Models
Datasets
Spaces
Docs
Enterprise
Pricing
Log In
Sign Up

Collections

Discover the best community collections!

Collections including paper arxiv:2503.21614

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 29
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks

Paper • 2504.05118 • Published Apr 7 • 26
T1: Tool-integrated Self-verification for Test-time Compute Scaling in Small Language Models

Paper • 2504.04718 • Published Apr 7 • 42
SynWorld: Virtual Scenario Synthesis for Agentic Action Knowledge Refinement

Paper • 2504.03561 • Published Apr 4 • 18
Concept Lancet: Image Editing with Compositional Representation Transplant

Paper • 2504.02828 • Published Apr 3 • 16

🤔 Reasoning about Reasoning

papers and articles about reasoning LLMs

A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond

Paper • 2503.21614 • Published Mar 27 • 42
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model

Paper • 2503.24290 • Published Mar 31 • 62
JudgeLRM: Large Reasoning Models as a Judge

Paper • 2504.00050 • Published Mar 31 • 62
Skywork R1V: Pioneering Multimodal Reasoning with Chain-of-Thought

Paper • 2504.05599 • Published Apr 8 • 85

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL

Paper • 2503.07536 • Published Mar 10 • 88
Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model

Paper • 2503.07703 • Published Mar 10 • 37
Gemini Embedding: Generalizable Embeddings from Gemini

Paper • 2503.07891 • Published Mar 10 • 45
Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning

Paper • 2503.07572 • Published Mar 10 • 47

Reasoning Models

Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs

Paper • 2501.18585 • Published Jan 30 • 61
LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!

Paper • 2502.07374 • Published Feb 11 • 40
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling

Paper • 2502.06703 • Published Feb 10 • 153
S*: Test Time Scaling for Code Generation

Paper • 2502.14382 • Published Feb 20 • 63

Inference-paper

Inference-Time Computations for LLM Reasoning and Planning: A Benchmark and Insights

Paper • 2502.12521 • Published Feb 18
Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching

Paper • 2503.05179 • Published Mar 7 • 46
Chain of Draft: Thinking Faster by Writing Less

Paper • 2502.18600 • Published Feb 25 • 50
SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs

Paper • 2502.12134 • Published Feb 17 • 2

interesting work

MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization

Paper • 2504.00999 • Published Apr 1 • 95
Any2Caption:Interpreting Any Condition to Caption for Controllable Video Generation

Paper • 2503.24379 • Published Mar 31 • 76
Exploring the Effect of Reinforcement Learning on Video Understanding: Insights from SEED-Bench-R1

Paper • 2503.24376 • Published Mar 31 • 38
A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond

Paper • 2503.21614 • Published Mar 27 • 42

Natural Language Reinforcement Learning

Paper • 2411.14251 • Published Nov 21, 2024 • 31
Towards General-Purpose Model-Free Reinforcement Learning

Paper • 2501.16142 • Published Jan 27 • 30
Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn't

Paper • 2503.16219 • Published Mar 20 • 52
Teaching Large Language Models to Reason with Reinforcement Learning

Paper • 2403.04642 • Published Mar 7, 2024 • 50

Visual-RFT: Visual Reinforcement Fine-Tuning

Paper • 2503.01785 • Published Mar 3 • 85
When an LLM is apprehensive about its answers -- and when its uncertainty is justified

Paper • 2503.01688 • Published Mar 3 • 21
Predictive Data Selection: The Data That Predicts Is the Data That Teaches

Paper • 2503.00808 • Published Mar 2 • 56
Chain of Draft: Thinking Faster by Writing Less

Paper • 2502.18600 • Published Feb 25 • 50

RL+reason model

RL + Transformer = A General-Purpose Problem Solver

Paper • 2501.14176 • Published Jan 24 • 28
Towards General-Purpose Model-Free Reinforcement Learning

Paper • 2501.16142 • Published Jan 27 • 30
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28 • 123
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Paper • 2412.12098 • Published Dec 16, 2024 • 4

