LLM Reasoning

LLM: Large Language Model

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68 papers in the last four weeks, up 143% on the four weeks before. 0.7% of all new papers.

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Improving Mathematical Reasoning Capabilities in Large Language Models via Reasoning Process Error Classification
Sep 14, 2026Runa Yoshida, Kosuke Nishida, Kyosuke NishidaLLM Prompting LLM Mathematical Reasoning
Human Informatics Labs., NTT, Inc.
Can LLMs in Draft-Verify-Revise Pipelines Resolve Deictic Ambiguity?
Sep 14, 2026Obinna I. EkekezieCoreference Resolution LLM Answer Verification
Cambridge Health Alliance, Cambridge, MA, United States of America. · Harvard Medical School, Boston, MA, United States of America.
Chopthin-Consensus Power Sampling: A Diversity-Preserving Approach to LLM Decoding
Sep 14, 2026Minoo Ahmadi, Seyedarmin Azizi, Erfan Baghaei Potraghloo +2Language Model Decoding LLM Inference
University of Southern California, Los Angeles, USA
Sampling via Decision-Flow: Training-Free Extraction of Improved Latent Reasoning Paths in Large Language Models
Sep 14, 2026Zhendong Mi, Shaoyi HuangInference-Time Search LLM Inference
Stevens Institute of Technology
Separating Engineering Reasoning from DEXPI Serialization in LLM-Based Greenfield Surface-Process Design: A Three-Case Study for Underground Gas Storage
Sep 14, 2026Qingchuan Zhu, Shuyue Tong, Pengju RenStructured Output Generation LLM Reasoning
Sinopec Petroleum Engineering Zhongyuan Co., Ltd., No. 33 Zhengguang North Street, Zhengdong New District, Zhengzhou, Henan, China · Xi’an Jiaotong University, No. 28 Xianning West Road, Xi’an, Shaanxi 710049, P.R. China
An Open Recipe for IMO Gold: Training Nemotron for Olympiad Mathematics
Sep 12, 2026Ivan Moshkov, Stephen Ge, George Armstrong +3Mathematical Reasoning Benchmarks Test-Time Scaling
NVIDIA
Can LLMs Follow Medical Expert Logic? A Benchmark for Hierarchical Logical Consistency in Risk-of-Bias Assessment
Sep 12, 2026Jiayu Huang, Zichen Tang, Qianhui Ling +2Reasoning Consistency in Language Models Clinical Language Model Evaluation
Beijing University of Posts and Telecommunications · Hypertension Center, Beijing Anzhen Hospital, Capital Medical University
Beyond Confidence: Stability-Aware Test-Time Adaptation for LLM Reasoning
Sep 12, 2026Bincheng Gu, Min Gao, Zongwei Wang +3Test-Time Adaptation LLM Reliability
Key Laboratory of Dependable Service Computing in Cyber Physical Society, Chongqing University, China · King’s College London, London, UK · Griffith University, Brisbane, Australia
Negative Self-Distillation: Learning to Reason by Avoiding Flaws
Sep 10, 2026Rongcan Pei, Zhepei Wei, Shuyao Xu +3Language Model Distillation Self-Distillation
Department of Computer Science, University of Virginia · Stanford University
Quantifying Logical Consistency in Transformers via Query-Key Alignment
Sep 10, 2026Eduard Tulchinskii, Anastasia Voznyuk, Laida Kushnareva +4Transformer Interpretability LLM Evaluation
Skolkovo Institute of Science and Technology · AI Foundation and Algorithm Lab · Moscow Institute of Physics and Technology +2
CompassOPD: Cross-Family On-Policy Distillation via Within-Family Likelihood Shifts
Sep 9, 2026Naibin Gu, Qingyi Si, Chenxu Yang +5Language Model Distillation On-Policy Distillation
Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China · School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China
Answer-Distribution Trajectories: A Stochastic-Dynamics View of LLM Reasoning
Sep 8, 2026Mar Gonzàlez I Català, Haitz Sáez de Ocáriz Borde, Davide Murari +3LLM Uncertainty Estimation LLM Reasoning
University of Cambridge · Harvey Mudd College
Difficulty-Adaptive Tree-Structured Policy Optimization for Expanding Reasoning Coverage in RLVR
Sep 8, 2026Youngjun Yu, Sanghwan Jang, Hwanjo YuRL for Language Model Reasoning RL Exploration
Pohang University of Science and Technology (POSTECH)
The Internal Anatomy of Strategic Choice in Large Language Models
Sep 7, 2026Vinícius Ferraz, Leon Houf, Enrico FerreaLLM Interpretability Strategic Reasoning Risks in Language Models
Institute of Management and KD2Lab, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany · Singularity AI Research, Singularity.Inc, Vienna, Austria · BrainSpot Labs, BrainSpot.AI, London, UK +2
Long-Horizon Language Model Reinforcement Learning via Progressive Point Matching
Sep 7, 2026Preston Fu, Kevin Frans, Oleh Rybkin +2Reinforcement Learning Reward Shaping
UC Berkeley · Carnegie Mellon University
Extremely Sparse Supervision Incentivizes Reasoning Ability
Sep 7, 2026Zhishuai Liu, Xingzi Xu, Mehmet Saygin Seyfioglu +2On-Policy Distillation Language Model Post-Training
Amazon, Seattle, WA 98109, USA · Duke University, Durham, NC 27708, USA
DODR: Deterministic Operator-Driven Reasoning in Latent Space
Sep 7, 2026Weicai Huang (Beijing MQPat Technologies, Co., Ltd.)Logical Reasoning Abductive Reasoning
Beijing MQPat Technologies, Co., Ltd.
GrowPage: On-Demand KV Budgeting for Efficient LLM Reasoning Serving
