NeurIPS 2025PastMath & reasoningLarge language models
First Workshop on Foundations of Reasoning in Language Models
FoRLM 2025
- Submission deadline
- Sep 9, 2025, 11:59 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (101)
Fetched from OpenReview (v2) on 2026-06-10.
"Think Just Enough: Sequence-Level Entropy as a Confidence Signal for LLM Reasoning"
ActivationReasoning: Logical Reasoning in Latent Activation Spaces
Agentic Reasoning and Tool Integration for LLMs via Reinforcement Learning
ARS: Adaptive Reasoning Suppression for Efficient Large Reasoning Language Models
Asking the Missing Piece: Context-Driven Clarification for Ambiguous VQA
Benchmarking Temporal Reasoning: Can Large Language Models Navigate Time When Stories Refuse to Follow a Straight Line?
Benefits and Limitations of Communication in Multi-Agent Reasoning
Beyond 'Aha!': Toward Systematic Meta-Abilities Alignment in Large Reasoning Models
Beyond Introspection: Reinforcing Thinking via Externalist Behavioral Feedback
Beyond Pass@k: Breadth-Depth Metrics for Reasoning Boundaries
Beyond Semantics: The Unreasonable Effectiveness of Reasonless Intermediate Tokens
Can Reasoning Models Obfuscate Reasoning? Stress-Testing Chain-of-Thought Monitorability
Can We Predict Alignment Before Models Finish Thinking? Towards Monitoring Misaligned Reasoning Models
CARE: Turning LLMs Into Causal Reasoning Expert
CaRT: Teaching LLM Agents to Know When They Know Enough
Chain-of-Frames: Advancing Video Understanding in Multimodal LLMs via Frame-Aware Reasoning
Characterizing Deep Research: A Benchmark and Formal Definition
Characterizing good teachers for distillation using gradient features
Correct Reasoning Paths Visit Shared Decision Pivots
COSMIR: Chain Orchestrated Structured Memory for Iterative Reasoning over Long Context
Data Diversification Methods In Alignment Enhance Math Performance In LLMs
Decoupling the "What" and "Where" With Polar Coordinate Positional Embedding
Deep sequence models tend to memorize geometrically, we do not understand why.
Deep Thinking via Recursive Self-Aggregation
Demystifying Scientific Problem-Solving in LLMs by Probing Knowledge and Reasoning
Diagnosing Moral Reasoning: A Benchmark for Evaluating Consistency and Robustness in Large Language Models
Discerning What Matters: A Multi-Dimensional Assessment of Moral Competence in LLMs
Dormant Reasoning Circuits in RL-Trained Language Models
EAT: Entropy After $\langle/ \tt Think \rangle$ for reasoning model early exiting
Efficient First-Order Logic-Based Method for Enhancing Logical Reasoning Capabilities of LLMs
Executable Counterfactuals: Improving LLMs' Causal Reasoning Through Code
Exploration with Foundation Models: Capabilities, Limitations, and Hybrid Approaches
Exploring System 1 and 2 communication for latent reasoning in LLMs
Fathom-Search-4B: Unlocking Long-Horizon DeepSearch via RL
FlagEval Findings Report: A Preliminary Evaluation of Large Reasoning Models on Automatically Verifiable Textual and Visual Questions
FRIT: Using Causal Importance to Improve Chain-of-Thought Faithfulness
GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning
GraphARC: A Comprehensive Benchmark for Graph-Based Abstract Reasoning
Grounding LLM Reasoning with Knowledge Graphs
Hessian-Enhanced Token Attribution (HETA): Interpreting Autoregressive Language Models
Hop, Skip, and Overthink: Diagnosing Why Reasoning Models Fumble during Multi-Hop Analysis
How Instruction and Reasoning Data shape Post-Training: Data Quality through the Lens of Layer-wise Gradients
How to Train Your Advisor: Steering Black-Box LLMs with Advisor Models
Influence Functions for Efficient Data Selection in Reasoning
Investigating Advanced Reasoning of Large Language Models via Black-Box Interaction
Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens
Is Random Attention Sufficient for Sequence Modeling?
