NeurIPS 2025PastMath & reasoningEfficiency
NeurIPS 2025 Workshop on Efficient Reasoning
NeurIPS 2025 ER Workshop
- Submission deadline
- Oct 2, 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 (223)
Fetched from OpenReview (v2) on 2026-06-10.
A Cooperation Index for Model Pruning
A Simple "Motivation" Can Enhance Reinforcement Finetuning of Large Reasoning Models
Activation Steering for Chain-of-Thought Compression
Active Inference Control: Steering, Not Just Scaling, Language Model Reasoning
AdaptDistill: Improving Small Language Models with Skill-Aware Teaching
AdaptInfer: Adaptive Token Pruning for Vision–Language Model Inference with Dynamical Text Guidance
Adaptive Dual Reasoner: Large Reasoning Models Can Think Efficiently by Hybrid Reasoning
Adaptive Guidance Accelerates Reinforcement Learning of Reasoning Models
Agentic NL2SQL to Reduce Computational Costs
AGENTIQL: An Agent-Inspired Multi-Expert Framework for Text-to-SQL Generation
Amortized Latent Steering: Low-Cost Alternative to Test-Time Optimization
An Empirical Study of Attention and Diversity for Adaptive Visual Token Pruning in Multimodal Reasoning Models
Analysis of Emergence of Reasoning in Language Models: Factors, Thresholds and Interpretations
Are We Scaling the Right Thing? A System Perspective on Test-Time Scaling
ARM: Adaptive Reasoning Model
Attention Guided Alignment in Efficient Vision-Language Models
AutoL2S: Auto Long-Short Reasoning for Efficient Large Language Models
Bayesian Social Deduction with Graph-Informed Language Models
BenchHub: A Unified Benchmark Suite for Holistic and Customizable LLM Evaluation
Beyond Static Cutoffs: One-Shot Dynamic Thresholding for Diffusion Language Models
Boundary Guidance for Efficient 3D CT Vision–Language Reasoning
Breadcrumbs Reasoning: Memory-Efficient Reasoning with Compression Beacons
Budget-aware Test-time Scaling via Discriminative Verification
Calibrated Reasoning: An Explanatory Verifier for Dynamic and Efficient Problem-Solving
Can Explanations Improve Recommendations? A Joint Optimization with LLM Reasoning
CaRT: Teaching LLM Agents to Know When They Know Enough
CATS: Category-Aware Token-level Steering for Training-Free Redundancy Reduction in Large Reasoning Models
Causal Reflection with Language Models
CGES: Confidence-Guided Early Stopping for Efficient and Accurate Self-Consistency
Chopping Trees: Semantic Similarity Based Dynamic Pruning for Tree-of-Thought Reasoning
Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner
COMPACT: Common-token Optimized Model Pruning Across Channels and Tokens
Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision
Compute When Worth It: Risk Control for Reasoning on a Compute Budget
Confidence-Coverage Gating for Early Exit
ConstrainedSQL: Training LLMs for Text2SQL via Constrained Reinforcement Learning
Correct Reasoning Paths Visit Shared Decision Pivots
DA-CoTD: Efficient Chain-of-Thought Reasoning with Difficulty-Aware CoT-Distillation
DAG-Math: Graph-Guided Mathematical Reasoning in LLMs
Data Diversification Methods In Alignment Enhance Math Performance In LLMs
Data Scaling Isn't Enough: Towards Improving Compositional Reasoning in Video-Language Models
Decomposing Reasoning Efficiency in Large Language Models
Deep Think with Confidence
Delta Activations: A Representation for Finetuned Large Language Models
Demystifying and Enhancing the Efficiency of Interleaved Reasoning-Search LLM Agents
Demystifying Delays in Reasoning: A Pilot Temporal and Token Analysis of Reasoning Systems
DHP: Discrete Hierarchical Planning for HRL Agents
DiFFPO: Training Diffusion LLMs to Reason Fast and Furious via Reinforcement Learning
Diffusion Language Models Know the Answer Before Decoding
DISCO Balances the Scales: Adaptive Domain- and Difficulty-Aware Reinforcement Learning on Imbalanced Data