Sep 3, 2026Qiankun Ma, Yanjiang Zhou, Zinan Xiong +5LLM Inference KV Caching
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences · Pengcheng Laboratory · University of Chinese Academy of Sciences
It's the Problem, Not the Path: Budget and Difficulty Confounds in LLM Reasoning Trajectories
Sep 3, 2026Yigit Utku BulutLLM Evaluation Language Model Probing
Johannes Kepler University Linz
Language-encoded network topology enables large language models to reason about complex networks
Sep 3, 2026Ucchwas Talukder Utsha, Sakib Mostafa, James Zou +1Graph Representation Learning LLM Reasoning with Graphs
Department of Radiation Oncology, Stanford University, Stanford, California, USA · Department of Electrical Engineering, Stanford University, Stanford, California, USA · Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California, USA +1
Cliff: Learning Process Rewards from the First Mistake
Sep 2, 2026Peixuan Han, Runhui Wang, Ketan Ramaneti +3Reinforcement Learning with Verifiable Rewards LLM Reasoning
1Amazon Web Services · University of Illinois Urbana-Champaign
Large Language Models (LLMs) for Telecom Root Cause Analysis (RCA): A Structured Reasoning Framework for Evidence-Grounded Diagnosis
Sep 2, 2026Hao Zhou, Mandar Kulkarni, Hao Chen +3Root Cause Analysis LLM Reasoning
Jianzhong · Samsung Research America, Toronto, Ontario, ON M5E0C5 · Samsung Research America, Berkeley Heights, NJ 07922 USA +1
Knowledge Distillation During Mid-Training Favors Reasoning over Factual Recall
Sep 1, 2026Jacqueline He, Howard Yen, Shuyue Stella Li +9Language Model Distillation Factual Knowledge in Language Models
Meta AI · University of Washington · Princeton University
Latent Recurrent Thoughts: Recurrent Refinement of Proposed Latents for Reasoning with Frozen LLMs
Sep 1, 2026Zhaoliang Chen, Jie FuEfficient Language Model Reasoning Continuous Latent Reasoning
Emory University · IQuest Research
RPCBench: A Benchmark for Proactive Premise Critique in LLM-based Recommendation
Sep 1, 2026Zhongru Chen, Yuan Wu, Yi ChangLLM Evaluation Large Language Model-Based Recommendation
School of Artificial Intelligence, Jilin University · Engineering Research Center of Knowledge-Driven Human-Machine Intelligence, MOE, China · International Center of Future Science, Jilin University
Learning What to Practice: Diagnosis-Guided Self-Evolution for Language Models
Sep 1, 2026Xincheng Wei, Yifan Ding, Fucheng Xiong +6Self-Training for Language Models Language Model Self-Improvement
The Chinese University of Hong Kong, Shenzhen · Meituan, LongCat Team · Peking University +2
A Model with No Head and Many Thoughts
Aug 31, 2026Nikita Koriagin, Yaroslav Aksenov, George Bredis +3Efficient Language Model Reasoning LLM Inference Acceleration
1Yandex · 2T-Tech
Wrong Prediction, Right Answer: Recovering Evidence from Collapsed LLM Sequence Scores
Aug 31, 2026Qiyao Yan, Chenpeng Wang, Liangming PanLLM Evaluation Language Model Calibration
State Key Laboratory of Multimedia Information Processing, Peking University · School of Computer Science, Peking University · YiXin-AILab, YIXIN, Beijing, China +1
CARVE: Verified Expansion for Variable-Length Generation in Diffusion Language Models
Aug 31, 2026Wail Bouhedja, Amr Mohamed, Guokan ShangMasked Diffusion Models LLM Inference Acceleration
1MBZUAI · 2Sorbonne Université · 3Ecole Polytechnique
LCoT-GV: Graph Attention Networks for Verifying Long Reasoning Chains in Large Language Models
Aug 31, 2026Bérénice Jaulmes, Mehwish AlamLLM Reasoning with Graphs LLM Reasoning
1T´el´ecom Paris, Institut Polytechnique de Paris, France · 2BNP Paribas, IT Group, France

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Improving Mathematical Reasoning Capabilities in Large Language Models via Reasoning Process Error Classification

Runa Yoshida, Kosuke Nishida, Kyosuke Nishida

Human Informatics Labs., NTT, Inc.

LLM Prompting LLM Mathematical Reasoning LLM Reasoning

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The reasoning ability of large language models (LLMs) is a critical factor for practical LLM-based applications. To investigate the current reasoning capability of LLMs, we clarify the types of errors that arise in LLMs' reasoning processes on mathematical datasets. We focus on problems where LLMs produce an incorrect answer. We define errors in the reasoning process as reasoning errors and manually analyze the features of reasoning errors. We defined and classified 21 error classes and identified the frequently occurring classes among them. Beyond qualitative evaluation, we leverage the evaluation results to improve the reasoning capability. We designed a prompt that explicitly focuses on eight error classes. The experiments demonstrate that this prompt effectively improves reasoning performance. Furthermore, the results suggest that the frequent reasoning errors identified in this paper are common across LLMs of comparable scale.

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