Large Language Model Reasoning

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Large Language Model Reasoning

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Chain-of-Thought Reasoning

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Detecting Unfaithful Chain-of-Thought via Circuit-Guided Internal-External Discrepancy
May 25, 2026Xu Shen, Zhen Tan, Song Wang +4Reasoning Traces Explanation Faithfulness
AnE: Pushing the Reasoning Frontier of Multimodal LLMs via Anchor Evolution
May 25, 2026Zehao Wang, Yihan Zeng, Zidong Gong +5Multimodal Reasoning Benchmarks Large Language Model Reasoning
Uncertainty Reasoning with Large Language Models for Explainable Disease Diagnosis
May 25, 2026Xiaoyang Fan, Yufan Cai, Zhe Hou +1Large Language Model Reasoning Neuro-Symbolic Framework
BC Protocol: Structured Dual-Expert Dialogue for Eliciting High-Quality Chain-of-Thought Post-Training Data
May 25, 2026Bo Zou, Chao XuLarge Language Model Post-Training Large Language Model Reasoning
ProSR: Process-Shaped Spatial Reasoning for Reliable Chain-of-Thought in VLMs
May 25, 2026Jiangyang Li, Cong Wan, Changjie Wu +8Spatial Reasoning Reasoning Trajectory
Credit Assignment with Resets in Language Model Reasoning
May 25, 2026Ankur Samanta, Akshayaa Magesh, Ayush Jain +7Credit Assignment Multi-Objective Policy Optimization
Harmony in Diversity: Multi-domain Contrastive Policy Optimization for Large Reasoning Models
May 25, 2026Zongji Yu, Wenshui Luo, Yiliu Sun +4Large Reasoning Models Reasoning Trajectory
GeoMathCode: Understanding Interleaved Math-Code Reasoning for Geometry Problem Solving
May 25, 2026Yingji Zhang, Yong Dai, André FreitasRepresentational Geometry Visual Representations
Context-CoT: Enhancing Context Learning via High-Quality Reasoning Synthesis
May 25, 2026Hongbo Jin, Mingnan Zhu, Jingqi Tian +6Large Language Model Reasoning In-Context Learning
Boosting Inference with Guided Reasoning: Stochastic Exploration for Recursive Models
May 24, 2026Andrew Corbett, Archit Sood, Anna Tzatzopoulou +2Reasoning Trajectory Recursion
DarkForest: Less Talk, Higher Accuracy for Multi-Agent LLMs
May 24, 2026Yi Li, Songtao Wei, Dongming Jiang +3Multi-Agent Large Language Model Multi-Agent Large Language Model Systems
Knowledge Graph-Driven Expert-Level Reasoning for Neuroscience
May 24, 2026Jake Stephen, Niraj K. JhaLarge Language Model Reasoning Knowledge Graphs
Beyond the Frontier: Stochastic Backtracking for Efficient Test-Time Scaling
May 24, 2026Dao Tran, Duc Anh Le, Ngoc Luu +3Test-Time Scaling Reasoning Benchmark
Better, Faster: Harnessing Self-Improvement in Large Reasoning Models
May 24, 2026Qihuang Zhong, Liang Ding, Juhua Liu +3Large Reasoning Models Reasoning Trajectory
Investigating the Interplay between Contextual and Parametric Chain-of-Thought Faithfulness under Optimization
May 24, 2026Jingyi Sun, Qianli Wang, Pepa Atanasova +2Explanation Faithfulness Faithfulness
When Reasoning Hurts: Source-Aware Evaluation of Frontier LLMs for Clinical SOAP Note Generation
May 24, 2026Faizan FaisalClinical Reasoning Reasoning Benchmark
Towards a Universal Causal Reasoner
May 24, 2026Qirun Dai, Xiao Liu, Jiawei Zhang +3Large Language Model Reasoning Causal Reasoning
Clustering as Reasoning: A $k$ -Means Interpretation of Chain-of-Thought Graph Learning
May 24, 2026Xuanting Xie, Zhaochen Guo, Bingheng Li +4Graph Representation Learning Chain-of-Thought Reasoning
Geo-Expert: Towards Expert-Level Geological Reasoning via Parameter-Efficient Fine-Tuning
May 24, 2026Chenyou Guo, Zongqi Liu, Yizhou Zhang +2Geological Semantic Understanding Large Language Model Reasoning
Test-Time Deep Thinking to Explore Implicit Rules
May 24, 2026Wentong Chen, Xin Cong, Zhong Zhang +8Agentic Reasoning Reasoning Trajectory
Measuring Reasoning Quality in LLMs: A Multi-Dimensional Behavioral Framework
May 23, 2026Ali Şenol, Garima Agrawal, Huan LiuReasoning Benchmark Cognitive Science
HiMed: Incentivizing Hindi Reasoning in Medical LLMs
May 23, 2026Dingfeng Jiang, Han Yan, Chenze Ma +12Large Language Model Reasoning
Guarded Repair for Harm-Aware Post-hoc Replacement of LLM Mathematical Reasoning
May 23, 2026Haizhou XiaMathematical Reasoning Large Language Model Reasoning
Learning to Reason Efficiently with A* Post-Training
May 23, 2026Andreas Opedal, Francesco Ignazio Re, Abulhair Saparov +3Large Language Model Reasoning Natural Language Inference
PALoRA: Projection-Adaptive LoRA for Preserving Reasoning in Large Language Models
May 23, 2026Mustafa Hayri Bilgin, Mariam Barry, Albert Bifet +2Large Language Model Reasoning Low-Rank Adaptation
RL with Learnable Textual Feedback: A Bilevel Approach
May 23, 2026Utsav Singh, Sidhaarth Sredharan, Souradip Chakraborty +1Reinforcement Learning From Human Feedback Large Language Model Reasoning
Reasoning as an Attack Surface: Adaptive Evolutionary CoT Jailbreaks for LLMs
May 23, 2026Jianan Li, Simeng Qin, Xiaojun Jia +5Large Language Model Jailbreaks Jailbreak Evaluations
Understanding and Mitigating Premature Confidence for Better LLM Reasoning
May 23, 2026Jingchu Gai, Guanning Zeng, Christina Baek +4Large Language Model Reasoning Overconfidence
CurveRL: Principled Distribution-Aware Context Reweighting for LLM Reasoning
May 23, 2026Ke Sun, Yizhou Zhao, Jiayi Xin +2Reinforcement Learning With Verifiable Reward Reweighting
