Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search
Paper
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2412.18319
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Published
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39
Reasoning, Thinking, RL and Test-Time Scaling
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Token-Budget-Aware LLM Reasoning
Paper • 2412.18547 • Published • 46 -
Efficiently Serving LLM Reasoning Programs with Certaindex
Paper • 2412.20993 • Published • 37 -
B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners
Paper • 2412.17256 • Published • 47 -
OpenAI o1 System Card
Paper • 2412.16720 • Published • 35 -
DRT-o1: Optimized Deep Reasoning Translation via Long Chain-of-Thought
Paper • 2412.17498 • Published • 22 -
Outcome-Refining Process Supervision for Code Generation
Paper • 2412.15118 • Published • 19 -
Critical Tokens Matter: Token-Level Contrastive Estimation Enhence LLM's Reasoning Capability
Paper • 2411.19943 • Published • 63 -
MALT: Improving Reasoning with Multi-Agent LLM Training
Paper • 2412.01928 • Published • 45 -
Mars-PO: Multi-Agent Reasoning System Preference Optimization
Paper • 2411.19039 • Published • 1 -
Flow-DPO: Improving LLM Mathematical Reasoning through Online Multi-Agent Learning
Paper • 2410.22304 • Published • 18 -
o1-Coder: an o1 Replication for Coding
Paper • 2412.00154 • Published • 44 -
Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions
Paper • 2411.14405 • Published • 61 -
OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models
Paper • 2410.09671 • Published • 1 -
SRA-MCTS: Self-driven Reasoning Augmentation with Monte Carlo Tree Search for Code Generation
Paper • 2411.11053 • Published • 4 -
Beyond Examples: High-level Automated Reasoning Paradigm in In-Context Learning via MCTS
Paper • 2411.18478 • Published • 37 -
Reverse Thinking Makes LLMs Stronger Reasoners
Paper • 2411.19865 • Published • 23 -
Enhancing LLM Reasoning via Critique Models with Test-Time and Training-Time Supervision
Paper • 2411.16579 • Published • 3 -
Vision-Language Models Can Self-Improve Reasoning via Reflection
Paper • 2411.00855 • Published • 5 -
Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
Paper • 2411.04282 • Published • 37 -
Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models
Paper • 2411.14432 • Published • 25 -
Critic-V: VLM Critics Help Catch VLM Errors in Multimodal Reasoning
Paper • 2411.18203 • Published • 41 -
O1 Replication Journey -- Part 2: Surpassing O1-preview through Simple Distillation, Big Progress or Bitter Lesson?
Paper • 2411.16489 • Published • 47 -
VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame Selection
Paper • 2411.14794 • Published • 13 -
Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization
Paper • 2411.10442 • Published • 87 -
LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning
Paper • 2410.02884 • Published • 54 -
LLaVA-o1: Let Vision Language Models Reason Step-by-Step
Paper • 2411.10440 • Published • 129 -
Large Language Models Can Self-Improve in Long-context Reasoning
Paper • 2411.08147 • Published • 66 -
Self-Consistency Preference Optimization
Paper • 2411.04109 • Published • 19 -
rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Paper • 2501.04519 • Published • 285 -
URSA: Understanding and Verifying Chain-of-thought Reasoning in Multimodal Mathematics
Paper • 2501.04686 • Published • 53 -
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though
Paper • 2501.04682 • Published • 99 -
BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning
Paper • 2501.03226 • Published • 44 -
Test-time Computing: from System-1 Thinking to System-2 Thinking
Paper • 2501.02497 • Published • 46 -
Virgo: A Preliminary Exploration on Reproducing o1-like MLLM
Paper • 2501.01904 • Published • 33 -
Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs
Paper • 2412.21187 • Published • 41 -
Search-o1: Agentic Search-Enhanced Large Reasoning Models
Paper • 2501.05366 • Published • 102 -
The Lessons of Developing Process Reward Models in Mathematical Reasoning
Paper • 2501.07301 • Published • 99 -
O1 Replication Journey -- Part 3: Inference-time Scaling for Medical Reasoning
Paper • 2501.06458 • Published • 31 -
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs
Paper • 2501.06186 • Published • 65 -
OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking
Paper • 2501.09751 • Published • 48 -
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
Paper • 2501.09686 • Published • 41 -
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper • 2501.12948 • Published • 420 -
Kimi k1.5: Scaling Reinforcement Learning with LLMs
Paper • 2501.12599 • Published • 123 -
s1: Simple test-time scaling
Paper • 2501.19393 • Published • 124 -
Demystifying Long Chain-of-Thought Reasoning in LLMs
Paper • 2502.03373 • Published • 58 -
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling
Paper • 2502.06703 • Published • 153 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 122 -
On the Emergence of Thinking in LLMs I: Searching for the Right Intuition
Paper • 2502.06773 • Published • 1 -
Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 68 -
Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 115 -
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
Paper • 2501.09775 • Published • 33 -
InternLM-XComposer2.5-Reward: A Simple Yet Effective Multi-Modal Reward Model
Paper • 2501.12368 • Published • 45 -
Reasoning Language Models: A Blueprint
Paper • 2501.11223 • Published • 33 -
O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning
Paper • 2501.12570 • Published • 27 -
Pairwise RM: Perform Best-of-N Sampling with Knockout Tournament
Paper • 2501.13007 • Published • 20 -
Can We Generate Images with CoT? Let's Verify and Reinforce Image Generation Step by Step
Paper • 2501.13926 • Published • 42 -
Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback
Paper • 2501.10799 • Published • 15 -
Chain-of-Retrieval Augmented Generation
Paper • 2501.14342 • Published • 58 -
RL + Transformer = A General-Purpose Problem Solver
Paper • 2501.14176 • Published • 28 -
Towards General-Purpose Model-Free Reinforcement Learning
Paper • 2501.16142 • Published • 30 -
Atla Selene Mini: A General Purpose Evaluation Model
Paper • 2501.17195 • Published • 35 -
Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs
Paper • 2501.18585 • Published • 61 -
Large Language Models Think Too Fast To Explore Effectively
Paper • 2501.18009 • Published • 24 -
Reward-Guided Speculative Decoding for Efficient LLM Reasoning
Paper • 2501.19324 • Published • 39 -
Process Reinforcement through Implicit Rewards
Paper • 2502.01456 • Published • 61 -
NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions
Paper • 2502.13124 • Published • 6 -
ACECODER: Acing Coder RL via Automated Test-Case Synthesis
Paper • 2502.01718 • Published • 29 -
Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search
Paper • 2502.02508 • Published • 23 -
QLASS: Boosting Language Agent Inference via Q-Guided Stepwise Search
Paper • 2502.02584 • Published • 17 -
LIMO: Less is More for Reasoning
Paper • 2502.03387 • Published • 62 -
Boosting Multimodal Reasoning with MCTS-Automated Structured Thinking
Paper • 2502.02339 • Published • 22 -
On Teacher Hacking in Language Model Distillation
Paper • 2502.02671 • Published • 18 -
Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning
Paper • 2502.03275 • Published • 18 -
Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2
Paper • 2502.03544 • Published • 43 -
BOLT: Bootstrap Long Chain-of-Thought in Language Models without Distillation
Paper • 2502.03860 • Published • 25 -
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
Paper • 2502.05171 • Published • 150 -
DuoGuard: A Two-Player RL-Driven Framework for Multilingual LLM Guardrails
Paper • 2502.05163 • Published • 23 -
Step Back to Leap Forward: Self-Backtracking for Boosting Reasoning of Language Models
Paper • 2502.04404 • Published • 25 -
Generating Symbolic World Models via Test-time Scaling of Large Language Models
Paper • 2502.04728 • Published • 19 -
Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning
Paper • 2502.06781 • Published • 59 -
Training Language Models for Social Deduction with Multi-Agent Reinforcement Learning
Paper • 2502.06060 • Published • 38 -
ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates
Paper • 2502.06772 • Published • 22 -
CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction
Paper • 2502.07316 • Published • 50 -
LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!
