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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SynCo: Data Synthesis Co-Training for Self-Evolving LLMs via Multi-Agent Reinforcement Learning
Oct 8, 2026Wei Yang, Shawn Li, Yuehan Qin +8Self-Evolving Agents Synthetic Data Generation for Language Models
University of Southern California · The George Washington University · Georgia Institute of Technology
Balancing Reference Guidance and Free Generation in Trajectory Rollouts for Reasoning RL
Oct 8, 2026Hanyu Wang, Nakul Agarwal, Hossein Nourkhiz Mahjoub +4LLM Reasoning RL for Language Model Reasoning
The Pennsylvania State University · Honda Research Institute USA · Honda Research Institute Japan
SemanticFold: Latent Sequence Compression SeparatesLanguage Modeling, Decodability, and Reasoning
Oct 7, 2026Mingyan Liu, Min HuangLLM Compression LLM Inference
SAPD: Step-Aligned Privileged Distillation
Oct 7, 2026Tianle Wang, Jiayu Liu, Ruizhi Zhao +1LLM Post-Training Language Model Distillation
Department of Data Science, City University of Hong Kong · Hong Kong Institute of AI for Science, City University of Hong Kong · Shenzhen University
Which Language Should a Skeleton Speak? Language Choices in Multilingual Reasoning
Oct 7, 2026HyeonSeok Lim, SeungWoo Song, Inho Won +3LLM Reasoning Cross-Lingual Reasoning in Language Models
ETRI · KAIST · Department of Artificial Intelligence, Dankook University
Collaborative Reasoning Distillation via Cross-Feedback and Coherent Curation
Oct 7, 2026Taehoon Kim, Seunggeun Cho, Dongsu HanReasoning Distillation LLM Reasoning
KAIST
The Dichotomy Between Pattern Recognition and Step-by-Step Reasoning
Oct 6, 2026Amrut Nadgir, Pratik Chaudhari, Vijay BalasubramanianLLM Reasoning Efficient Language Model Reasoning
University of Pennsylvania
ThinkFuse: Trajectory-Aware Test-Time Fusion for Small Reasoning Models
Oct 6, 2026Myunghoon Kang, Jungseob Lee, Jaehyung Seo +1Efficient Language Model Reasoning LLM Reasoning
Department of Computer Science and Engineering, Korea University · Department of Computer Science and Engineering, Konkuk University · Human-inspired AI Research
Can Language Models Learn to Reject Their Own Bad Reasoning Steps?
Oct 5, 2026Siheng Xiong, Xiaoze Liu, Yiqiao Jin +2LLM Self-Correction Language Model Decoding
Georgia Institute of Technology · Purdue University
Expanding LLM Reasoning
Oct 4, 2026Rian Atri, Evan LuoLLM Inference Efficiency Inference-Time Scaling
Keiji AI · University of California, Berkeley
Safe Context Switching for Agents in the Wild: Mitigating Subspace Interference via Orthogonal Adaptation
Oct 4, 2026Akash Das, Ishan RoyLLM Safety Alignment LLM Safety
Fidelity Investments
ReHoPER: Receding-Horizon Planning for Enhanced Reasoning
Oct 1, 2026Saeed Ahmadnia, Cornelia CarageaCompositional Reasoning Sequential Decision Making
Department of Computer Science University of Illinois Chicago
Reason in Style: Discovering and Controlling Style in Language Models
Sep 30, 2026Ioana Marinescu, Eric Karl Oermann, Kyunghyun ChoUnsupervised Learning Language Model Steering
NYU · NYU & NYU Langone Health
Exploring More, Reasoning Better: Stepwise Risk-Sensitive GRPO for Diffusion Language Models
Sep 30, 2026Yue YU, Bowen Zuo, David Crandall +2RL for Language Model Reasoning Group Relative Policy Optimization
Indiana University · University of California, Riverside
Random Recursive Models
Sep 30, 2026Jama Hussein Mohamud, Mirco RavanelliEfficient Neural Network Inference LLM Reasoning
Mila – Quebec AI Institute · Université de Montréal · Concordia University
Semifactual Credit-Augmented Policy Optimization
Sep 30, 2026Junshu Pan, Zhizhang Fu, Shulin Huang +5Prompt Sensitivity RL for Language Model Reasoning
Zhejiang University · Westlake University · Shanghai Innovation Institute +1
When a Kindergartener Solves Calculus: Measuring Capability Leakage in Role-Prompted Reasoning Models
Sep 30, 2026Pakhapoom Sarapat, Saksorn Ruangtanusak, Kunat Pipatanakul +1Large Language Model-Based Role-Play Simulation LLM Security
SCB DataX · Nanyang Technological University
OverForge: Reasoning Through Strategies and Tactics Helps Cooperative Lifelong Adaptation
Sep 30, 2026Oana Madalina Fron, Ojas Shirekar, Chirag RamanContinual Learning for LLM Agents Multi-Agent LLM Systems
Tapri Lab, Department of Pattern Recognition and Bioinformatics, Delft University of Technology, Delft, The Netherlands
Self-Repulsive Sampling for Diffusion Language Models
Sep 30, 2026Michael Helcig, Martin JaggiDiffusion Language Model Decoding Diverse Text Generation
ETH Zürich · EPFL
Can Computation from Earlier Problems Help LLMs Solve New Ones?
Sep 30, 2026Jipei He, Wenhui Tan, Xiaoyi Yu +4Memory-Augmented Language Models LLM Inference
Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China · University of Modena and Reggio Emilia, Italy
GRPO Training Dynamics for Small Language Models
Sep 30, 2026Rajat Ghosh, Vaishnavi Bhargava, Henry Wong +2RL for Language Model Reasoning Group Relative Policy Optimization
Nutanix
What Was Said, Not What Was 'Thought': Type-6 Logic for CoT Verification
