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Single-Rollout Asynchronous Optimization for Agentic Reinforcement Learning
Paper • 2607.07508 • Published • 32 -
Proximal Policy Optimization Algorithms
Paper • 1707.06347 • Published • 12 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 12 -
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning
Paper • 2012.13255 • Published • 6
Collections
Discover the best community collections!
Collections including paper arxiv:2402.03300
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DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 148 -
Proximal Policy Optimization Algorithms
Paper • 1707.06347 • Published • 12 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 71 -
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Paper • 2402.03300 • Published • 149
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VESPO: Variational Sequence-Level Soft Policy Optimization for Stable Off-Policy LLM Training
Paper • 2602.10693 • Published • 222 -
Reinforced Attention Learning
Paper • 2602.04884 • Published • 30 -
Learning to Reason in 13 Parameters
Paper • 2602.04118 • Published • 6 -
LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters
Paper • 2405.17604 • Published • 4
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DeepSeekMath-V2: Towards Self-Verifiable Mathematical Reasoning
Paper • 2511.22570 • Published • 96 -
DeepSeek-OCR: Contexts Optical Compression
Paper • 2510.18234 • Published • 95 -
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper • 2501.12948 • Published • 463 -
Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures
Paper • 2505.09343 • Published • 79
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SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 127 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 65 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 13 -
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Paper • 2305.10601 • Published • 15
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GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization
Paper • 2601.05242 • Published • 234 -
On Predictability of Reinforcement Learning Dynamics for Large Language Models
Paper • 2510.00553 • Published • 9 -
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models
Paper • 2501.03262 • Published • 103 -
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Paper • 2402.03300 • Published • 149
-
Proximal Policy Optimization Algorithms
Paper • 1707.06347 • Published • 12 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 71 -
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Paper • 2402.03300 • Published • 149 -
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper • 2501.12948 • Published • 463
-
Single-Rollout Asynchronous Optimization for Agentic Reinforcement Learning
Paper • 2607.07508 • Published • 32 -
Proximal Policy Optimization Algorithms
Paper • 1707.06347 • Published • 12 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 12 -
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning
Paper • 2012.13255 • Published • 6
-
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 148 -
Proximal Policy Optimization Algorithms
Paper • 1707.06347 • Published • 12 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 71 -
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Paper • 2402.03300 • Published • 149
-
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 127 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 65 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 13 -
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Paper • 2305.10601 • Published • 15
-
VESPO: Variational Sequence-Level Soft Policy Optimization for Stable Off-Policy LLM Training
Paper • 2602.10693 • Published • 222 -
Reinforced Attention Learning
Paper • 2602.04884 • Published • 30 -
Learning to Reason in 13 Parameters
Paper • 2602.04118 • Published • 6 -
LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters
Paper • 2405.17604 • Published • 4
-
GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization
Paper • 2601.05242 • Published • 234 -
On Predictability of Reinforcement Learning Dynamics for Large Language Models
Paper • 2510.00553 • Published • 9 -
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models
Paper • 2501.03262 • Published • 103 -
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Paper • 2402.03300 • Published • 149
-
DeepSeekMath-V2: Towards Self-Verifiable Mathematical Reasoning
Paper • 2511.22570 • Published • 96 -
DeepSeek-OCR: Contexts Optical Compression
Paper • 2510.18234 • Published • 95 -
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper • 2501.12948 • Published • 463 -
Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures
Paper • 2505.09343 • Published • 79
-
Proximal Policy Optimization Algorithms
Paper • 1707.06347 • Published • 12 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 71 -
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Paper • 2402.03300 • Published • 149 -
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper • 2501.12948 • Published • 463