Large Language Model Reasoning

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OSCToM: RL-Guided Adversarial Generation for High-Order Theory of Mind
May 19, 2026Sharmin Sultana Srishty, Kazi Mahathir Rahman, Malaika Parizat Sakkhi +2Theory-Of-Mind Reasoning Large Language Model Reasoning
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 +3Large Language Model Bias Gender Bias
Do as I Say, Not as I Do: Instruction-Induction Conflict in LLMs
May 19, 2026Carolina Camassa, Derek ShillerInstruction-Tuned Models Instruction
From Seeing to Thinking: Decoupling Perception and Reasoning Improves Post-Training of Vision-Language Models
May 19, 2026Juncheng Wu, Hardy Chen, Haoqin Tu +6Large Vision Language Models Visual Reasoning
Less Data, Faster Training: repeating smaller datasets speeds up learning via sampling biases
May 19, 2026Jingwen Liu, Ezra Edelman, Surbhi Goel +1Unified Inductive Bias Table Reasoning Datasets
MixRea: Benchmarking Explicit-Implicit Reasoning in Large Language Models
May 19, 2026Yuanqing Cai, Ziyi Huang, Minhao Liu +3Large Language Model Reasoning Cognitive Science
CopT: Contrastive On-Policy Thinking with Continuous Spaces for General and Agentic Reasoning
May 19, 2026Dachuan Shi, Hanlin Zhu, Xiangchi Yuan +4Large Language Model Reasoning Thinking
A Nash Equilibrium Framework For Training-Free Multimodal Step Verification
May 19, 2026Rohit Sinha, Kunal Tilaganji, Tanuja Ganu +3Verification-Triggered Multimodal Reasoning Chain
A Measure-Theoretic Analysis of Reasoning: Structural Generalization and Approximation Limits
May 19, 2026Yuyang Zhang, Yifu Zhang, Xuehai Zhou +1Structural Generalization Large Language Model Reasoning
Are Tools Always Beneficial? Learning to Invoke Tools Adaptively for Dual-Mode Multimodal LLM Reasoning
May 19, 2026Qinghe Ma, Zhen Zhao, Yiming Wu +3Tool Invocation Large Language Model Reasoning
CogScale: Scalable Benchmark for Sequence Processing
May 19, 2026Yannis Bendi-Ouis, Romain de Coudenhove, Xavier HinautNeural Architectures Sequence Modeling
Mathematical Reasoning in Large Language Models: Benchmarks, Architectures, Evaluation, and Open Challenges
May 19, 2026Husnain Amjad, Raja Khurram Shahzad, Aamir Shahzad +1Mathematical Reasoning Large Language Model Reasoning
Formal Skill: Programmable Runtime Skills for Efficient and Accurate LLM Agents
May 19, 2026Xi Zhang, Meijun Gao, Yuntian Zhao +6Large Language Model Agents Large Reasoning Models
LLMEval-Logic: A Solver-Verified Chinese Benchmark for Logical Reasoning of LLMs with Adversarial Hardening
May 19, 2026Ming Zhang, Qiyuan Peng, Yinxi Wei +13Reasoning Benchmark
Attention-Guided Reward for Reinforcement Learning-based Jailbreak against Large Reasoning Models
May 19, 2026Zheng Lin, Zhenxing Niu, Haoxuan Ji +2Large Language Model Jailbreaks Large Reasoning Models
LC-ERD: Mining Latent Logic for Self-Evolving Reasoning via Consistency-Regulated Reward Decomposition
May 19, 2026Yanyu Chen, Jiyue Jiang, Dianzhi Yu +8Efficient Latent Reasoning Reinforcement Learning With Verifiable Reward
Backtracking When It Strays: Mitigating Dual Exposure Biases in LLM Reasoning Distillation
May 19, 2026Bing Wang, Shaotian Yan, Chen Shen +7Large Language Model Reasoning Large Language Model Performance
Taming the Thinker: Conditional Entropy Shaping for Adaptive LLM Reasoning
May 19, 2026Shuyu Wei, Jian Sun, Delai Qiu +6Large Language Model Reasoning Efficient Latent Reasoning
Are Rationales Necessary and Sufficient? Tuning LLMs for Explainable Misinformation Detection
May 19, 2026Bing Wang, Rui Miao, Ximing Li +6Misinformation Detection Misinformation
Lost in Interpretation: The Plausibility-Faithfulness Trade-off in Cross-Lingual Explanations
May 19, 2026Somnath Banerjee, Pranav Jha, Rima Hazra +1Rationales Physical Plausibility
Diagnosing Multi-step Reasoning Failures in Black-box LLMs via Stepwise Confidence Attribution
May 19, 2026Xiaoou Liu, Tiejin Chen, Dengjia Zhang +3Large Language Model Reasoning Reasoning Failures
Monitoring the Internal Monologue: Probe Trajectories Reveal Reasoning Dynamics
May 18, 2026Maciej Chrabąszcz, Aleksander Szymczyk, Marcin Sendera +2Large Reasoning Models Reasoning Trajectory
Implicit Hierarchical GRPO: Decoupling Tool Invocation from Execution for Tool-Integrated Mathematical Reasoning
May 18, 2026Li Wang, Xiaohan Wang, Xiaodong Lu +5Large Language Model Reasoning Mathematical Reasoning
QSTRBench: a New Benchmark to Evaluate the Ability of Language Models to Reason with Qualitative Spatial and Temporal Calculi
May 18, 2026Anthony G. Cohn, Robert E. BlackwellReasoning Benchmark
Efficient Table QA via TableGrid Navigation and Progressive Inference Prompting
May 18, 2026Amritansh Maurya, Navjot Singh, Mohammed Javed +1Tabular Data Table Reasoning Datasets
Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains
May 18, 2026Zhonghang Yuan, Zhefan Wang, Fang Hu +7Reinforcement Learning With Verifiable Reward Large Language Model Reasoning
The Expressive Power of Low Precision Softmax Transformers with (Summarized) Chain-of-Thought
May 18, 2026Moritz Brösamle, Stephan EcksteinTransformer Layers Gumbel-Softmax Relaxation
Enhancing the Code Reasoning Capabilities of LLMs via Consistency-based Reinforcement Learning
May 18, 2026Zhanyue Qin, Jia Feng, Yibo Lyu +4Large Language Model Reasoning Large Reasoning Models
Entropy-Gradient Inversion: Moving Toward Internal Mechanism of Large Reasoning Models