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 29
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

Inference-paper

Inference-Time Computations for LLM Reasoning and Planning: A Benchmark and Insights

Paper • 2502.12521 • Published Feb 18
Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching

Paper • 2503.05179 • Published Mar 7 • 46
Chain of Draft: Thinking Faster by Writing Less

Paper • 2502.18600 • Published Feb 25 • 50
SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs

Paper • 2502.12134 • Published Feb 17 • 2

VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks

Paper • 2504.05118 • Published Apr 7 • 26
T1: Tool-integrated Self-verification for Test-time Compute Scaling in Small Language Models

Paper • 2504.04718 • Published Apr 7 • 42
SynWorld: Virtual Scenario Synthesis for Agentic Action Knowledge Refinement

Paper • 2504.03561 • Published Apr 4 • 18
Concept Lancet: Image Editing with Compositional Representation Transplant

Paper • 2504.02828 • Published Apr 3 • 16

interesting work

MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization

Paper • 2504.00999 • Published Apr 1 • 95
Any2Caption:Interpreting Any Condition to Caption for Controllable Video Generation

Paper • 2503.24379 • Published Mar 31 • 76
Exploring the Effect of Reinforcement Learning on Video Understanding: Insights from SEED-Bench-R1

Paper • 2503.24376 • Published Mar 31 • 38
A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond

Paper • 2503.21614 • Published Mar 27 • 42

🤔 Reasoning about Reasoning

papers and articles about reasoning LLMs

A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond

Paper • 2503.21614 • Published Mar 27 • 42
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model

Paper • 2503.24290 • Published Mar 31 • 62
JudgeLRM: Large Reasoning Models as a Judge

Paper • 2504.00050 • Published Mar 31 • 62
Skywork R1V: Pioneering Multimodal Reasoning with Chain-of-Thought

Paper • 2504.05599 • Published Apr 8 • 85

Natural Language Reinforcement Learning

Paper • 2411.14251 • Published Nov 21, 2024 • 31
Towards General-Purpose Model-Free Reinforcement Learning

Paper • 2501.16142 • Published Jan 27 • 30
Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn't

Paper • 2503.16219 • Published Mar 20 • 52
Teaching Large Language Models to Reason with Reinforcement Learning

Paper • 2403.04642 • Published Mar 7, 2024 • 50

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL

Paper • 2503.07536 • Published Mar 10 • 88
Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model

Paper • 2503.07703 • Published Mar 10 • 37
Gemini Embedding: Generalizable Embeddings from Gemini

Paper • 2503.07891 • Published Mar 10 • 45
Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning

Paper • 2503.07572 • Published Mar 10 • 47

Visual-RFT: Visual Reinforcement Fine-Tuning

Paper • 2503.01785 • Published Mar 3 • 85
When an LLM is apprehensive about its answers -- and when its uncertainty is justified

Paper • 2503.01688 • Published Mar 3 • 21
Predictive Data Selection: The Data That Predicts Is the Data That Teaches

Paper • 2503.00808 • Published Mar 2 • 56
Chain of Draft: Thinking Faster by Writing Less

Paper • 2502.18600 • Published Feb 25 • 50

Reasoning Models

Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs

Paper • 2501.18585 • Published Jan 30 • 61
LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!

Paper • 2502.07374 • Published Feb 11 • 40
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling

Paper • 2502.06703 • Published Feb 10 • 153
S*: Test Time Scaling for Code Generation

Paper • 2502.14382 • Published Feb 20 • 63

RL+reason model

RL + Transformer = A General-Purpose Problem Solver

Paper • 2501.14176 • Published Jan 24 • 28
Towards General-Purpose Model-Free Reinforcement Learning

Paper • 2501.16142 • Published Jan 27 • 30
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28 • 123
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Paper • 2412.12098 • Published Dec 16, 2024 • 4

Previous
1
2
Next

Company

TOS Privacy About Careers

Website

Models Datasets Spaces Pricing Docs