ChaosBench-Logic v2: Evaluating LLM Logical Reasoning over Dynamical Systems at Scale
May 23, 2026Noel ThomasReasoning Benchmark Large Language Model Reasoning
HyperGuide: Hyperbolic Guidance for Efficient Multi-Step Reasoning in Large Language Models
May 22, 2026Yuyu Liu, Haotian Xu, Yanan He +3Large Language Model Reasoning Few-Step Generation
Metacognition as Reward: Reinforcing LLM Reasoning via Knowledge and Regulation Signals
May 22, 2026Sirui Chen, Lei Xu, Yuying Zhao +6Large Language Model Reasoning Metacognition
FD-RAG: Federated Dual-System Retrieval-Augmented Generation
May 22, 2026Tianhao Gao, Kai Yang, Yiyang LiRetrieval-Augmented Generation Systems Hievi-Rag
Positional Failures in Long-Context LLMs: A Blind Spot in Reasoning Benchmarks
May 22, 2026Chuyifei Zhang, Hongyu Cui, Xiaowen Huang +1Reasoning Benchmark Blind Spots
PathCal: State-Aware Reflection-Marker Calibration for Efficient Reasoning
May 21, 2026Lingyu Jiang, Zirui Li, Shuo Xing +6Reasoning Trajectory Multicalibration and Calibration
Learnability-Informed Fine-Tuning of Diffusion Language Models
May 21, 2026Shubham Parashar, Atharv Chagi, Jacob Helwig +5Diffusion Language Models Discrete Tokens
Think Thrice Before You Speak: Dual knowledge-enhanced Theory-of-Mind Reasoning for Persuasive Agents
May 21, 2026Minghui Ma, Bin Guo, Runze Yang +7Theory-Of-Mind Reasoning Persuasion
LANG: Reinforcement Learning for Multilingual Reasoning with Language-Adaptive Hint Guidance
May 21, 2026Yuchun Fan, Bei Li, Peiguang Li +9Multilingual Reasoning Large Language Model Reasoning
Reflecti-Mate: A Conversational Agent for Adaptive Decision-Making Support Through System 1 and System 2 Thinking
May 21, 2026Morita Tarvirdians, Senthil Chandrasegaran, Hayley Hung +2Agent Decisions Reflections
Unified Data Selection for LLM Reasoning
May 21, 2026Xiaoyuan Li, Yubo Ma, Chengpeng Li +6Large Language Model Reasoning
Tailoring Teaching to Aptitude: Direction-Adaptive Self-Distillation for LLM Reasoning
May 21, 2026Hongbin Zhang, Chaozheng Wang, Kehai Chen +4Unsupervised On-Policy Self-Distillation On-Policy Distillation
Reinforced Graph of Thoughts: RL-Driven Adaptive Prompting for LLMs
May 21, 2026Manuel Noah Riesen, Peter Alfred von NiederhäusernLarge Language Model Reasoning Tree-Of-Thoughts
ArborKV: Structure-Aware KV Cache Management for Scaling Tree-based LLM Reasoning
May 21, 2026Yeqiu Chen, Ziyan Liu, Zhenxin Huang +3Key-Value Cache Tree-Of-Thoughts
ExComm: Exploration-Stage Communication for Error-Resilient Agentic Test-Time Scaling
May 21, 2026Woomin Song, Beomjun Kim, Daewon Choi +4Test-Time Scaling Communication
From Reasoning Chains to Verifiable Subproblems: Curriculum Reinforcement Learning Enables Credit Assignment for LLM Reasoning
May 21, 2026Xitai Jiang, Zihan Tang, Wenze Lin +3Curriculum Reinforcement Learning Reinforcement Learning With Verifiable Reward
PointLLM-R: Enhancing 3D Point Cloud Reasoning via Chain-of-Thought
May 21, 2026Chaoqi Chen, Qile Xu, Wenjun Zhou +13D Scene Understanding Certified Point-Cloud
Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs
May 21, 2026Jialin Chen, Aosong Feng, Harshit Verma +7Load Forecasting Large Language Model Reasoning
OPPO: Bayesian Value Recursion for Token-Level Credit Assignment in LLM Reasoning
May 21, 2026Yu Li, Rui Miao, Tian Lan +1Large Language Model Reasoning Credit Assignment
Manifold-Guided Attention Steering
May 20, 2026Ian Li, Kapilesh Guruprasad, Raunak Sengupta +3Large Language Model Reasoning Activation Steering
MindLoom: Composing Thought Modes for Frontier-Level Reasoning Data Synthesis
May 20, 2026Haiyang Shen, Taian Guo, Xuanzhong Chen +11Table Reasoning Datasets
Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning
May 20, 2026Benhao Huang, Zhengyang Geng, Zico KolterTest-Time Scaling Recursive Reasoner
Self-Verified Distillation: Your Language Model Is Secretly Its Own Synthetic Data Pipeline
May 20, 2026Tony Lee, Percy LiangLarge Language Model Post-Training Large Reasoning Models
Tracing the ongoing emergence of human-like reasoning in Large Language Models
May 20, 2026Paolo Morosi, Nikoleta Pantelidou, Fritz Günther +2Large Language Model Reasoning Large Language Model Performance
On the Cost and Benefit of Chain of Thought: A Learning-Theoretic Perspective
May 20, 2026Yue Zhang, Zhiyi Dong, Tommaso Cesari +1Reasoning Trajectory Hypothesis
LamPO: A Lambda Style Policy Optimization for Reasoning Language Models
May 20, 2026Redacted by arXivReinforcement Learning With Verifiable Reward Group Relative Policy Optimization
Reasoning-Trace Collapse: Evaluating the Loss of Explicit Reasoning During Fine-Tuning
May 20, 2026Lukas Twist, Helen Yannakoudakis, Jie M. ZhangReasoning Traces
Draw2Think: Harnessing Geometry Reasoning through Constraint Engine Interaction
May 20, 2026Juncheng Hu, Jiawei Du, Xin Zhang +1Representational Geometry Thinking
AGPO: Adaptive Group Policy Optimization with Dual Statistical Feedback
May 20, 2026Miaobo Hu, Shuhao Hu, Bokun Wang +5Group Relative Policy Optimization Large Language Model Reasoning
When Do LLMs Reason? A Dynamical Systems View via Entropy Phase Transitions
May 20, 2026Wei Xia, Haoqing Wang, Zhi-Hong Deng +1Large Language Model Reasoning LLM Inference Efficiency
High Quality Embeddings for Horn Logic Reasoning
May 19, 2026Yifan Zhang, Yasir White, Dean Clark +4Global Embeddings Recursive Reasoner

