Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models Paper • 2502.17387 • Published Feb 24 • 7
RLAD: Training LLMs to Discover Abstractions for Solving Reasoning Problems Paper • 2510.02263 • Published Oct 2 • 8
Recursive Introspection: Teaching Language Model Agents How to Self-Improve Paper • 2407.18219 • Published Jul 25, 2024 • 3
Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning Paper • 2310.18247 • Published Oct 27, 2023
Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning Paper • 2503.07572 • Published Mar 10 • 47
Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs Paper • 2503.01307 • Published Mar 3 • 38
Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models Paper • 2310.10639 • Published Oct 16, 2023 • 3
Vision-Language Models Provide Promptable Representations for Reinforcement Learning Paper • 2402.02651 • Published Feb 5, 2024
ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL Paper • 2402.19446 • Published Feb 29, 2024
Unfamiliar Finetuning Examples Control How Language Models Hallucinate Paper • 2403.05612 • Published Mar 8, 2024 • 3
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data Paper • 2404.14367 • Published Apr 22, 2024 • 1
RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold Paper • 2406.14532 • Published Jun 20, 2024
Recursive Introspection: Teaching Language Model Agents How to Self-Improve Paper • 2407.18219 • Published Jul 25, 2024 • 3