ComputerRL: Scaling End-to-End Online Reinforcement Learning for Computer Use Agents Paper • 2508.14040 • Published Aug 19 • 3
SATQuest: A Verifier for Logical Reasoning Evaluation and Reinforcement Fine-Tuning of LLMs Paper • 2509.00930 • Published Aug 31 • 4
CAMEL: Continuous Action Masking Enabled by Large Language Models for Reinforcement Learning Paper • 2502.11896 • Published Feb 17
The N+ Implementation Details of RLHF with PPO: A Case Study on TL;DR Summarization Paper • 2403.17031 • Published Mar 24, 2024 • 6
Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models Paper • 2410.18252 • Published Oct 23, 2024 • 7
TÜLU 3: Pushing Frontiers in Open Language Model Post-Training Paper • 2411.15124 • Published Nov 22, 2024 • 67
If You Can't Use Them, Recycle Them: Optimizing Merging at Scale Mitigates Performance Tradeoffs Paper • 2412.04144 • Published Dec 5, 2024 • 6
RLHF Can Speak Many Languages: Unlocking Multilingual Preference Optimization for LLMs Paper • 2407.02552 • Published Jul 2, 2024 • 4
Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning Paper • 2309.05444 • Published Sep 11, 2023 • 1
Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs Paper • 2402.14740 • Published Feb 22, 2024 • 15