CoT Reasoning

CoT: Chain-of-Thought

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12 papers in the last four weeks, up 71% on the four weeks before. 0.1% of all new papers.

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When Do LLMs Reason? A Dynamical Systems View via Entropy Phase Transitions
May 20, 2026Wei Xia, Haoqing Wang, Zhi-Hong Deng +1Language Model Decoding CoT Reasoning
Samsung Research, Beijing, China · State Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University
Mechanics of Bias and Reasoning: Interpreting the Impact of Chain-of-Thought Prompting on Gender Bias in LLMs
May 19, 2026Edie Pearman, Sophia Osborne, Mira Kandlikar-Bloch +3Gender Bias in Language Models LLM Interpretability
1Mila – Quebec AI Institute, Montreal, Canada · 2McGill University, Montreal, Canada · 3HEC Montreal, Montreal, Canada
Passive Construction Site Safety Monitoring via Persona-Scaffolded Adversarial Chain-of-Thought VLM Verification
May 19, 2026Ananth Sriram, Neel Mokaria, Rajveer SinghCoT Reasoning Video Surveillance
Department of Computer Science, University of Maryland, College Park, MD, USA
EgoCoT-Bench: Benchmarking Grounded and Verifiable Operation-Centric Chain of Thought Reasoning for MLLMs
May 19, 2026Yang Dai, Dian Jiao, Tianwei Lin +1Egocentric Video QA CoT Reasoning
Zhejiang University · Hangzhou, Zhejiang, China
The Expressive Power of Low Precision Softmax Transformers with (Summarized) Chain-of-Thought
May 18, 2026Moritz Brösamle, Stephan EcksteinTransformer Expressivity Transformer
Department of Mathematics, University of Tübingen, Germany.
Stop When Reasoning Converges: Semantic-Preserving Early Exit for Reasoning Models
May 17, 2026Dehai Min, Giovanni Vaccarino, Huiyi Chen +3Early Stopping CoT Reasoning
University of Illinois Chicago · Politecnico di Milano · University of Illinois Urbana-Champaign +1
ACIL: Auto Chain of Thoughts for In-Context Learning
May 16, 2026Rui ChuLLM Prompting CoT Reasoning
COTCAgent: Preventive Consultation via Probabilistic Chain-of-Thought Completion
May 14, 2026Zihan Deng, Xiaozhen Zhong, Chuanzhi XuHealthcare Clinical Decision Support
School of Computing and Data Science, The University of Hong Kong · 2Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China · School of Computer Science, The University of Sydney
SliceGraph: Mapping Process Isomers in Multi-Run Chain-of-Thought Reasoning
May 14, 2026Kang Chen, Junjie Nian, Yixin Cao +1CoT Reasoning Reasoning Trace Analysis
1Fudan University · 2Shanghai Innovation Institute
Stateful Reasoning via Insight Replay
May 14, 2026Bin Lei, Caiwen Ding, Jiachen Yang +2Memory-Augmented Language Models CoT Reasoning
University of Minnesota · 2Simular AI
Uncovering the Representation Geometry of Minimal Cores in Overcomplete Reasoning Traces
May 14, 2026Sanjoy Chowdhury, Dinesh ManochaNeural Representation Geometry LLM Interpretability
University of Maryland, College Park, USA
Pause and Reflect: Conformal Aggregation for Chain-of-Thought Reasoning
May 13, 2026Yu Gu, Zijun Yu, Vahid Partovi Nia +1Selective Prediction Self-Consistency Decoding
Department of Mathematics and Statistics McGill University Montréal, QC, Canada · Department of Mathematics and Industrial Engineering Polytechnique de Montréal Montréal, QC, Canada
Multilingual OCR-Aware Fine-Tuning and Prompt-Guided Chain-of-Thought Reasoning for Multimodal Large Language Models
May 13, 2026Qinwu Xu, Yifan Jiang, Haoyu RenMultimodal Grounding CoT Reasoning
Meta AI · UT Austin · Current independent researcher
Many-Shot CoT-ICL: Making In-Context Learning Truly Learn
May 13, 2026Tsz Ting Chung, Lemao Liu, Mo Yu +1CoT Reasoning In-Context Learning
Hong Kong University of Science and Technology · Fudan University · Wechat AI, Tencent.
3D Primitives are a Spatial Language for VLMs
May 12, 2026Junze Liu, Kun Qian, Florian Dubost +8Spatial Reasoning Benchmarks 3D Spatial Reasoning
Unity Technologies
Latent Chain-of-Thought Improves Structured-Data Transformers
May 11, 2026Carson Dudley, Samet OymakCoT Reasoning Time Series Forecasting
Tracing Uncertainty in Language Model "Reasoning"
May 8, 2026Nils Grünefeld, Bertram Højer, Philipp Mondorf +5LLM Evaluation CoT Reasoning
Data Science Section, IT University of Copenhagen · Pioneer Centre for Artificial Intelligence · MaiNLP, Center for Information and Language Processing, LMU Munich +2
The Coupling Tax: How Shared Token Budgets Undermine Visible Chain-of-Thought Under Fixed Output Limits
May 8, 2026Wenhua Nie, Junlin Liu, Jianan Wu +5CoT Evaluation CoT Reasoning
National Taiwan University
LaTER: Efficient Test-Time Reasoning via Latent Exploration and Explicit Verification
May 8, 2026Xuan Li, Yining Wang, Yuchen Liu +7CoT Reasoning Efficient Language Model Reasoning
University of Science and Technology of China · Unisound AI Technology Co., Ltd · MAIS, Institute of Automation, Chinese Academy of Sciences
Rethinking Dense Sequential Chains: Reasoning Language Models Can Extract Answers from Sparse, Order-Shuffling Chain-of-Thoughts
May 8, 2026Yi-Chang Chen, Feng-Ting Liao, Da-shan Shiu +1CoT Reasoning Causal Interventions in Language Models
MediaTek Research · Artificial Intelligence Center of Research Excellence, National Taiwan University
Convergence and Emergence of In-Context Reinforcement Learning with Chain of Thought
May 8, 2026Zixuan Xie, Xinyu Liu, Rohan Chandra +1Reinforcement Learning Transformer
University of Virginia
A Theory of Online Learning with Autoregressive Chain-of-Thought Reasoning
May 7, 2026Ilan Doron-Arad, Idan Mehalel, Elchanan MosselCoT Reasoning Autoregressive Generation
1MIT · 2The Hebrew University
Measuring Black-Box Confidence via Reasoning Trajectories: Geometry, Coverage, and Verbalization
May 7, 2026Marc Boubnovski Martell, Josefa Lia Stoisser, Kaspar Märtens +4Confidence Estimation in Language Models CoT Reasoning
1Novo Nordisk · University of Oxford
The Scaling Properties of Implicit Deductive Reasoning in Transformers
May 5, 2026Enrico Vompa, Tanel TammetLogical Reasoning CoT Reasoning
Applied Artificial Intelligence Group Tallinn University of Technology, Estonia
FinSTaR: Towards Financial Reasoning with Time Series Reasoning Models
May 5, 2026Seunghan Lee, Jun Seo, Jaehoon Lee +7Time Series Reasoning CoT Reasoning
LG AI Research · Seoul, South Korea
Barriers to Universal Reasoning With Transformers (And How to Overcome Them)
Apr 28, 2026Oliver Kraus, Yash Sarrof, Yuekun Yao +2Transformer Expressivity CoT Reasoning
1Saarland University · 2Ohio State University
Dual-Track CoT: Budget-Aware Stepwise Guidance for Small LMs
Apr 27, 2026Sagnik Chatterjee, Atharva Patil, Sricharan RameshCoT Reasoning Small Language Models
Meta-CoT: Enhancing Granularity and Generalization in Image Editing
Apr 27, 2026Shiyi Zhang, Yiji Cheng, Tiankai Hang +8Text-Guided Image Editing Unified Multimodal Models
Shenzhen International Graduate School, Tsinghua University · Hunyuan, Tencent
Thoughts-as-Planning: Latent World Models for Chain-of-Thoughts Optimization via Reinforcement Planning
Apr 27, 2026Dong Liu, Yanxuan Yu, Ying Nian WuCoT Reasoning Large Language Model-Guided Optimization
University of California, Los Angeles · Columbia University
Thinking Like a Clinician: A Cognitive AI Agent for Clinical Diagnosis via Panoramic Profiling and Adversarial Debate
Apr 26, 2026Zhiqi Lv, Duofan Tu, Jun Li +4Tree of Thoughts Clinical Decision Support
School of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230026, P.R. China · Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, Jiangsu, 215123, P.R. China · Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing, PR China +2

