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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Mind the Perspective: Let's Reason Recursively for Theory of Mind
Jun 10, 2026Chao Lei, Guang Hu, Meng Yang +2Logical Reasoning Theory of Mind
School of Computing and Information Systems, The University of Melbourne, Australia · SensiLab, Monash University, Australia
Can AI Reason Like an Urban Planner? Benchmarking Large Language Models Against Professional Judgment
Jun 10, 2026Yijie Deng, He Zhu, Wen Wang +3LLM Evaluation Urban Planning
Behavioral and Spatial AI Lab, Tongji University · Behavioral and Spatial AI Lab, Peking University · College of Architecture and Urban Planning, Tongji University
LLMs+Graphs: Toward Graph-Native, Synergistic AI Systems
Jun 10, 2026Arijit Khan, Longxu Sun, Xin HuangKnowledge Augmentation for Language Models LLM Reasoning with Graphs
Bowling Green State University, Ohio, USA · Hong Kong Baptist University, Hong Kong, China
The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes
Jun 9, 2026Avinash Anand, Mahisha Ramesh, Avni Mittal +7CoT Reasoning RL for Language Model Reasoning
SIT × Nvidia AI Center (SNAIC) · MIDAS Lab, IIIT Delhi · MIDAS Lab, IIT Mandi +4
The Role of Feedback Alignment in Self-Distillation
Jun 9, 2026Semih Kara, Oğuzhan ErsoyRL for Language Model Reasoning Language Model Distillation
Gensyn
ReasonAlloc: Hierarchical Decoding-Time KV Cache Budget Allocation for Reasoning Models
Jun 9, 2026Wenhao Liu, Hao Shi, Yunhe Li +7KV Caching Memory-Efficient Optimization
1Tsinghua University · 2City University of Hong Kong · 3Peking University +2
Benchmarking Knowledge Editing using Logical Rules
Jun 9, 2026Tatiana Moteu Ngoli, NDah Jean Kouagou, Hamada M. Zahera +1Knowledge Editing LLM Evaluation
Data Science Group, Heinz Nixdorf Institute, Paderborn University
TabClaw: An Interactive and Self-Evolving Agent for Spreadsheet Manipulation and Table Reasoning
Jun 9, 2026Mingyue Cheng, Shuo Yu, Daoyu Wang +5Multi-Agent LLM Systems LLM Agent Skill Learning
Optical Reasoning: Rethinking Images as an Expressive Reasoning Medium Beyond Text
Jun 8, 2026Yutong Bian, Dongjie Cheng, Heming Xia +2Visual Reasoning Multimodal Reasoning
The Hong Kong Polytechnic University
Detecting Differences Is Not Understanding Structure: Large Language Models Fail at Graph Isomorphism
Jun 8, 2026Kumar Thushalika, Sukumar Kishanthan, Asela HevapathigeLLM Evaluation LLM Reasoning with Graphs
University of Ruhuna, Galle, Sri Lanka · University of Moratuwa, Moratuwa, Sri Lanka · University of Melbourne, Melbourne, Australia
Capacity, Not Format: Rethinking Structured Reasoning Failures
Jun 8, 2026Hengxin FanLLM Evaluation Structured Prompting
Tianjin Normal University
SEF-CLGC at SemEval-2026 Task 11: Logical Notation Impact on Language Model Performance
Jun 8, 2026Hanna Abi Akl, Fabien Gandon, Catherine Faron +1Logical Reasoning Symbolic Reasoning
Université Côte d’Azur, Inria, CNRS, I3S, Sophia Antipolis, France · Data ScienceTech Institute, Paris, France
Inference-Time Conformal Reasoning with Valid Factuality Control for Large Language Models
Jun 7, 2026Ting Wang, Yuanjie Shi, Yan Yan +1LLM Inference LLM Reasoning with Graphs
University of Illinois Urbana-Champaign · School of EECS, Washington State University.
PAEC: Position-Aware Entropy Calibration for LLM Reasoning in RLVR
Jun 7, 2026Shumeng Yang, Yisu Liu, Jiayi Zheng +2RL for Language Model Reasoning Maximum Entropy RL
Institute of Automation, Chinese Academy of Sciences · School of Artificial Intelligence, University of Chinese Academy of Sciences · School of Artificial Intelligence, Beijing University of Posts and Telecommunications +2
Personalized and Robust Proactive Robot Assistance with Uncertainty-Guided LLM Reasoning
Jun 7, 2026Alvaro Gonzalez, M. H. Hasan Shovo, Ali AyubMarkov Models Assistive Robotics
Concordia University, Montreal, Quebec H3G 1M8, Canada
How reliable are LLMs when it comes to playing dice?
Jun 5, 2026Luca Avena, Gianmarco Bet, Bernardo BusoniLLM Evaluation LLM Prompting
Università degli Studi di Firenze Dipartimento di Matematica e Informatica ‘Ulisse Dini’
M $^3$ Exam: Benchmarking Multimodal Memory for Realistic User-Agent Interactions
Jun 5, 2026Zhengjun Huang, Wenxuan Liu, Zhoujin Tian +6Multimodal Grounding Efficient Multimodal Inference
The Hong Kong University of Science and Technology · Peng Cheng Laboratory · Beijing University of Chemical Technology +4
Think Fast: Estimating No-CoT Task-Completion Time Horizons of Frontier AI Models
Jun 5, 2026Dewi Gould, Francis Rhys Ward, Anders Cairns Woodruff +18LLM Evaluation AI Safety Evaluation
Redwood Research · Astra Fellows Program · Aether Research +10
DyCon: Dynamic Reasoning Control via Evolving Difficulty Modeling
Jun 5, 2026Tengyao Tu, Yulin Li, Hui-Ling Zhen +6Overthinking in Language Models Efficient Language Model Reasoning
Harbin Institute of Technology, Shenzhen · Zhongguancun Academy · Huawei Noah’s Ark Lab +2
RASFT: Rollout-Adaptive Supervised Fine-Tuning for Reasoning
Jun 5, 2026Yongliang Miao, Fengyuan Liu, Wei Shi +4Supervised Fine-Tuning LLM Mathematical Reasoning
The Chinese University of Hong Kong, Shenzhen · Shanghai Artificial Intelligence Laboratory · New Jersey Institute of Technology +1
Quantum-Inspired Trace-Augmented Evidence Selection for Reasoning over Structured Hypothesis Spaces
Jun 5, 2026Laura Wynter, Nirvik Sahoo, Paul GriffinEvidence-Grounded Reasoning CoT Reasoning
School of Computing and Information Systems Singapore Management University Singapore
ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM Reasoning
Jun 5, 2026Vladislav Smirnov, Chieu Nguyen, Sergey Senichev +14LLM Evaluation Test-Time Scaling
1MBZUAI · 7Independent Researcher · 2ETH Zürich +4
TALAN: Task-Aligned Latent Adaptation Networks for Targeted Post-Training of Large Language Models
Jun 5, 2026Chengkai Zhang, Ziteng Liu, Junpu Wang +4Supervised Fine-Tuning Adapter Tuning
Meta AI
Skip a Layer or Loop It? Learning Program-of-Layers in LLMs
Jun 4, 2026Ziyue Li, Yang Li, Tianyi ZhouLLM Inference LLM Inference Acceleration
University of Maryland, College Park, MD, USA · 2MBZUAI, Abu Dhabi, UAE.
Closing the Loop on Latent Reasoning via Test-Time Reconstruction
Jun 4, 2026Xiaopeng Yuan, Haibo Jin, Ye Yu +4LLM Inference Test-Time Training
University of Illinois Urbana-Champaign · Google · Florida State University
The Tell-Tale Norm: $\ell_2$ Magnitude as a Signal for Reasoning Dynamics in Large Language Models
Jun 4, 2026Jinyang Zhang, Hongxin Ding, Yue Fang +4LLM Interpretability Test-Time Scaling
School of Computer Science, Peking University · National Engineering Research Center of Software Engineering, Peking University · Key Laboratory of High Confidence Software Technologies, Ministry of Education +2
The Self-Correction Illusion: LLMs Correct Others but Not Themselves
Jun 4, 2026Kuan-Yen Chen, Fang-Yi Su, Jung-Hsien ChiangLLM Self-Correction LLM Prompting
National Cheng Kung University
Failed Reasoning Traces Tell You What Is Fixable (But Not by Reading Them)
Jun 3, 2026Nizar Islah, Istabrak Abbes, Irina Rish +2Test-Time Scaling LLM Routing
1Mila - Quebec AI Institute · 2Université de Montréal · 3Polytechnique Montréal +1
Imbuing Large Language Models with Bidirectional Logic for Robust Chain Repair
Jun 3, 2026Zehua Cheng, Wei Dai, Jiahao Sun +1LLM Self-Correction Symbolic Reasoning
Department of Computer Science, University of Oxford, UK · Institute of Logic and Computation, TU Wien, Austria
DAR: Deontic Reasoning with Agentic Harnesses
Jun 3, 2026Guangyao Dou, William Jurayj, Nils Holzenberger +1Logical Reasoning Agentic Reasoning
Johns Hopkins University · Télécom Paris, Institut Polytechnique de Paris