Paper • 2502.07374 • Published • 40 -
Teaching Language Models to Critique via Reinforcement Learning
Paper • 2502.03492 • Published • 24 -
Fino1: On the Transferability of Reasoning Enhanced LLMs to Finance
Paper • 2502.08127 • Published • 58 -
Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning
Paper • 2502.06533 • Published • 17 -
An Open Recipe: Adapting Language-Specific LLMs to a Reasoning Model in One Day via Model Merging
Paper • 2502.09056 • Published • 31 -
SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models
Paper • 2502.09604 • Published • 35 -
MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency
Paper • 2502.09621 • Published • 28 -
Logical Reasoning in Large Language Models: A Survey
Paper • 2502.09100 • Published • 24 -
SQuARE: Sequential Question Answering Reasoning Engine for Enhanced Chain-of-Thought in Large Language Models
Paper • 2502.09390 • Published • 16 -
Typhoon T1: An Open Thai Reasoning Model
Paper • 2502.09042 • Published • 16 -
CoT-Valve: Length-Compressible Chain-of-Thought Tuning
Paper • 2502.09601 • Published • 14 -
Mathematical Reasoning in Large Language Models: Assessing Logical and Arithmetic Errors across Wide Numerical Ranges
Paper • 2502.08680 • Published • 11 -
Small Models Struggle to Learn from Strong Reasoners
Paper • 2502.12143 • Published • 39 -
S*: Test Time Scaling for Code Generation
Paper • 2502.14382 • Published • 63 -
Diverse Inference and Verification for Advanced Reasoning
Paper • 2502.09955 • Published • 18 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 36 -
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution
Paper • 2502.18449 • Published • 75 -
Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning
Paper • 2502.14768 • Published • 47 -
AlphaMaze: Enhancing Large Language Models' Spatial Intelligence via GRPO
Paper • 2502.14669 • Published • 14 -
I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models
Paper • 2502.10458 • Published • 37 -
S^2R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning
Paper • 2502.12853 • Published • 29 -
Thinking Preference Optimization
Paper • 2502.13173 • Published • 17 -
Self-rewarding correction for mathematical reasoning
Paper • 2502.19613 • Published • 83 -
Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?
Paper • 2502.19361 • Published • 28 -
LightThinker: Thinking Step-by-Step Compression
Paper • 2502.15589 • Published • 31 -
Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn't
Paper • 2503.16219 • Published • 52 -
R1-T1: Fully Incentivizing Translation Capability in LLMs via Reasoning Learning
Paper • 2502.19735 • Published • 9 -
PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving
Paper • 2502.16111 • Published • 9 -
TAG: A Decentralized Framework for Multi-Agent Hierarchical Reinforcement Learning
Paper • 2502.15425 • Published • 9 -
The Relationship Between Reasoning and Performance in Large Language Models -- o3 (mini) Thinks Harder, Not Longer
Paper • 2502.15631 • Published • 9 -
Multimodal Inconsistency Reasoning (MMIR): A New Benchmark for Multimodal Reasoning Models
Paper • 2502.16033 • Published • 18 -
Linguistic Generalizability of Test-Time Scaling in Mathematical Reasoning
Paper • 2502.17407 • Published • 26 -
VEM: Environment-Free Exploration for Training GUI Agent with Value Environment Model
Paper • 2502.18906 • Published • 12 -
Agentic Reward Modeling: Integrating Human Preferences with Verifiable Correctness Signals for Reliable Reward Systems
Paper • 2502.19328 • Published • 23 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 113 -
Visual-RFT: Visual Reinforcement Fine-Tuning
Paper • 2503.01785 • Published • 84 -
Chain of Draft: Thinking Faster by Writing Less
Paper • 2502.18600 • Published • 49 -
Process-based Self-Rewarding Language Models
Paper • 2503.03746 • Published • 39 -
DeepSolution: Boosting Complex Engineering Solution Design via Tree-based Exploration and Bi-point Thinking
Paper • 2502.20730 • Published • 38 -
Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs
Paper • 2503.01307 • Published • 38 -
Sim-to-Real Reinforcement Learning for Vision-Based Dexterous Manipulation on Humanoids
Paper • 2502.20396 • Published • 15 -
Language Models can Self-Improve at State-Value Estimation for Better Search
Paper • 2503.02878 • Published • 10 -
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Paper • 2504.13837 • Published • 135 -
SoS1: O1 and R1-Like Reasoning LLMs are Sum-of-Square Solvers