Sep 29, 2026Adrian de WynterLLM Answer Verification Dynamic Epistemic Logic
Microsoft and the University of York
Privy to the Foil: Recasting Value Estimation with a Self-Privileged Critic for RLVR
Sep 29, 2026Kun Liang, Chenming Tang, Clive Bai +5Value Function Estimation RL for Language Model Reasoning
School of Computer Science, Peking University · National Key Laboratory for Multimedia Information Processing, Peking University · Foundation Model Department, Tencent
Solving Without Stopping: On-Policy Distillation at Small Scale
Sep 29, 2026Hongyang Li, Yiming Zhu, Xiao Li +3Reasoning Distillation Small Language Models
University of Luxembourg · Seafill Open-Source Community · Universit´e Paris-Saclay
What Does Post-Training Change in Multilingual Reasoning?
Sep 29, 2026Hongyang Li, Xiao Li, Caesar Wu +2Multilingual Language Model Evaluation Cross-Lingual Reasoning in Language Models
University of Luxembourg · Seafill Open-Source Community
Beam Search as Test-Time Self-Distillation via Counterfactual Contexts
Sep 29, 2026Su Ee Tan, Xiaotong Ji, Rasul Tutunov +2Language Model Distillation Self-Distillation
Huawei Noah’s Ark Lab · UCL Centre for AI
SRJudge: Empowering Large Language Models with Selective Reasoning for Fine-Grained Knowledge Concept Tagging
Sep 29, 2026Zhiwei Yang, Jiahua Yang, Huiru Lin +2RL for Language Model Reasoning AI in Education
Guangdong Institute of Smart Education, Jinan University, Guangzhou, China · School of Physical Education, Jinan University, Guangzhou, China · Guangdong Provincial Key Laboratory of Speed Capability Research, Guangzhou, China +1
Transformers Stop Thinking Too Early, and a Tiny LoRA Fixes It
Sep 29, 2026Zehao Jin, Ruixuan Deng, Junran WangTransformer LLM Fine-Tuning
Georgia Institute of Technology
ThinkingGuard: Decoding Implicit Hazards via Step-by-Step Risk Attribution in Multimodal Large Language Models
Sep 29, 2026Ruochen Zhang, Yao Huang, Yitong Sun +5Multimodal Reasoning LLM Safety
Beihang University Beijing, China · Tsinghua University Beijing, China · Institute of Artificial Intelligence Beihang University Beijing, China State Key Laboratory of AI Safety
Rethinking Reasoning Paths as Phase-Structured Trajectories
Sep 29, 2026Zhenghao He, Guangzhi Xiong, Sanchit Sinha +3Structured Reasoning Language Model Probing
Department of Computer Science, University of Virginia
Learning from Teacher Continuations at Student States
Sep 28, 2026Haojin Wang, Dylan Zhang, Huaibo Chen +8Language Model Distillation On-Policy Distillation
University of Illinois at Urbana-Champaign · Massachusetts Institute of Technology · University of Pennsylvania +2
When Confidence Rises Too Early: Detecting Shortcut Reasoning via Premature Answer Commitment
Sep 28, 2026Zhaohan Zhang, Junjie Liu, Chengzhengxu Li +6Faithfulness of Language Model Explanations Confidence Estimation in Language Models
Queen Mary University of London · Tongyi Lab, Alibaba Group · Xi’an Jiaotong University
Teach to Learn: Hint Annealing for Self-improving LLM Reasoning
Sep 28, 2026Zile Wang, Zijian Li, Haodong Wang +5Reinforcement Learning Self-Training for Language Models
The Hong Kong University of Science and Technology · Yuanbao Team, Tencent
Rewarding Novel Deductions: Solver-guided Process Supervision for Logical Reasoning
Sep 28, 2026Muhammad Asif Ali, Wenqing Wang, Huan Wang +1RL for Language Model Reasoning Process Supervision
FORTE Lab, Faculty of Science, Information Technology University, Lahore, Pakistan · College of Informatics, Huazhong Agricultural University, Wuhan, China · Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar
Knowing When Thinking Is Not Enough: Teaching Small Reasoning Models to Reason Beyond Their Parametric Knowledge
Sep 28, 2026Chanuk Lee, Minki Kang, Sangwoo Park +3Cost-Aware Inference Efficient Language Model Reasoning
KAIST
Direct Self-Evolving Optimization: Evolving LLMs without Challenger Training
Sep 28, 2026Yuyang Deng, Yu Wang, Jiayun WangSelf-Training for Language Models Large Language Model-Guided Optimization
Accenture, Center for Advanced AI · Georgia Institute of Technology
Investigating Human--AI Discrepancies via Multiple-Solution Problems
Sep 28, 2026Zihao Wang, Francesco Insulla, Andrea MontanariGenerative AI Evaluation LLM Reasoning
Department of Mathematics, Stanford University · Institute of Computational and Mathematical Engineering, Stanford University · Department of Statistics and Department of Mathematics, Stanford University
How code helps different tasks? A decompositional lens on LLM post-training
Sep 27, 2026Zheng Yu, Yiwei Li, Yishen Chen +4LLM Fine-Tuning Instruction-Tuning Data Selection
Sun Yat-sen University · Shenzhen Loop Area Institute · The Chinese University of Hong Kong, Shenzhen +1
Selecting Diverse SFT Traces Improves Post-RL Generalization
Sep 27, 2026Dylan Zhang, Mingyuan Wu, Jinning LiReasoning Diversity RL for Language Model Reasoning
University of Illinois Urbana-Champaign, work done at Google · Google
Rethinking Token Reweighting for SFT: Suppress, Reverse, and Extrapolate Learned Features