Distilling Multi-modal Large Language Models for Autonomous Driving
DIVERSED: Relaxed Speculative Decoding via Dynamic Ensemble Verification
DMORE: Differentiable Mixture-of-Reasoning-Experts with Uncertainty-Guided Multi-Level Routing
Don’t Let It Hallucinate: Premise Verification via Retrieval-Augmented Logical Reasoning
DRPO: Efficient Reasoning via Decoupled Reward Policy Optimization
DTS: Enhancing Large Reasoning Models via Decoding Tree Sketching
Dual-Head Reasoning Distillation: Improving Classifier Accuracy with Train-Time-Only Reasoning
e1: Learning Adaptive Control of Reasoning Effort
EcoSpa: Efficient Transformer Training with Coupled Sparsity
Efficient Long CoT Reasoning in Small Language Models
Efficient Parallel Samplers for Recurrent-Depth Models and Their Connections to Diffusion Language Models
Efficient Post-Training for Industry-Specialized Reasoning in Small Language Models
Efficient Reasoning at Fixed Test-Time Cost via Length-Aware Attention Priors and Gain-Aware Training
Efficient Reinforcement Finetuning via Adaptive Curriculum Learning
Efficient Reinforcement Learning for Large Language Models with Intrinsic Exploration
Efficient RL Training for Reasoning Models via Length-Aware Optimization
Efficient Sparse Decoding for Test-Time Scaling with KV Cache Disaggregation and Asynchronism
Efficient Test-Time Scaling via Self-Calibration
Episode-Level Multimodal KV Caching for Embodied Question Answering
Evaluating the Safety and Skill Reasoning of Large Reasoning Models Under Compute Constraints
EWoRA: Expert Weighted Low-Rank Adaptation for Reasoning over Heterogeneous Data
Extending AutoCompressors via Surprisal-Based Dynamic Segmentation
Feature-Level Knowledge Distillation from LMM for Enhanced Image Classification
Federation of Agents: A Semantics-Aware Communication Fabric for Large-Scale Agentic AI
Finding the Sweet Spot: Trading Quality, Cost, and Speed During Inference-Time LLM Reflection
Fractional Reasoning via Latent Steering Vectors Improves Inference Time Compute
Free Draft-and-Verification: Toward Lossless Parallel Decoding for Diffusion Large Language Models
From Evidence to Trajectory: Abductive Reasoning Path Synthesis for Retrieval-Augmented Generation Agents Development
From Long to Short: LLMs Excel at Trimming Own Reasoning Chains
FrugalRAG: Learning to retrieve and reason for multi-hop QA
GEAR-X: Expanders for Next-Gen KV Cache Compression
Generalized Parallel Scaling with Interdependent Generations
Generating Domain Specific Natural Language SAT Reasoning Datasets
Hard Examples Are All You Need: Maximizing GRPO Post-Training Under Annotation Budgets
Harnessing Negative Signals: Reinforcement Distillation from Teacher Data for LLM Reasoning
Hierarchical Planning Agent for Web-Browsing Tasks
Hold Onto That Thought: Assessing KV Cache Compression On Reasoning
How Does RL Induce Skill Composition? A Case Study Using Countdown
How Far Can SLMs Go Without `Thinking' in the LLM-as-a-Judge Paradigm?
How Weight Pruning Destroys Chain-of-Thought Reasoning in Language Reasoning Models: A Model Similarity and Faithfulness Correlation Analysis
HybridCoT: Interleaving Latent and Text Chain-of-Thought for Efficient Reasoning
Hydra: A Modular Architecture for Efficient Long-Context Reasoning
Improving LLM Reasoning under Uncertainty with Coach-Player Multi-agent
In Good GRACEs: Principled Teacher Selection for Knowledge Distillation
In-the-Flow Agentic System Optimization for Effective Planning and Tool Use
Inference-Time Chain-of-Thought Pruning with Latent Informativeness Signals
Influence Functions for Efficient Data Selection in Reasoning
Information-Theoretic Bounds on Multi-Step Reasoning: When is Chain-of-Thought Provably Necessary?