Label-Invariant Hessian Regularization Mitigates Grokking in Mathematical Reasoning
Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models
Language Models That Think, Chat Better
Learning Composable Chains-of-Thought
Learning to Answer from Correct Demonstrations
Limits of Emergent Reasoning of Large Language Models in Agentic Frameworks for Deterministic Games
LLM CHESS: Benchmarking Reasoning and Instruction-Following in LLMs through Chess
Lost at the Beginning of Reasoning
MagiC: Evaluating Multimodal Cognition Toward Grounded Visual Reasoning
Monitor-Generate-Verify (MGV): Formalising Metacognitive Theory for Language Model Reasoning
Multi-module GRPO: Composing Policy Gradients and Prompt Optimization for Language Model Programs
Multiple Token Divergence: A Measure of In-Context Computation Density
Murphy: Reflective Multi-Turn Reinforcement Learning for Self-Correcting Code Generation in Large Language
Not All Thoughts Matter: Selective Attention for Efficient Reasoning
Observer, Not Player: Simulating Theory of Mind in Large Language Models through Game Observation
OIBench: Benchmarking Strong Reasoning Models with Olympiad in Informatics
On the generalization of language models from in-context learning and finetuning: a controlled study
On the Optimization Dynamics of RLVR: Gradient Gap and Step Size Scaling
On the Role of Temperature Sampling in Test-Time Scaling
OpenThoughts: Data Recipes for Reasoning Models
Peek-a-Boo Reasoning: Contrastive Region Masking in MLLMs
POLYMATH: A Challenging Multi-modal Mathematical Reasoning Benchmark
R1-Compress: Long Chain-of-Thought Compression via Chunk Compression and Search
Reasoning Large Language Model Errors Arise from Hallucinating Critical Problem Features
Reasoning Through Chess: How Reasoning Evolves from Data Through Fine-Tuning and Reinforcement Learning
Reasoning Up the Instruction Ladder for Controllable Language Models
Reasoning with Preference Constraints: A Benchmark for Language Models in Many-to-One Matching Markets
ReFIne: A Framework for Trustworthy Large Reasoning Models with Reliability, Faithfulness, and Interpretability
Reinforcement Learning Improves Traversal of Hierarchical Knowledge in LLMs
Representational Homomorphism Error Predicts Compositional Generalization In Language Models
Reverse-KL Reinforcement Learning Can Sample From Multiple Diverse Modes
RL Fine-Tuning Heals the OOD Forgetting in SFT
RL in Name Only? Analyzing the Structural Assumptions in RL post-training for LLMs
RoBoN: Routed Online Best-of-n for Test-Time Scaling with Multiple LLMs
Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning
Scratchpad Thinking: Alternation Between Storage and Computation in Latent Reasoning Models
Skill-Targeted Adaptive Training
SLR: Automated Synthesis for Scalable Logical Reasoning
Smaller Models, Smarter Rewards: A Two-Sided Approach to Process and Outcome Rewards
Steering LLMs’ Reasoning With Activation State Machines
T-FIX: Text-Based Explanations with Features Interpretable to eXperts
TATTO: Tool-Augmented Thinking PRM for Tabular Reasoning
Test-Time Alignment for Large Language Models via Textual Model Predictive Control
The Ends Justify the Thoughts: RL-Induced Motivated Reasoning in LLMs
To Think or Not to Think: Exploring the Unthinking Vulnerability in Large Reasoning Models
TokUR: Token-Level Uncertainty Estimation for Large Language Mode Reasoning
Towards Understanding the Optimization Landscape of GRPO and its Variants
Tracing the Traces: Latent-Space Metrics for Efficient and Accurate Reasoning
TS-Agent: A Time Series Reasoning Agent with Iterative Statistical Insight Gathering
Understanding the Test-Time Computing of Transformers: A Theoretical Study on In-Context Linear Regression
UQ: Assessing Language Models on Unsolved Questions
Variation in Verification: Understanding Verification Dynamics in Large Language Models
Visual-TableQA: Open-Domain Benchmark for Reasoning over Table Images
Weak-to-Strong Generalization with Failure Trajectories