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QeRL: Beyond Efficiency -- Quantization-enhanced Reinforcement Learning for LLMs
Paper • 2510.11696 • Published • 181 -
Does Your Reasoning Model Implicitly Know When to Stop Thinking?
Paper • 2602.08354 • Published • 261 -
Learning When to Act or Refuse: Guarding Agentic Reasoning Models for Safe Multi-Step Tool Use
Paper • 2603.03205 • Published • 11 -
π-StepNFT: Wider Space Needs Finer Steps in Online RL for Flow-based VLAs
Paper • 2603.02083 • Published • 9
Collections
Discover the best community collections!
Collections including paper arxiv:2603.02083
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LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 58 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 52 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 45 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 64
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A Survey on Vision-Language-Action Models: An Action Tokenization Perspective
Paper • 2507.01925 • Published • 39 -
Zebra-CoT: A Dataset for Interleaved Vision Language Reasoning
Paper • 2507.16746 • Published • 34 -
MolmoAct: Action Reasoning Models that can Reason in Space
Paper • 2508.07917 • Published • 44 -
Discrete Diffusion VLA: Bringing Discrete Diffusion to Action Decoding in Vision-Language-Action Policies
Paper • 2508.20072 • Published • 32
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Foundation Models in Robotics: Applications, Challenges, and the Future
Paper • 2312.07843 • Published • 16 -
Neural Fields in Robotics: A Survey
Paper • 2410.20220 • Published • 5 -
Robots Pre-train Robots: Manipulation-Centric Robotic Representation from Large-Scale Robot Dataset
Paper • 2410.22325 • Published • 10 -
Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning
Paper • 2410.21845 • Published • 16
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lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 468 • 98 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 38 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
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AgentConductor: Topology Evolution for Multi-Agent Competition-Level Code Generation
Paper • 2602.17100 • Published • 2 -
GroupGPT: A Token-efficient and Privacy-preserving Agentic Framework for Multi-User Chat Assistant
Paper • 2603.01059 • Published • 1 -
Multi-Domain Riemannian Graph Gluing for Building Graph Foundation Models
Paper • 2603.00618 • Published -
Heterogeneous Agent Collaborative Reinforcement Learning
Paper • 2603.02604 • Published • 159
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Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning
Paper • 2407.20798 • Published • 24 -
Offline Reinforcement Learning for LLM Multi-Step Reasoning
Paper • 2412.16145 • Published • 38 -
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models
Paper • 2501.03262 • Published • 104 -
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution
Paper • 2502.18449 • Published • 75
-
QeRL: Beyond Efficiency -- Quantization-enhanced Reinforcement Learning for LLMs
Paper • 2510.11696 • Published • 181 -
Does Your Reasoning Model Implicitly Know When to Stop Thinking?
Paper • 2602.08354 • Published • 261 -
Learning When to Act or Refuse: Guarding Agentic Reasoning Models for Safe Multi-Step Tool Use
Paper • 2603.03205 • Published • 11 -
π-StepNFT: Wider Space Needs Finer Steps in Online RL for Flow-based VLAs
Paper • 2603.02083 • Published • 9
-
lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 468 • 98 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 38 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
-
LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 58 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 52 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 45 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 64
-
AgentConductor: Topology Evolution for Multi-Agent Competition-Level Code Generation
Paper • 2602.17100 • Published • 2 -
GroupGPT: A Token-efficient and Privacy-preserving Agentic Framework for Multi-User Chat Assistant
Paper • 2603.01059 • Published • 1 -
Multi-Domain Riemannian Graph Gluing for Building Graph Foundation Models
Paper • 2603.00618 • Published -
Heterogeneous Agent Collaborative Reinforcement Learning
Paper • 2603.02604 • Published • 159
-
A Survey on Vision-Language-Action Models: An Action Tokenization Perspective
Paper • 2507.01925 • Published • 39 -
Zebra-CoT: A Dataset for Interleaved Vision Language Reasoning
Paper • 2507.16746 • Published • 34 -
MolmoAct: Action Reasoning Models that can Reason in Space
Paper • 2508.07917 • Published • 44 -
Discrete Diffusion VLA: Bringing Discrete Diffusion to Action Decoding in Vision-Language-Action Policies
Paper • 2508.20072 • Published • 32
-
Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning
Paper • 2407.20798 • Published • 24 -
Offline Reinforcement Learning for LLM Multi-Step Reasoning
Paper • 2412.16145 • Published • 38 -
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models
Paper • 2501.03262 • Published • 104 -
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution
Paper • 2502.18449 • Published • 75
-
Foundation Models in Robotics: Applications, Challenges, and the Future
Paper • 2312.07843 • Published • 16 -
Neural Fields in Robotics: A Survey
Paper • 2410.20220 • Published • 5 -
Robots Pre-train Robots: Manipulation-Centric Robotic Representation from Large-Scale Robot Dataset
Paper • 2410.22325 • Published • 10 -
Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning
Paper • 2410.21845 • Published • 16