LLM Reasoning

LLM: Large Language Model

This field asks how language models can carry out multi-step inference across mathematics, coding, logic, science, and real-world tasks, and how to tell robust reasoning from pattern matching. Common approaches include chain-of-thought prompting, self-consistency and tree search at inference time, tool use and symbolic verification, and post-training with supervised traces, reinforcement learning from verifiable rewards, or process feedback. Researchers are also exploring latent and recurrent computation to reduce reliance on long written traces, alongside benchmarks that test compositionality, robustness, and long-horizon execution. A central tension is that more computation can improve accuracy but raise cost, while plausible explanations and correct final answers do not by themselves establish faithful, reliable reasoning.

Latest papers

931 papers105 papers in the last four weeks, up 27% on the four weeks before. 0.6% of all new papers.

Compositional Neuro-Symbolic Reasoning
Apr 2, 2026Anugyan Das, Omkar Ghugarkar, Vishvesh Bhat +1Neuro-Symbolic Reasoning Visual Reasoning
CoreThink AI · Stanford University
Batched Contextual Reinforcement: A Task-Scaling Law for Efficient Reasoning
Apr 2, 2026Bangji Yang, Hongbo Ma, Jiajun Fan +1Efficient Language Model Reasoning Efficient Language Model Inference
University of Illinois Urbana-Champaign · Tsinghua University
How LLMs Might Think
Apr 2, 2026Joseph Gottlieb, Ethan Kemp, Matthew TragerLLM Reasoning
Dept. of Philosophy, Texas Tech University · Dept. of Philosophy, New York University · Dept. of History and Philosophy of Science, University of Pittsburgh, Matthew Trager
Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs
Apr 2, 2026Abinitha Gourabathina, Inkit Padhi, Manish Nagireddy +2LLM Abstention LLM Hallucination Mitigation
MIT · IBM Research · MIT-IBM Watson AI Lab
Reliable Control-Point Selection for Steering Reasoning in Large Language Models
Apr 2, 2026Haomin Zhuang, Hojun Yoo, Xiaonan Luo +2Language Model Steering Activation Steering
University of Notre Dame
Human-Guided Reasoning with Large Language Models for Vietnamese Speech Emotion Recognition
Apr 2, 2026Truc Nguyen, Then Tran, Binh Truong +1Speech Emotion Recognition Human-in-the-Loop AI
University of Information Technology, Ho Chi Minh City, Vietnam · Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Vietnam
Fragile Reasoning: A Mechanistic Analysis of LLM Sensitivity to Meaning-Preserving Perturbations
Apr 2, 2026Shou-Tzu Han, Rodrigue Rizk, KC SantoshLanguage Model Robustness LLM Reasoning
Department of Computer Science, University of South Dakota
ThinkTwice: Jointly Optimizing Large Language Models for Reasoning and Self-Refinement
Apr 2, 2026Difan Jiao, Qianfeng Wen, Blair Yang +2RL for Language Model Reasoning LLM Reasoning
Department of Computer Science, University of Toronto · Coolwei AI Lab
Procedural Knowledge at Scale Improves Reasoning
Apr 1, 2026Di Wu, Devendra Singh Sachan, Wen-tau Yih +1Retrieval-Augmented Reasoning LLM Reasoning
University of California, Los Angeles · Meta FAIR
Reasoning Shift: How Context Silently Shortens LLM Reasoning
Apr 1, 2026Gleb Rodionov, Roman Garipov, George YakushevLanguage Model Robustness LLM Context Management
Yandex · HSE University
Hierarchical Chain-of-Thought: Enhancing LLM Reasoning Performance and Efficiency
Mar 31, 2026Xingshuai Huang, Derek Li, Bahareh Nikpour +1CoT Reasoning LLM Reasoning
Huawei Technologies Canada, Canada · Huawei Noah’s Ark Lab, Canada
Bethe Ansatz with a Large Language Model
Mar 31, 2026Balázs Pozsgay, István VonaQuantum Many-Body Physics Large Language Model-Guided Scientific Discovery
MTA-ELTE “Momentum” Integrable Quantum Dynamics Research Group, ELTE Eötvös Loránd University, Budapest, Hungary · Holographic Quantum Field Theory Research Group, HUN-REN Wigner Research Centre for Physics, Budapest, Hungary
Learning to Generate Formally Verifiable Step-by-Step Logic Reasoning via Structured Formal Intermediaries
Mar 31, 2026Luoxin Chen, Yichi Zhou, Huishuai ZhangLLM Reasoning LLM Reliability
Wangxuan Institue of Computer Technology, Peking University. · ByteDance.
ERPO: Token-Level Entropy-Regulated Policy Optimization for Large Reasoning Models
Mar 30, 2026Song Yu, Li Li, Wenwen Zhao +1RL for Language Model Reasoning RL for Language Models
School of Computer and Information Science, Southwest University, Chongqing, 400715, China
Model Capability Dominates: Inference-Time Optimization Lessons from AIMO 3
Mar 29, 2026Natapong NitarachLLM Reasoning LLM Prompting
Rethinking Easy-to-Hard: Limits of Curriculum Learning in Post-Training for Deductive Reasoning
Mar 28, 2026Maximilian Mordig, Andreas Opedal, Weiyang Liu +1Curriculum Learning Language Model Post-Training
Max Planck Institute for Intelligent Systems, Tübingen · ETH Zürich · The Chinese University of Hong Kong
SafeMath: Safe Solutions for Unsafe Math Word Problems
Mar 26, 2026Sagnik Basu, Subhrajit Mitra, Aman Juneja +3LLM Safety Alignment LLM Safety Evaluation
1Indian Institute of Technology Kharagpur · 2Cisco Systems · 3National University of Singapore
Why Does Self-Distillation (Sometimes) Degrade the Reasoning Capability of LLMs?
Mar 25, 2026Jeonghye Kim, Xufang Luo, Minbeom Kim +5Self-Distillation Language Model Distillation
Microsoft Research · KAIST · SK hynix +1
Thinking with Tables: Enhancing Multi-Modal Tabular Understanding via Neuro-Symbolic Reasoning
Mar 25, 2026Kun-Yang Yu, Zhi Zhou, Shi-Yu Tian +6Multimodal Understanding Multimodal Large Language Models
State Key Laboratory of Novel Software Technology, Nanjing University, China · School of Artificial Intelligence, Nanjing University, China · School of Intelligence Science and Technology, Nanjing University, China
HDPO: Hybrid Distillation Policy Optimization via Privileged Self-Distillation
Mar 25, 2026Ken DingRL for Language Model Reasoning LLM Reasoning
NVIDIA
Off-Policy Value-Based Reinforcement Learning for Large Language Models
Mar 24, 2026Peng-Yuan Wang, Ziniu Li, Tian Xu +8Reinforcement Learning RL for Language Model Reasoning
National Key Laboratory for Novel Software Technology & School of Artificial Intelligence, Nanjing University, China · The Chinese University of Hong Kong, Shenzhen · Shenzhen Research Institute of Big Data +1
LogicDiff: Logic-Guided Denoising Improves Zero-Shot Reasoning in Masked Diffusion Language Models
Mar 24, 2026Shaik AmanMasked Diffusion Models Diffusion Language Model Decoding
Independent Researcher, Nellore, Andhra Pradesh, India
PRISM: A Dual View of LLM Reasoning through Semantic Flow and Latent Computation
Mar 24, 2026Ruidi Chang, Jiawei Zhou, Hanjie ChenLLM Reasoning LLM Interpretability
Rice University · Stony Brook University
Explanation Generation for Contradiction Reconciliation with LLMs
Mar 24, 2026Jason Chan, Zhixue Zhao, Robert GaizauskasLLM Reasoning Reasoning Consistency in Language Models
University of Sheffield, UK
Thinking Deeper, Not Longer: Memory-Efficient Test-Time Reasoning with Depth-Recurrent Transformers for Compositional Generalization
Mar 23, 2026Hung-Hsuan ChenEfficient Transformer Inference Recurrent Transformers
Computer Science and Information Engineering National Central University Taoyuan, Taiwan
Beyond Memorization: Distinguishing Between Pattern-Based and Epistemic Reasoning in LLMs Using Epistemic Puzzles
Mar 22, 2026Adi Gabay, Gabriel Stanovsky, Liat PeterfreundEpistemic Logic LLM Reasoning
School of Computer Science and Engineering The Hebrew University of Jerusalem
Enhancing reasoning accuracy in large language models during inference time
Mar 22, 2026Vinay Sharma, Manish JainLLM Inference LLM Reasoning
ORACLE: Optimizing Reasoning Abilities of Large Language Models via Constraint-Led Synthetic Data Elicitation
Mar 22, 2026Zhuojie Yang, Wentao Wan, Keze WangSynthetic Data Generation for Language Models LLM Reasoning
School of Computer Science and Engineering, Sun Yat-sen University
Mitigating Shortcut Reasoning in Language Models: A Gradient-Aware Training Approach
Mar 21, 2026Hongyu Cao, Kunpeng Liu, Dongjie Wang +1Shortcut Learning in Language Models LLM Reasoning
Arizona State University · Clemson University · University of Kansas
Reasoning Topology Matters: Network-of-Thought for Complex Reasoning Tasks
Mar 21, 2026Fan HuangLLM Reasoning LLM Reasoning with Graphs
Indiana University Bloomington

