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cs.LG2024
The Importance of Online Data: Understanding Preference Fine-tuning via Coverage
Yuda Song, Gokul Swamy, Aarti Singh +2
Learning from human preference data has emerged as the dominant paradigm for fine-tuning large language models (LLMs). The two most common families of techniques -- online reinforc…
cs.LG2023
Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees
Yifei Zhou, Ayush Sekhari, Yuda Song +1
Hybrid RL is the setting where an RL agent has access to both offline data and online data by interacting with the real-world environment. In this work, we propose a new hybrid RL…