Inpainting-Guided Policy Optimization for Diffusion Large Language Models
Instance-Adaptive Inference-Time Scaling with Calibrated Process Reward Models
Internal Value Functions: Leveraging Hidden States for Efficient Test-Time Scaling in Large Reasoning Models
iOS as Acceleration
It Takes Two: Your GRPO Is Secretly DPO
Just Enough Thinking: Efficient Reasoning with Adaptive Length Penalties Reinforcement Learning
Lark: Biologically Inspired Neuroevolution for Multi-Stakeholder LLM Agents
LayerMerge: Modality-Agnostic Depth Pruning for Efficient Foundation Model Deployment
Learnable Adaptive KV-cache Compression
Learning to Reason Across Parallel Samples for LLM Reasoning
Learning to Reason via Mixture-of-Thought for Logical Reasoning
Learning to See Before Seeing: Demystifying LLM Visual Priors from Language Pre-training
Less is Not Worse: Effective Reasoning Without Complete Reasoning Chains
Local Coherence or Global Validity? Investigating RLVR Traces in Math Domains
LOGCA: Layer-Optimized GPU-CPU Allocation for Efficient Resource Management in Large-Scale Models
Logit–Entropy Adaptive Stopping Heuristic for Efficient Chain-of-Thought Reasoning
Long-Context Modeling with Dynamic Hierarchical Sparse Attention for On-Device LLMs
LoRA-Guided PPO for Cost-Aware and Compute-Efficient Agent Orchestration
LSPO: Length-aware Dynamic Sampling for Policy Optimization in LLM Reasoning
M-GRPO: Stabilizing Self-Supervised Reinforcement Learning for Large Language Models with Momentum-Anchored Policy Optimization
M1: Towards Scalable Test-Time Compute with Mamba Reasoning Models
Mechanistic Interpretability of GPT-2: Lexical and Contextual Layers in Sentiment Analysis
MetroRLHF: Enabling Memory-Effective Training for On-Policy RLHF via Adaptive Sequence Streaming
Mimicking the Physicist's Eye : A VLM-centric Approach for Physics Formula Discovery
Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing
MLM: Multi-linguistic LoRA Merging
Mode-conditioning unlocks superior test-time compute scaling
Multi-Head Low-Rank Attention
MultiGA: Leveraging Multi-Source Seeding in Genetic Algorithms
Multimodal Chain of Continuous Thought for Latent-Space Reasoning in Vision-Language Models
Muon: Training and Trade-offs with Latent Attention and MoE
NaturalThoughts: Selecting and Distilling Reasoning Traces for General Reasoning Tasks
Nested-ReFT: Efficient Reinforcement Learning for Large Language Model Fine-Tuning via Off-Policy Rollouts
No Question, No Passage, No Problem: Investigating Artifact Exploitation and Reasoning in Multiple-Choice Reading Comprehension
Not All Bits Are Equal: Scale-Dependent Memory Optimization Strategies for Reasoning Models
Not All Thoughts Matter: Selective Attention for Efficient Reasoning
OckBench: Tokens are Not to Be Multiplied without Necessity
Off-Trajectory Reasoning: Can LRMs Collaborate on Reasoning Trajectory?
On the Role of Temperature Sampling in Test-Time Scaling
On the Rollout-Training Mismatch in Modern RL Systems
One Sample to Rule Them All: Extreme Data Efficiency in RL Scaling
One-Pass to Reason: Token Duplication and Block-Sparse Mask for Efficient Fine-Tuning on Multi-Turn Reasoning
Optimal Self-Consistency for Efficient Reasoning with Large Language Models
OptimalThinkingBench: Evaluating Over and Underthinking in LLMs
Optimizing Reasoning Efficiency through Prompt Difficulty Prediction
ORPO-Distill: Mixed-Policy Preference Optimization for Cross-Architecture LLM Distillation
Parallel-R1: Towards Parallel Thinking via Reinforcement Learning
Pay-Per-Search Models are Abstention Models
Performative Thinking? The Brittle Correlation Between CoT Length and Problem Complexity
PHLoRA: data-free Post-hoc Low-Rank Adapter extraction from full-rank checkpoint
PosS:Position Specialist Generates Better Draft for Speculative Decoding
PREMISE: Scalable and Strategic Prompt Optimization for Efficient Mathematical Reasoning in Large Reasoning Models
Probe-Rewrite-Evaluate: A Workflow for Reliable Benchmarks and Quantifying Evaluation Awareness
ProofSketch: Efficient Verified Reasoning for Large Language Models
ProRefine: Inference-time Prompt Refinement with Textual Feedback
Prosperity before Collapse: How Far Can Off-Policy RL Reach with Stale Data on LLMs?