May 18, 2026Junyao Yang, Chen Qian, Kun Wang +4Large Reasoning Models Prompt Optimization
EXG: Self-Evolving Agents with Experience Graphs
May 18, 2026Yuxin Jin, Siyuan Zhang, Hanchen Wang +3Self-Evolving Agents Experience
Stop When Reasoning Converges: Semantic-Preserving Early Exit for Reasoning Models
May 17, 2026Dehai Min, Giovanni Vaccarino, Huiyi Chen +3Large Reasoning Models Redundancy
Self-Supervised On-Policy Distillation for Reasoning Language Models
May 17, 2026Zhiquan Tan, Yinrong HongUnsupervised On-Policy Self-Distillation On-Policy Distillation
RSD: Moving Local Triangular Charts for Auditing Language-Model Hidden States
May 17, 2026Seungmin JinHidden States Algorithm Auditing
Learning Transferable Topology Priors for Multi-Agent LLM Collaboration Across Domains
May 17, 2026Taolin Zhang, Zijie Zhou, Jiuheng Wan +4Multi-Agent Large Language Model Reasoning Benchmark
Leveraging Error Diversity in Group Rollouts for Reinforcement Learning
May 17, 2026Wenpu Liu, Yuqi Xu, Weichu Xie +8Reinforcement Learning With Verifiable Reward Long Rollouts
LPG: Balancing Efficiency and Policy Reasoning in Latent Policy Guardrails
May 17, 2026Nanxi Li, Zhengyue Zhao, Chaowei XiaoStreaming Guardrails Large Language Model Safety
Reasoning Before Diagnosis: Physician-Inspired Structured Thinking for ECG Classification
May 17, 2026Yang Wu, Xiaoyan Yuan, Hau-San Wong +1Electrocardiogram Classification Pediatric-Adult Electrocardiogram Alignment
A2RBench: An Automatic Paradigm for Formally Verifiable Abstract Reasoning Benchmark Generation
May 17, 2026Qingchuan Ma, Yuexiao Ma, Yongkang Xie +3Reasoning Benchmark Benchmarking Large Language Models
Is VLA Reasoning Faithful? Probing Safety of Chain-of-Causation in Autonomous Driving Models
May 17, 2026Nicanor Mayumu, Xiaoheng Deng, Patrick MukalaAutonomous Driving Vision-Language-Action Models
ChemVA: Advancing Large Language Models on Chemical Reaction Diagrams Understanding
May 17, 2026Mingyang Rao, Kehua Feng, Zhihui Zhu +4Vast Chemical Space Reaction
The Point of No Return: Counterfactual Localization of Deceptive Commitment in Language-Model Reasoning
May 16, 2026Scott Merrill, Shashank SrivastavaDeception Large Language Model Reasoning
Scientific Logicality Enriched Methodology for LLM Reasoning: A Practice in Physics
May 16, 2026Zhaoxin Yu, Nan Xu, Kun Chen +3Large Language Model Reasoning Scientific Discovery
ACIL: Auto Chain of Thoughts for In-Context Learning
May 16, 2026Rui ChuLarge Language Model Reasoning In-Context Learning
Why Do Reasoning Models Lose Coverage? The Role of Data and Forks in the Road
May 16, 2026Ngoc-Hieu Nguyen, Parshin Shojaee, Phuc Minh Nguyen +4Large Reasoning Models Reasoning Paths
How do Humans Process AI-generated Hallucination Contents: a Neuroimaging Study
May 16, 2026Shuqi Zhu, Yi Zhong, Ziyi Ye +4Robust Hallucination Detection Hallucinations
Effort as Ceiling, Not Dial: Reasoning Budget Does Not Modulate Cognitive Cost Alignment Between Humans and Large Reasoning Models
May 16, 2026Yueqing Hu, Tianhong WangLarge Reasoning Models Inference Cost
Reasoning Can Be Restored by Correcting a Few Decision Tokens
May 16, 2026Changshuo Shen, Leheng Sheng, Yuxin Chen +2Large Reasoning Models Decisions
RTI-Bench: A Structured Dataset for Indian Right-to-Information Decision Analysis
May 16, 2026Joy BoseTable Reasoning Datasets Ghana
Confidence Geometry Reveals Trace-Level Correctness in Large Language Model Reasoning
May 16, 2026Shuo Liu, Ding Liu, Shi-Ju RanLarge Language Model Uncertainty Large Language Model Reasoning
TIER: Trajectory-Invariant Execution Rewards for Multi-Step Tool Composition
May 16, 2026Anay Kulkarni, ChiaEn Lu, Dheeraj Mekala +3Reasoning Trajectory Tool
The Unlearnability Phenomenon in RLVR for Language Models
May 16, 2026Yulin Chen, He He, Chen ZhaoReinforcement Learning With Verifiable Reward Large Language Model Unlearning
TTE-Flash: Accelerating Reasoning-based Multimodal Representations via Think-Then-Embed Tokens
May 15, 2026Jianpeng Cheng, Xian Wu, Jiangfan Zhang +10Multimodal Embeddings Latent Reasoning Tokens
Distributional Energy-Based Models for Uncertainty-Aware Structured LLM Reasoning
May 15, 2026Shireen Kudukkil Manchingal, Abhey Kalia, Fernanda Gonçalves +1Large Language Model Reasoning Large Language Model Uncertainty
SGR: A Stepwise Reasoning Framework for LLMs with External Subgraph Generation
May 15, 2026Xin Zhang, Yang Cao, Baoxing Wu +2Large Language Model Reasoning Interaction Trajectories
GRASP: Learning to Ground Social Reasoning in Multi-Person Non-Verbal Interactions
May 15, 2026Junho Kim, Xu Cao, Houze Yang +6Social Reasoning Nonverbal Cues
SAGE: Shaping Anchors for Guided Exploration in RLVR of LLMs
May 15, 2026Chanuk Lee, Minki Kang, Sung Ju HwangReinforcement Learning With Verifiable Reward Large Language Model Reasoning
CAPS: Cascaded Adaptive Pairwise Selection for Efficient Parallel Reasoning
May 15, 2026Fangzhou Lin, Shuo Xing, Peiran Li +6Reasoning Benchmark Verifier
Reasoning Models Don't Just Think Longer, They Move Differently
May 14, 2026Anders Gjølbye, Lars Kai Hansen, Sanmi KoyejoLarge Reasoning Models Chain-of-Thought Reasoning
Minerva-Ego: Spatiotemporal Hints for Egocentric Video Understanding
May 14, 2026Arsha Nagrani, Jasper Uijilings, Shyamal Buch +6Egocentric Video Visual Reasoning
Zero-Shot Goal Recognition with Large Language Models
May 14, 2026Kin Max Piamolini Gusmão, Nathan Gavenski, Nir Oren +1Large Language Model Planning Planning Methods

