Episode 51
Arash Ahmadian on Rethinking RLHF
TalkRL: The Reinforcement Learning Podcast
March 25, 202433m 30s
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Show Notes
Arash Ahmadian is a Researcher at Cohere and Cohere For AI focussed on Preference Training of large language models. He’s also a researcher at the Vector Institute of AI.
Featured Reference
Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs
Arash Ahmadian, Chris Cremer, Matthias Gallé, Marzieh Fadaee, Julia Kreutzer, Olivier Pietquin, Ahmet Üstün, Sara Hooker
Additional References
- Self-Rewarding Language Models, Yuan et al 2024
- Reinforcement Learning: An Introduction, Sutton and Barto 1992
- Learning from Delayed Rewards, Chris Watkins 1989
- Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning, Williams 1992
Topics
Reinforcement LearningMachine LearningArtificial Intelligence