ProtFunAgent: Agentic LLM Cascades for Low-Resource Protein Function Gap-Filling via Homology RAG and Ontology-Constrained Decoding
Pull Requests with Bugs: Benchmarking Model Reasoning for Code Reviews
RaanA: A Fast, Flexible, and Data-Efficient Post-Training Quantization Algorithm
RAT: Bridging RNN Efficiency and Attention Accuracy via Chunk-based Sequence Modeling
Re-FORC: Adaptive Reward Prediction for Efficient Chain-of-Thought Reasoning
Reasoning Elicitation is Scale-Dependent
Reasoning Models Better Express Their Confidence
Reasoning Models Can Be Accurately Pruned via Chain-of-Thought Reconstruction
Reasoning Models Reason Inefficiently
Reasoning Under Pressure: LLMs in Competitive Pokémon Battles
Reasoning with Fewer Eyes: Efficient Visual Token Withdrawal for Multimodal Reasoning
Reasoning-Focused Evaluation of Efficient Long-Context Inference Techniques
Reasoning-Intensive Regression
Reject Only Critical Tokens: Pivot-Aware Speculative Decoding
Resa: Transparent Reasoning Models via SAEs
Reuse, Don't Recompute: Efficient Large Reasoning Model Inference via Memory Orchestration
Reversal Is Structural: Concept-Aware Post-Training Recovers Rare, Deep Mathematical Skills
RoiRL: Efficient, Self-Supervised Reasoning with Offline Iterative Reinforcement Learning
Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains
Sample, Align, Synthesize: Graph-Based Response Synthesis with ConGrs
SATBench: Benchmarking LLMs Logical Reasoning via Automated Puzzle Generation from SAT Formulas
Scheherazade: Evaluating Chain-of-Thought Math Reasoning in LLMs with Chain-of-Problems
Scratchpad Thinking: Alternation Between Storage and Computation in Latent Reasoning Models
SeqFusion: Scalable Long-Context Reasoning through Parallel Fragment Fusion and Memory-Augmented Attention
SGD-KV: Summarization Guided KV Cache Compression
Short-to-Long Distillation: Learning Long-Context Policies from Short-Context Supervision
SituationalPriv: A Context-Aware Framework for Privacy Detection and Protection in Vision-Language Models
Software Engineering Agents for Embodied Controller Generation : A Study in Minigrid Environments
SparseVILA-R1: Decoupling Visual Sparsity for Efficient VLM Reasoning
SpatialTraceGen: High-Fidelity Traces for Efficient VLM Spatial Reasoning Distillation
SpecReason: Fast and Accurate Inference-Time Compute via Speculative Reasoning
SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models
SRT: Accelerating Reinforcement Learning via Speculative Rollout with Tree-Structured Cache
Stable Reinforcement Learning for Efficient Reasoning
Statistical Early Stopping for Reasoning Models
Superposition Reasoning Model
SwiftSolve: A Self-Iterative, Complexity-Aware Multi-Agent Framework for Competitive Programming
Teaching Pretrained Language Models to Think Deeper with Retrofitted Recurrence
The Conductor and the Engine: A Path Towards Co-Designed Reasoning
The Effect of Dataset Diversification on Mathematical Problem Solving Performance
The Impact of Quantization on Large Reasoning Model Reinforcement Learning
The Path Not Taken: RLVR Provably Learns Off the Principals
The Sequential Edge: Inverse-Entropy Voting Beats Parallel Self-Consistency at Matched Compute
The Virtues of Brevity: Avoid Overthinking in Parallel Test-Time Reasoning
The Zero-Step Thinking: An Empirical Study of Mode Selection as Harder Early Exit in Reasoning Models
Think Straight, Stop Smart: Structured Reasoning for Efficient Multi-Hop RAG
ThinkBrake: Mitigating Overthinking in Tool Reasoning
Thinking in Many Modes: How Composite Reasoning Elevates Large Language Model Performance with Limited Data
TimeAlign: Contamination-Aware Evaluation for Resource-Constrained Foundation Models
To See or To Read: User Behavior Reasoning in Multimodal LLMs
Towards a Mechanistic Understanding of Robustness in Finetuned Reasoning Models
Towards Label-Free Biological Reasoning Synthetic Dataset Creation via Uncertainty Filtering
Towards Quantifying Bias in Large Language Models
TRACE: Transparent Reasoning and Attribution Chains for Extended Multimodal Contexts
Training Dynamics Impact Quantization Degradation
Uncovering Graph Reasoning in Decoder-only Transformers with Circuit Tracing
Understanding and Steering the Cognitive Behaviors of Reasoning Models at Test-Time
UniFormer: Unified and Efficient Transformer for Reasoning Across General and Custom Computing
Universal Properties of Activation Sparsity in Modern Large Language Models
Verbalized Algorithms
What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT
What’s Missing in Vision-Language Models? Probing Their Struggles with Causal Order Reasoning
When Do Symbolic Solvers Enhance Reasoning in Large Language Models?
When Reasoning Meets Its Laws
When Visualizing is the First Step to Reasoning: MIRA, a Benchmark for Visual Chain-of-Thought
Where do Reasoning Models make a Difference? Follow the Reasoning Leader for Efficient Decoding
Why GRPO Needs Normalization: A Local-Curvature Perspective on Adaptive Gradients
Wide-In, Narrow-Out: Revokable Decoding for Efficient and Effective DLLM
WST: Weak-to-Strong Knowledge Transfer via Reinforcement Learning