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Collections including paper arxiv:2505.14674

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

Less is More: Recursive Reasoning with Tiny Networks

Paper • 2510.04871 • Published Oct 6 • 489
When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs

Paper • 2510.07499 • Published Oct 8 • 48
Improving Context Fidelity via Native Retrieval-Augmented Reasoning

Paper • 2509.13683 • Published Sep 17 • 8
Multimodal Iterative RAG for Knowledge-Intensive Visual Question Answering

Paper • 2509.00798 • Published Aug 31 • 1

lusxvr/nanoVLM-222M

Image-Text-to-Text • 0.2B • Updated May 8 • 391 • 98
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Paper • 2503.09516 • Published Mar 12 • 36
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning

Paper • 2505.17667 • Published May 23 • 88

Scaling Law for Quantization-Aware Training

Paper • 2505.14302 • Published May 20 • 76
Reward Reasoning Model

Paper • 2505.14674 • Published May 20 • 38
Qwen3 Technical Report

Paper • 2505.09388 • Published May 14 • 318
AdaptThink: Reasoning Models Can Learn When to Think

Paper • 2505.13417 • Published May 19 • 82

A Survey on Inference Engines for Large Language Models: Perspectives on Optimization and Efficiency

Paper • 2505.01658 • Published May 3 • 39
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Paper • 2205.14135 • Published May 27, 2022 • 15
Reward Reasoning Model

Paper • 2505.14674 • Published May 20 • 38

Reasoning with Sampling: Your Base Model is Smarter Than You Think

Paper • 2510.14901 • Published Oct 16 • 47
VideoReasonBench: Can MLLMs Perform Vision-Centric Complex Video Reasoning?

Paper • 2505.23359 • Published May 29 • 39
OThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation

Paper • 2506.02397 • Published Jun 3 • 35
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 141

MLLM Reasoning, Rewarding, and Understanding

Papers on the reasoning, rewarding, and understanding of the MLLMs and LLMs

Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning

Paper • 2505.24726 • Published May 30 • 275
SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis

Paper • 2506.02096 • Published Jun 2 • 52
OThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation

Paper • 2506.02397 • Published Jun 3 • 35
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 141

PotentialApplication

Let LLMs Break Free from Overthinking via Self-Braking Tuning

Paper • 2505.14604 • Published May 20 • 23
AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios

Paper • 2505.16944 • Published May 22 • 8
Training Step-Level Reasoning Verifiers with Formal Verification Tools

Paper • 2505.15960 • Published May 21 • 7
The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning

Paper • 2505.15134 • Published May 21 • 6

J1: Incentivizing Thinking in LLM-as-a-Judge via Reinforcement Learning

Paper • 2505.10320 • Published May 15 • 24
Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures

Paper • 2505.09343 • Published May 14 • 72
Beyond 'Aha!': Toward Systematic Meta-Abilities Alignment in Large Reasoning Models

Paper • 2505.10554 • Published May 15 • 120
Scaling Reasoning can Improve Factuality in Large Language Models

Paper • 2505.11140 • Published May 16 • 7

CoRAG: Collaborative Retrieval-Augmented Generation

Paper • 2504.01883 • Published Apr 2 • 9
VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning

Paper • 2504.08837 • Published Apr 10 • 43
Mavors: Multi-granularity Video Representation for Multimodal Large Language Model

Paper • 2504.10068 • Published Apr 14 • 30
xVerify: Efficient Answer Verifier for Reasoning Model Evaluations

Paper • 2504.10481 • Published Apr 14 • 85

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

Reasoning with Sampling: Your Base Model is Smarter Than You Think

Paper • 2510.14901 • Published Oct 16 • 47
VideoReasonBench: Can MLLMs Perform Vision-Centric Complex Video Reasoning?

Paper • 2505.23359 • Published May 29 • 39
OThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation

Paper • 2506.02397 • Published Jun 3 • 35
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 141

Less is More: Recursive Reasoning with Tiny Networks

Paper • 2510.04871 • Published Oct 6 • 489
When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs

Paper • 2510.07499 • Published Oct 8 • 48
Improving Context Fidelity via Native Retrieval-Augmented Reasoning

Paper • 2509.13683 • Published Sep 17 • 8
Multimodal Iterative RAG for Knowledge-Intensive Visual Question Answering

Paper • 2509.00798 • Published Aug 31 • 1

MLLM Reasoning, Rewarding, and Understanding

Papers on the reasoning, rewarding, and understanding of the MLLMs and LLMs

Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning

Paper • 2505.24726 • Published May 30 • 275
SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis

Paper • 2506.02096 • Published Jun 2 • 52
OThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation

Paper • 2506.02397 • Published Jun 3 • 35
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 141

lusxvr/nanoVLM-222M

Image-Text-to-Text • 0.2B • Updated May 8 • 391 • 98
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Paper • 2503.09516 • Published Mar 12 • 36
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning

Paper • 2505.17667 • Published May 23 • 88

PotentialApplication

Let LLMs Break Free from Overthinking via Self-Braking Tuning

Paper • 2505.14604 • Published May 20 • 23
AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios

Paper • 2505.16944 • Published May 22 • 8
Training Step-Level Reasoning Verifiers with Formal Verification Tools

Paper • 2505.15960 • Published May 21 • 7
The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning

Paper • 2505.15134 • Published May 21 • 6

Scaling Law for Quantization-Aware Training

Paper • 2505.14302 • Published May 20 • 76
Reward Reasoning Model

Paper • 2505.14674 • Published May 20 • 38
Qwen3 Technical Report

Paper • 2505.09388 • Published May 14 • 318
AdaptThink: Reasoning Models Can Learn When to Think

Paper • 2505.13417 • Published May 19 • 82

J1: Incentivizing Thinking in LLM-as-a-Judge via Reinforcement Learning

Paper • 2505.10320 • Published May 15 • 24
Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures

Paper • 2505.09343 • Published May 14 • 72
Beyond 'Aha!': Toward Systematic Meta-Abilities Alignment in Large Reasoning Models

Paper • 2505.10554 • Published May 15 • 120
Scaling Reasoning can Improve Factuality in Large Language Models

Paper • 2505.11140 • Published May 16 • 7

A Survey on Inference Engines for Large Language Models: Perspectives on Optimization and Efficiency

Paper • 2505.01658 • Published May 3 • 39
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Paper • 2205.14135 • Published May 27, 2022 • 15
Reward Reasoning Model

Paper • 2505.14674 • Published May 20 • 38

CoRAG: Collaborative Retrieval-Augmented Generation

Paper • 2504.01883 • Published Apr 2 • 9
VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning

Paper • 2504.08837 • Published Apr 10 • 43
Mavors: Multi-granularity Video Representation for Multimodal Large Language Model

Paper • 2504.10068 • Published Apr 14 • 30
xVerify: Efficient Answer Verifier for Reasoning Model Evaluations

Paper • 2504.10481 • Published Apr 14 • 85

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