Collections
Discover the best community collections!
Collections including paper arxiv:2508.08221
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How to inject knowledge efficiently? Knowledge Infusion Scaling Law for Pre-training Large Language Models
Paper • 2509.19371 • Published -
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free
Paper • 2505.06708 • Published • 4 -
Selective Attention: Enhancing Transformer through Principled Context Control
Paper • 2411.12892 • Published -
A Survey of Reinforcement Learning for Large Reasoning Models
Paper • 2509.08827 • Published • 188
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Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning
Paper • 2508.08221 • Published • 48 -
Don't Overthink It: A Survey of Efficient R1-style Large Reasoning Models
Paper • 2508.02120 • Published • 19 -
Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers
Paper • 2506.23918 • Published • 88 -
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 224
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Let LLMs Break Free from Overthinking via Self-Braking Tuning
Paper • 2505.14604 • Published • 23 -
AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios
Paper • 2505.16944 • Published • 8 -
Training Step-Level Reasoning Verifiers with Formal Verification Tools
Paper • 2505.15960 • Published • 7 -
The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning
Paper • 2505.15134 • Published • 6
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Large Reasoning Models Learn Better Alignment from Flawed Thinking
Paper • 2510.00938 • Published • 58 -
What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT
Paper • 2509.19284 • Published • 22 -
Learning to Reason as Action Abstractions with Scalable Mid-Training RL
Paper • 2509.25810 • Published • 5 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 262
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lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 243 • 98 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 36 -
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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microsoft/bitnet-b1.58-2B-4T
Text Generation • 0.8B • Updated • 5.62k • 1.22k -
M1: Towards Scalable Test-Time Compute with Mamba Reasoning Models
Paper • 2504.10449 • Published • 15 -
nvidia/Llama-3.1-Nemotron-8B-UltraLong-2M-Instruct
Text Generation • 8B • Updated • 110 • 15 -
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
Paper • 2504.11536 • Published • 63
-
Large Reasoning Models Learn Better Alignment from Flawed Thinking
Paper • 2510.00938 • Published • 58 -
What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT
Paper • 2509.19284 • Published • 22 -
Learning to Reason as Action Abstractions with Scalable Mid-Training RL
Paper • 2509.25810 • Published • 5 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 262
-
How to inject knowledge efficiently? Knowledge Infusion Scaling Law for Pre-training Large Language Models
Paper • 2509.19371 • Published -
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free
Paper • 2505.06708 • Published • 4 -
Selective Attention: Enhancing Transformer through Principled Context Control
Paper • 2411.12892 • Published -
A Survey of Reinforcement Learning for Large Reasoning Models
Paper • 2509.08827 • Published • 188
-
Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning
Paper • 2508.08221 • Published • 48 -
Don't Overthink It: A Survey of Efficient R1-style Large Reasoning Models
Paper • 2508.02120 • Published • 19 -
Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers
Paper • 2506.23918 • Published • 88 -
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 224
-
lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 243 • 98 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 36 -
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
-
Let LLMs Break Free from Overthinking via Self-Braking Tuning
Paper • 2505.14604 • Published • 23 -
AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios
Paper • 2505.16944 • Published • 8 -
Training Step-Level Reasoning Verifiers with Formal Verification Tools
Paper • 2505.15960 • Published • 7 -
The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning
Paper • 2505.15134 • Published • 6
-
microsoft/bitnet-b1.58-2B-4T
Text Generation • 0.8B • Updated • 5.62k • 1.22k -
M1: Towards Scalable Test-Time Compute with Mamba Reasoning Models
Paper • 2504.10449 • Published • 15 -
nvidia/Llama-3.1-Nemotron-8B-UltraLong-2M-Instruct
Text Generation • 8B • Updated • 110 • 15 -
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
Paper • 2504.11536 • Published • 63