Paper • 2502.20545 • Published • 22 -
Unified Reward Model for Multimodal Understanding and Generation
Paper • 2503.05236 • Published • 123 -
LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL
Paper • 2503.07536 • Published • 88 -
MM-Eureka: Exploring Visual Aha Moment with Rule-based Large-scale Reinforcement Learning
Paper • 2503.07365 • Published • 61 -
R1-Zero's "Aha Moment" in Visual Reasoning on a 2B Non-SFT Model
Paper • 2503.05132 • Published • 57 -
World Modeling Makes a Better Planner: Dual Preference Optimization for Embodied Task Planning
Paper • 2503.10480 • Published • 55 -
Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching
Paper • 2503.05179 • Published • 46 -
Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning
Paper • 2503.07572 • Published • 46 -
VisualPRM: An Effective Process Reward Model for Multimodal Reasoning
Paper • 2503.10291 • Published • 36 -
R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcing Learning
Paper • 2503.05379 • Published • 38 -
Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models
Paper • 2503.06749 • Published • 31 -
Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyond
Paper • 2503.10460 • Published • 29 -
R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
Paper • 2503.05592 • Published • 27 -
AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning
Paper • 2503.07608 • Published • 23 -
Implicit Reasoning in Transformers is Reasoning through Shortcuts
Paper • 2503.07604 • Published • 23 -
TTRL: Test-Time Reinforcement Learning
Paper • 2504.16084 • Published • 120 -
Learning from Failures in Multi-Attempt Reinforcement Learning
Paper • 2503.04808 • Published • 18 -
R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization
Paper • 2503.10615 • Published • 17 -
GTR: Guided Thought Reinforcement Prevents Thought Collapse in RL-based VLM Agent Training
Paper • 2503.08525 • Published • 17 -
UI-R1: Enhancing Action Prediction of GUI Agents by Reinforcement Learning
Paper • 2503.21620 • Published • 62 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 141 -
Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models
Paper • 2503.16419 • Published • 75 -
Being-0: A Humanoid Robotic Agent with Vision-Language Models and Modular Skills
Paper • 2503.12533 • Published • 68 -
Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning
Paper • 2503.15558 • Published • 50 -
SPIN-Bench: How Well Do LLMs Plan Strategically and Reason Socially?
Paper • 2503.12349 • Published • 44 -
Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey
Paper • 2503.12605 • Published • 35 -
DeepPerception: Advancing R1-like Cognitive Visual Perception in MLLMs for Knowledge-Intensive Visual Grounding
Paper • 2503.12797 • Published • 32 -
R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization
Paper • 2503.12937 • Published • 30 -
MathFusion: Enhancing Mathematic Problem-solving of LLM through Instruction Fusion
Paper • 2503.16212 • Published • 25 -
MetaLadder: Ascending Mathematical Solution Quality via Analogical-Problem Reasoning Transfer
Paper • 2503.14891 • Published • 22 -
STEVE: AStep Verification Pipeline for Computer-use Agent Training
Paper • 2503.12532 • Published • 17 -
SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks
Paper • 2503.15478 • Published • 13 -
Measuring AI Ability to Complete Long Tasks
Paper • 2503.14499 • Published • 15 -
CLS-RL: Image Classification with Rule-Based Reinforcement Learning
Paper • 2503.16188 • Published • 11 -
Temporal Consistency for LLM Reasoning Process Error Identification
Paper • 2503.14495 • Published • 11 -
Free-form language-based robotic reasoning and grasping
Paper • 2503.13082 • Published • 11 -
MPBench: A Comprehensive Multimodal Reasoning Benchmark for Process Errors Identification
Paper • 2503.12505 • Published • 11 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 119 -
Video-R1: Reinforcing Video Reasoning in MLLMs
Paper • 2503.21776 • Published • 79 -
Open Deep Search: Democratizing Search with Open-source Reasoning Agents
Paper • 2503.20201 • Published • 48 -
Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language Models
Paper • 2503.21380 • Published • 38 -
Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation
Paper • 2503.19622 • Published • 31 -
SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild
Paper • 2503.18892 • Published • 31 -
ReaRAG: Knowledge-guided Reasoning Enhances Factuality of Large Reasoning Models with Iterative Retrieval Augmented Generation