May 19, 2026 · cs.AIJ/K move · Enter open · S save

OSCToM: RL-Guided Adversarial Generation for High-Order Theory of Mind

Sharmin Sultana Srishty, Kazi Mahathir Rahman, Malaika Parizat Sakkhi, Samia Shahid Prianna+1

Department of Computer Science BRAC University

Large Language Models (LLMs) perform well on many language tasks, but their Theory of Mind (ToM) reasoning is still uneven in complex social settings. Existing benchmarks, including ExploreToM, do not always test the recursive beliefs and information asymmetries that make these settings difficult. This paper presents OSCToM (Observer-Self Conflict Theory of Mind), an approach for modeling nested belief conflicts in LLM-based ToM tasks. The key case is one in which an observer's view of another agent conflicts with the observer's own belief state. Such cases go beyond simple perspective-taking and require recursive, multi-layered reasoning. OSCToM combines reinforcement learning (RL), an extended domain-specific language, and compositional surrogate models to generate observer-self conflicts. In our experiments, OSCToM-8B gives the best overall result among the systems tested. It improves on the reported ExploreToM results on FANToM and remains competitive on Hi-ToM and BigToM. On the information-asymmetric FANToM benchmark, OSCToM reaches 76% accuracy, compared with the 0.2% reported by ExploreToM. The data-synthesis procedure is also 6x more efficient, indicating that targeted training data can help smaller models handle advanced cognitive reasoning. The project code is available at https://github.com/sharminsrishty/osct.

Theory-Of-Mind Reasoning Large Language Model Reasoning

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