Apr 2, 2026J/K move · Enter open · S save

Compositional Neuro-Symbolic Reasoning

Anugyan Das, Omkar Ghugarkar, Vishvesh Bhat, Asad Aali

CoreThink AI · Stanford University

Neuro-Symbolic Reasoning Visual Reasoning LLM Reasoning Program Synthesis

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We study structured abstraction-based reasoning for the Abstraction and Reasoning Corpus (ARC) and compare its generalization to test-time approaches. Purely neural architectures lack reliable combinatorial generalization, while strictly symbolic systems struggle with perceptual grounding. We therefore propose a neuro-symbolic architecture that extracts object-level structure from grids, uses neural priors to propose candidate transformations from a fixed domain-specific language (DSL) of atomic patterns, and filters hypotheses using cross-example consistency. Instantiated as a compositional reasoning framework based on unit patterns inspired by human visual abstraction, the system augments large language models (LLMs) with object representations and transformation proposals. On ARC-AGI-2, it improves base LLM performance from 16% to 24.4% on the public evaluation set, and to 30.8% when combined with ARC Lang Solver via a meta-classifier. These results demonstrate that separating perception, neural-guided transformation proposal, and symbolic consistency filtering improves generalization without task-specific finetuning or reinforcement learning, while reducing reliance on brute-force search and sampling-based test-time scaling. We open-source the ARC-AGI-2 Reasoner code (https://github.com/CoreThink-AI/arc-agi-2-reasoner).