Bootstrapping Exploration with Group-Level Natural Language Feedback in Reinforcement Learning
Paper • 2603.04597 • Published • 210
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SII-Enigma/Llama3.2-8B-Ins-AMPO
Text Generation • 8B • Updated • 102 -
Understanding R1-Zero-Like Training: A Critical Perspective
Paper • 2503.20783 • Published • 59 -
Planner-R1: Reward Shaping Enables Efficient Agentic RL with Smaller LLMs
Paper • 2509.25779 • Published • 19 -
On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes
Paper • 2306.13649 • Published • 33 -
Unfamiliar Finetuning Examples Control How Language Models Hallucinate
Paper • 2403.05612 • Published • 3 -
Reinforcement Learning Finetunes Small Subnetworks in Large Language Models
Paper • 2505.11711 • Published • 11 -
Reinforcement Learning via Self-Distillation
Paper • 2601.20802 • Published • 43 -
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 238 -
AI Can Learn Scientific Taste
Paper • 2603.14473 • Published • 423 -
π_{0.5}: a Vision-Language-Action Model with Open-World Generalization
Paper • 2504.16054 • Published • 4 -
Sparse but Critical: A Token-Level Analysis of Distributional Shifts in RLVR Fine-Tuning of LLMs
Paper • 2603.22446 • Published • 10 -
FIPO: Eliciting Deep Reasoning with Future-KL Influenced Policy Optimization
Paper • 2603.19835 • Published • 337 -
On the Direction of RLVR Updates for LLM Reasoning: Identification and Exploitation
Paper • 2603.22117 • Published • 29