Paper • 2503.21729 • Published • 29 -
Think Twice: Enhancing LLM Reasoning by Scaling Multi-round Test-time Thinking
Paper • 2503.19855 • Published • 29 -
OpenVLThinker: An Early Exploration to Complex Vision-Language Reasoning via Iterative Self-Improvement
Paper • 2503.17352 • Published • 24 -
Embodied-Reasoner: Synergizing Visual Search, Reasoning, and Action for Embodied Interactive Tasks
Paper • 2503.21696 • Published • 23 -
Vision-R1: Evolving Human-Free Alignment in Large Vision-Language Models via Vision-Guided Reinforcement Learning
Paper • 2503.18013 • Published • 20 -
ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning
Paper • 2503.19470 • Published • 19 -
FastCuRL: Curriculum Reinforcement Learning with Progressive Context Extension for Efficient Training R1-like Reasoning Models
Paper • 2503.17287 • Published • 11 -
Unlocking Efficient Long-to-Short LLM Reasoning with Model Merging
Paper • 2503.20641 • Published • 10 -
Implicit Bias-Like Patterns in Reasoning Models
Paper • 2503.11572 • Published • 8 -
RL Tango: Reinforcing Generator and Verifier Together for Language Reasoning
Paper • 2505.15034 • Published • 5 -
Improved Visual-Spatial Reasoning via R1-Zero-Like Training
Paper • 2504.00883 • Published • 66 -
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
JudgeLRM: Large Reasoning Models as a Judge
Paper • 2504.00050 • Published • 62 -
Inference-Time Scaling for Generalist Reward Modeling
Paper • 2504.02495 • Published • 56 -
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models
Paper • 2503.24235 • Published • 54 -
Understanding R1-Zero-Like Training: A Critical Perspective
Paper • 2503.20783 • Published • 56 -
Efficient Inference for Large Reasoning Models: A Survey
Paper • 2503.23077 • Published • 46 -
A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond
Paper • 2503.21614 • Published • 42 -
Exploring the Effect of Reinforcement Learning on Video Understanding: Insights from SEED-Bench-R1
Paper • 2503.24376 • Published • 38 -
Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation
Paper • 2503.22675 • Published • 36 -
CodeARC: Benchmarking Reasoning Capabilities of LLM Agents for Inductive Program Synthesis
Paper • 2503.23145 • Published • 35 -
Rethinking RL Scaling for Vision Language Models: A Transparent, From-Scratch Framework and Comprehensive Evaluation Scheme
Paper • 2504.02587 • Published • 32 -
Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models
Paper • 2503.22165 • Published • 28 -
Z1: Efficient Test-time Scaling with Code
Paper • 2504.00810 • Published • 26 -
Expanding RL with Verifiable Rewards Across Diverse Domains
Paper • 2503.23829 • Published • 23 -
Recitation over Reasoning: How Cutting-Edge Language Models Can Fail on Elementary School-Level Reasoning Problems?
Paper • 2504.00509 • Published • 22 -
ReFeed: Multi-dimensional Summarization Refinement with Reflective Reasoning on Feedback
Paper • 2503.21332 • Published • 23 -
Effectively Controlling Reasoning Models through Thinking Intervention
Paper • 2503.24370 • Published • 19 -
Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models
Paper • 2503.24377 • Published • 18 -
When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning
Paper • 2504.01005 • Published • 15 -
GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning
Paper • 2504.00891 • Published • 14 -
Interpreting Emergent Planning in Model-Free Reinforcement Learning
Paper • 2504.01871 • Published • 12 -
m1: Unleash the Potential of Test-Time Scaling for Medical Reasoning with Large Language Models
Paper • 2504.00869 • Published • 10 -
Inference-Time Scaling for Complex Tasks: Where We Stand and What Lies Ahead
Paper • 2504.00294 • Published • 10 -
Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQL
Paper • 2503.23157 • Published • 10 -
VerifiAgent: a Unified Verification Agent in Language Model Reasoning
Paper • 2504.00406 • Published • 8 -
DeepSeek-R1 Thoughtology: Let's <think> about LLM Reasoning
Paper • 2504.07128 • Published • 86 -
Skywork R1V: Pioneering Multimodal Reasoning with Chain-of-Thought
Paper • 2504.05599 • Published • 85 -
Rethinking Reflection in Pre-Training
Paper • 2504.04022 • Published • 79 -
T1: Tool-integrated Self-verification for Test-time Compute Scaling in Small Language Models
Paper • 2504.04718 • Published • 42 -
Missing Premise exacerbates Overthinking: Are Reasoning Models losing Critical Thinking Skill?