May 25, 2026 · cs.AIJ/K move · Enter open · S save

Detecting Unfaithful Chain-of-Thought via Circuit-Guided Internal-External Discrepancy

Xu Shen, Zhen Tan, Song Wang, Pingjun Hong+3

1Jilin University · University of Central Florida · 3Arizona State University · University of Vienna · University of North Carolina at Chapel Hill

Chain-of-thought (CoT) reasoning improves the problem-solving ability of large language models (LLMs), but generated reasoning traces may not faithfully reflect the model's actual decision process. Existing CoT unfaithfulness detectors mainly rely on external signals from generated rationales, such as textual plausibility or answer consistency, while overlooking evidence from the model's internal computation. Although recent circuit tracing methods provide a way to obtain model-internal evidence by tracing how information flows through model components during reasoning, constructing full reasoning circuits for long CoTs is costly and difficult to scale. To address these challenges, we propose Circuit-guided Internal-External Discrepancy Scorer (CIE-Scorer), a framework for instance-level CoT unfaithfulness detection. The key idea is that faithful reasoning traces should align with the model's computational process, whereas unfaithful traces may diverge from it. CIE-Scorer efficiently traces compact sentence-level circuits from informative reasoning tokens, constructs internal and external reasoning graphs, and measures their discrepancy using Fused Gromov--Wasserstein distance. Experiments on four datasets from FaithCoT-Bench show that CIE-Scorer achieves state-of-the-art performance while reducing the cost of circuit construction, demonstrating the effectiveness of combining mechanistic interpretability signals with external reasoning traces for CoT unfaithfulness detection.

Reasoning Traces Explanation Faithfulness Mechanistic Interpretability Circuits Discrepancy Scoring

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