May 20, 2026, cs.LGJ/K move · Enter open · S save

When Do LLMs Reason? A Dynamical Systems View via Entropy Phase Transitions

Wei Xia, Haoqing Wang, Zhi-Hong Deng, Yehui Tang

Samsung Research, Beijing, China · State Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University

Language Model Decoding CoT Reasoning Efficient Language Model Reasoning Efficient Language Model Inference LLM Reasoning

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Chain-of-thought (CoT) reasoning has become the default strategy for enhancing LLM capabilities, yet its application raises a fundamental question: when is explicit reasoning actually beneficial? Empirical evidence reveals a striking paradox: CoT often provides marginal or even negative gains on factual and open-ended tasks while multiplying token consumption. In this work, we show that LLM reasoning is not a static property of tasks or models, but a \emph{dynamic decoding state} that emerges during generation. Through systematic analysis, we find early-stage entropy dynamics provide a reliable signal of this state: tasks benefiting from CoT exhibit consistent entropy reduction, while others display unstable or increasing patterns. This behavior can be interpreted as a phase-transition-like shift from a high-entropy exploratory regime to a low-entropy structured reasoning regime. Based on these insights, we propose \textbf{EDRM} (Entropy Dynamics-based Reasoning Manifold), a lightweight and training-free routing framework that leverages early decoding entropy to adaptively select inference strategies. EDRM embeds entropy trajectories into a compact and interpretable manifold representation, enabling both zero-shot deployment and fine-grained instance-level adaptation. Across 15 benchmarks and 4 LLMs of varying scales and architectures, EDRM consistently outperforms static baselines. At the dataset level, EDRM achieves \textbf{41--55%} token reduction while improving accuracy with as few as 50 calibration samples. At the instance level, it further improves accuracy by up to \textbf{4.7%} while maintaining \textbf{27--45%} token savings. These results suggest that reasoning should be invoked selectively rather than by default, and demonstrate the effectiveness of entropy-driven decoding control for efficient and adaptive LLM inference.

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