Jun 10, 2026, cs.AIJ/K move · Enter open · S save

Mind the Perspective: Let's Reason Recursively for Theory of Mind

Chao Lei, Guang Hu, Meng Yang, Yanbei Jiang+1

School of Computing and Information Systems, The University of Melbourne, Australia · SensiLab, Monash University, Australia

Logical Reasoning Theory of Mind Epistemic Logic LLM Reasoning

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Theory of Mind (ToM) reasoning requires inferring agents' beliefs from partial and asymmetric observations, which remains an open challenge for LLMs. Existing prompting-based approaches improve ToM reasoning through observable-event filtering or temporal belief chains, without explicitly modeling nested beliefs. We introduce RecToM, an inference-time framework for ToM reasoning that models nested beliefs via recursive perspective construction. RecToM constructs each character perspective from the preceding character perspective along the character chain specified by the question, reducing higher-order belief questions to actual-world questions within the final constructed perspective. We further provide a KD45 analysis showing that RecToM's perspective construction induces a well-formed belief modality beyond simple event filtering. Experiments on ToM benchmarks, including Hi-ToM, Big-ToM, and FanToM, across multiple LLM backbones show that RecToM consistently outperforms recent advanced approaches, achieving state-of-the-art performance. Notably, RecToM reaches 100% accuracy on Hi-ToM with GPT-5.4 and Qwen3.5, a benchmark requiring higher-order ToM reasoning.

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