Sep 27, 2026Cunchun Li, Haonan He, Yifan Gao +4Supervised Fine-Tuning Adaptive Loss Weighting
Shanghai AI Laboratory · University of Science and Technology of China · Fudan University +2
EnigmaForge: The Question Is Hidden in the Story
Sep 24, 2026Daniel EisnerQuestion Answering Synthetic Benchmark Generation
No More Free Lunch: Corpus Task Complexity Matters as Corpora Grow
Sep 24, 2026Prasann Singhal, Amanda Bertsch, Jacob Steinhardt +1Long-Context Language Model Evaluation LLM Reasoning
UC Berkeley · Carnegie Mellon University · Allen Institute for AI
ELF-REG: Scaling Continuous Diffusion Language Models to Reasoning Tasks
Sep 24, 2026Zeyu Michael Li, William Xingxu Chen, Bingshuo Qian +2Code Generation Diffusion Language Models
Duke University · Tsinghua University
Can LLMs Reason About Runtime Behavior? A Repository-Level Dynamic Benchmark
Sep 23, 2026Hamed Taherkhani, Mohammad Abdollahi, Melika Sepidband +3LLM Evaluation Software Engineering Benchmarks
York University Toronto, Canada · The University of Texas at Dallas Texas, USA
Planned Test-Time Scaling with Coordinated Reasoning Paths
Sep 23, 2026Xueqing Wu, Langxing Bai, Hritik Bansal +5RL for Language Model Reasoning Test-Time Scaling
University of California, Los Angeles · Amazon
LOCKR: A Hidden-State Trajectory-Guided Planner for Detecting and Repairing Stable-but-Wrong Lock-In in Diffusion Language Models
Sep 23, 2026Guoshenghui Zhao, Tan Yu, Weijie ZhaoDiffusion Language Model Inference Diffusion Language Models
Rochester Institute of Technology · NVIDIA Corporation
Beyond Repeated Sampling: Learning Search Policies for LLM Reasoning
Sep 22, 2026Ismail Labiad, Matthieu Kowalski, Marc Schoenauer +2RL for Language Model Reasoning LLM Reasoning
Meta FAIR · Université Paris-Saclay, LISN, Inria, CNRS · NYU Courant Institute and CDS
Ladders of Thought: A Self-Evolving Curriculum of Progressively Simplified Reasoning Traces
Sep 22, 2026Minghui Liu, Thomas Magelinski, Dehao Yuan +2Numerical Reasoning in Language Models Curriculum Learning
University of Maryland, College Park · Capital One
Robust Failure, Conservative Repair: Textual Knowledge Distillation from Cross-Model Failures
Sep 21, 2026Andrew Ren, Haokun Liu, Chenhao TanKnowledge Distillation LLM Reasoning
University of Chicago
Efficient Reasoning Exploration via State-Conditioned Latent Steering with Progress Guidance
Sep 21, 2026Hengyuan Zhang, Chenming Shang, Zunhai Su +10Best-of-N Sampling Inference-Time Guidance
The University of Hong Kong · University of California, Los Angeles · Arizona State University +3
What Does Privileged Information Add to On-Policy Self-Distillation?
Sep 17, 2026XiuYu Zhang, Wei Chow, Junfeng Fang +2On-Policy Self-Distillation Learning Using Privileged Information
National University of Singapore
Think Thrice Before Reranking: Multi-perspective Evidence and Reasoning Integration for Text Reranking
Sep 17, 2026Lijun Liu, Zhengzong Chen, Wenyan Li +2Learning to Rank RL for Language Model Reasoning
Honor Device Co., Ltd
LLM-as-an-Improver: Turning Verification into Better Candidates
Sep 17, 2026Akiyoshi Tomihari, Yuma IchikawaLLM Answer Verification LLM Reranking
Fujitsu Limited Department of Computer Science The University of Tokyo · Fujitsu Limited RIKEN center for AIP
Clueing up LLMs with Tool-Augmented Deductive Reasoning
Sep 16, 2026Rebecca Ansell, Autumn Toney-WailsMulti-Agent LLM Systems AI Agent Benchmarks
Georgetown University · Syntheos, Corp · UNU-MERIT
What Counts as Strategic Reasoning? A Systematic Mapping of Chess Research on Humans, Engines, and Language Models
Sep 16, 2026Paolo Ciancarini, Remo PareschiChess Human-AI Decision Making
Department of Computer Science and Engineering, University of Bologna, Bologna, Italy · Stake Lab, University of Molise, Campobasso, Italy
Bellman Policy Optimization
Sep 14, 2026Zhuoqing Song, Haotian Xu, Xikun Zhang +1Reinforcement Learning RL for Language Model Reasoning
1Apodex US, Inc. · 2Princeton University
Stellar Colosseum: A Many-Agent Harness for Long-Horizon Research in Mathematics and Theoretical Computer Science
Sep 14, 2026Honghao Lin, David P. Woodruff, Yuan Deng +3Inference-Time Search Automated Theorem Proving
1Google Research. · 2Carnegie Mellon University.
Discrete Beckmann Transport Models for One-Step Language Modeling and Reasoning
Sep 14, 2026Sophia Tang, Shiyi WangOne-Step Generative Modeling Flow-Based Generative Modeling
University of Pennsylvania · Harvard University · Kempner Institute +1
HISPO: Hierarchical Importance-Sampling Policy Optimization with Entropy-Derived Segments
Sep 14, 2026Quoc-Vinh Lai-Dang, Hyo-Sang ShinRL for Language Model Reasoning Credit Assignment in RL
Cho Chun Shik Graduate School of Mobility KAIST
CWM: Controllable White-Box Meta-Prompting for Adaptive Retrieval-Augmented Generation and Reasoning Ability
Sep 14, 2026Keuntae Kim, Eunhye Jeong, Yong Suk ChoiLLM Prompting Adaptive RAG
Department of Computer Science, Hanyang University, Seoul, Korea · Department of Artificial Intelligence, Hanyang University, Seoul, Korea