Paper • 2504.06514 • Published • 39 -
Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models
Paper • 2504.04823 • Published • 31 -
VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks
Paper • 2504.05118 • Published • 26 -
A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility
Paper • 2504.07086 • Published • 21 -
SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement
Paper • 2504.07934 • Published • 20 -
Self-Steering Language Models
Paper • 2504.07081 • Published • 18 -
SynWorld: Virtual Scenario Synthesis for Agentic Action Knowledge Refinement
Paper • 2504.03561 • Published • 18 -
Why Reasoning Matters? A Survey of Advancements in Multimodal Reasoning (v1)
Paper • 2504.03151 • Published • 15 -
Generative Evaluation of Complex Reasoning in Large Language Models
Paper • 2504.02810 • Published • 14 -
VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning
Paper • 2504.06958 • Published • 12 -
Accelerate Parallelizable Reasoning via Parallel Decoding within One Sequence
Paper • 2503.20533 • Published • 12 -
Efficient Reinforcement Finetuning via Adaptive Curriculum Learning
Paper • 2504.05520 • Published • 11 -
xVerify: Efficient Answer Verifier for Reasoning Model Evaluations
Paper • 2504.10481 • Published • 84 -
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
Paper • 2504.11536 • Published • 62 -
Genius: A Generalizable and Purely Unsupervised Self-Training Framework For Advanced Reasoning
Paper • 2504.08672 • Published • 55 -
VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning
Paper • 2504.08837 • Published • 43 -
How Instruction and Reasoning Data shape Post-Training: Data Quality through the Lens of Layer-wise Gradients
Paper • 2504.10766 • Published • 40 -
Heimdall: test-time scaling on the generative verification
Paper • 2504.10337 • Published • 33 -
VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model
Paper • 2504.07615 • Published • 33 -
SQL-R1: Training Natural Language to SQL Reasoning Model By Reinforcement Learning
Paper • 2504.08600 • Published • 31 -
SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models
Paper • 2504.11468 • Published • 29 -
S1-Bench: A Simple Benchmark for Evaluating System 1 Thinking Capability of Large Reasoning Models
Paper • 2504.10368 • Published • 21 -
NoisyRollout: Reinforcing Visual Reasoning with Data Augmentation
Paper • 2504.13055 • Published • 19 -
A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce
Paper • 2504.11343 • Published • 19 -
Efficient Reasoning Models: A Survey
Paper • 2504.10903 • Published • 20 -
DUMP: Automated Distribution-Level Curriculum Learning for RL-based LLM Post-training
Paper • 2504.09710 • Published • 19 -
TinyLLaVA-Video-R1: Towards Smaller LMMs for Video Reasoning
Paper • 2504.09641 • Published • 16 -
Sleep-time Compute: Beyond Inference Scaling at Test-time
Paper • 2504.13171 • Published • 15 -
ReZero: Enhancing LLM search ability by trying one-more-time
Paper • 2504.11001 • Published • 15 -
M1: Towards Scalable Test-Time Compute with Mamba Reasoning Models
Paper • 2504.10449 • Published • 15 -
SimpleAR: Pushing the Frontier of Autoregressive Visual Generation through Pretraining, SFT, and RL
Paper • 2504.11455 • Published • 14 -
The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search
Paper • 2504.08066 • Published • 14 -
Reasoning Models Can Be Effective Without Thinking
Paper • 2504.09858 • Published • 12 -
VisuoThink: Empowering LVLM Reasoning with Multimodal Tree Search
Paper • 2504.09130 • Published • 12 -
Syzygy of Thoughts: Improving LLM CoT with the Minimal Free Resolution
Paper • 2504.09566 • Published • 11 -
Do PhD-level LLMs Truly Grasp Elementary Addition? Probing Rule Learning vs. Memorization in Large Language Models
Paper • 2504.05262 • Published • 11 -
SpecReason: Fast and Accurate Inference-Time Compute via Speculative Reasoning
Paper • 2504.07891 • Published • 5 -
Learning to Reason under Off-Policy Guidance
Paper • 2504.14945 • Published • 88 -
VisuLogic: A Benchmark for Evaluating Visual Reasoning in Multi-modal Large Language Models
Paper • 2504.15279 • Published • 76 -
Tina: Tiny Reasoning Models via LoRA
Paper • 2504.15777 • Published • 56 -
FlowReasoner: Reinforcing Query-Level Meta-Agents
Paper • 2504.15257 • Published • 47 -
ToolRL: Reward is All Tool Learning Needs
Paper • 2504.13958 • Published • 48 -
Learning Adaptive Parallel Reasoning with Language Models
Paper • 2504.15466 • Published • 43 -
PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models
Paper • 2504.16074 • Published • 36 -
OTC: Optimal Tool Calls via Reinforcement Learning
Paper • 2504.14870 • Published • 35 -
Perspective-Aware Reasoning in Vision-Language Models via Mental Imagery Simulation
Paper • 2504.17207 • Published • 30 -
THOUGHTTERMINATOR: Benchmarking, Calibrating, and Mitigating Overthinking in Reasoning Models
Paper • 2504.13367 • Published • 26 -
LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Paper • 2504.16078 • Published • 21 -
Generative AI Act II: Test Time Scaling Drives Cognition Engineering
Paper • 2504.13828 • Published • 18 -
Process Reward Models That Think
Paper • 2504.16828 • Published • 18