +3Process Reward ModelsReinforcement Learning with Verifiable Rewards

    International Business Machines · ETH AI Center · Lirio +1

  13. CoVerRL: Breaking the Consensus Trap in Label-Free Reasoning via Generator-Verifier Co-Evolution

    Mar 18, 2026Teng Pan, Yuchen Yan, Zixuan Wang +6Language Model Self-VerificationRL for Language Model Reasoning

    Zhejiang University · Baidu Inc.

  14. Temperature-Dependent Performance of Prompting Strategies in Extended Reasoning Large Language Models

    Mar 18, 2026Mousa Salah, Amgad MuneerLLM PromptingLLM Reasoning

    Department of Computer Engineering, Gujarat Technological University, India · The University of Texas MD Anderson Cancer Center, Texas, USA

  15. Draft-and-Prune: Improving the Reliability of Auto-formalization for Logical Reasoning

    Mar 18, 2026Zhiyu Ni, Zheng Liang, Liangcheng Song +4AutoformalizationLLM Reasoning

    University of California, Berkeley · Microsoft

  16. When and Why Does Unsupervised RL Succeed in Mathematical Reasoning? A Manifold Envelopment Perspective

    Mar 17, 2026Zelin Zhang, Fei Cheng, Chenhui ChuUnsupervised RLReinforcement Learning

    Kyoto University

  17. Breaking the Chain: A Causal Analysis of LLM Faithfulness to Intermediate Structures

    Mar 17, 2026Oleg Somov, Mikhail Chaichuk, Gleb Ershov +4LLM ReasoningCausal Interventions in Language Models

    AIRI · MIPT · HSE University +2

  18. Mask Is What DLLM Needs: A Masked Data Training Paradigm for Diffusion LLMs

    Mar 16, 2026Linrui Ma, Yufei Cui, Kai Han +1Diffusion Language ModelsBlockwise Diffusion Language Models

    Noah’s Ark Lab, Huawei Montreal, Canada & Beijing, China

  19. Can LLMs Model Incorrect Student Reasoning? A Case Study on Distractor Generation

    Mar 16, 2026Yanick Zengaffinen, Andreas Opedal, Donya Rooein +3LLM PromptingGenerative AI in Education

    1ETH Zürich · 2Bocconi University · University of Central Florida

  20. Understanding Reasoning in LLMs through Strategic Information Allocation under Uncertainty

    Mar 16, 2026Jeonghye Kim, Xufang Luo, Minbeom Kim +3LLM ReasoningLLM Self-Correction

    Microsoft Research · KAIST · Seoul National University

  21. SAGE: Multi-Agent Self-Evolution for LLM Reasoning

    Mar 16, 2026Yulin Peng, Xinxin Zhu, Chenxing Wei +4LLM ReasoningSelf-Training for Language Models

    College of Computer Science and Software Engineering, Shenzhen University, China · Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), China · School of Information Technology, Carleton University, Canada

  22. Why the Valuable Capabilities of LLMs Are Precisely the Unexplainable Ones

    Mar 16, 2026Quan ChengExplainable Artificial IntelligenceLLM Interpretability

    Tsinghua University

  23. MALicious INTent Dataset and Inoculating LLMs for Enhanced Disinformation Detection

    Mar 15, 2026Arkadiusz Modzelewski, Witold Sosnowski, Eleni Papadopulos +4Fake News DetectionIntent Classification

    University of Padua, Italy · Polish-Japanese Academy of Information Technology, Poland · NASK National Research Institute, Poland +1

  24. On the Nature of Attention Sink that Shapes Decoding Strategy in Omni-LLMs

    Mar 15, 2026Suho Yoo, Youngjoon Jang, Joon Son ChungAttention SinksMultimodal Large Language Models

    KAIST · VGG, University of Oxford

  25. GRPO and Reflection Reward for Mathematical Reasoning in Large Language Models

    Mar 14, 2026Zhijie WangSelf-Reflection in Language Model AgentsLLM Reasoning

    School of Computer Science and Engineering, Sun Yat-sen University(SYSU), Guangzhou, China

  26. Domain-Specialized Tree of Thought through Plug-and-Play Predictors

    Mar 14, 2026Xuanqi Gao, Haoyu Wang, Jun Sun +2LLM ReasoningTree of Thoughts

    Xi’an Jiaotong University, China · Singapore Management University, Singapore · University of Massachusetts at Amherst, United States

  27. Can We Trust LLMs on Memristors? Diving into Reasoning Ability under Non-Ideality

    Mar 14, 2026Taiqiang Wu, Yuxin Cheng, Chenchen Ding +5Language Model RobustnessLLM Reasoning

    The University of Hong Kong

  28. When Right Meets Wrong: Bilateral Context Conditioning with Reward-Confidence Correction for GRPO

    Mar 13, 2026Yu Li, Tian Lan, Zhengling QiRL for Language Model ReasoningGroup Relative Policy Optimization

    Department of Electrical and Computer Engineering, George Washington University · School of Business, George Washington University

  29. TDA-RC: Task-Driven Alignment for Knowledge-Based Reasoning Chains in Large Language Models

    Mar 13, 2026Jiaquan Zhang, Qigan Sun, Chaoning Zhang +11Efficient Language Model ReasoningLLM Reasoning

    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China · School of Computing, Kyung Hee University, Yongin-si, South Korea · School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China +3

  30. FGTR: Fine-Grained Multi-Table Retrieval via Hierarchical LLM Reasoning

    Mar 13, 2026Chaojie Sun, Bin Cao, Tiantian Li +3Table RetrievalLLM Reasoning

    Zhejiang University of Technology Hangzhou, China · University of Aberdeen Aberdeen, UK