Oct 8, 2026, cs.AIJ/K move · Enter open · S save

SynCo: Data Synthesis Co-Training for Self-Evolving LLMs via Multi-Agent Reinforcement Learning

Wei Yang, Shawn Li, Yuehan Qin, Yawei Wang+7

University of Southern California · The George Washington University · Georgia Institute of Technology

Self-Evolving Agents Synthetic Data Generation for Language Models LLM Reasoning RL for Language Model Reasoning

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Self-evolving LLM agents promise to improve autonomously through continual interaction and learning, reducing their dependence on manually curated supervision. Realizing this promise requires not only updating the agent, but also evolving its training experience as its capabilities change. However, most existing pipelines rely on static datasets or separately updated synthesis models, causing previously useful tasks to become trivial while overly difficult tasks remain uninformative. This growing mismatch between agent capability and training experience limits sustained self-improvement. To address this problem, we propose SynCo, an agentic data synthesis co-training framework for self-evolving LLMs based on multi-agent reinforcement learning. SynCo jointly optimizes two independently parameterized agents: a Synthesizer that constructs training tasks from the Reasoner's evolving capability state, and a Reasoner that learns from the resulting experience. Each synthesized task induces multiple Reasoner rollouts whose outcomes provide complementary rewards to both agents. Correctness feedback improves the Reasoner, while task quality, answer reliability, and outcome-grounded teachability guide the Synthesizer. Their updates are fed back into subsequent synthesis rounds, allowing the task-solving policy and its training distribution to evolve together. Extensive experiments across eight mathematical reasoning benchmarks demonstrate that SynCo substantially outperforms a broad range of existing synthetic-data methods and controlled baselines, achieving the strongest overall performance while deriving most of its gains from previously unsolved problems.

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