Steven Wu
@zstevenwu.bsky.social
Computer science professor at Carnegie Mellon. Researcher in machine learning. Algorithmic foundations of responsible AI (e.g., privacy, uncertainty quantification), interactive learning (e.g., RLHF).
https://zstevenwu.com/
https://zstevenwu.com/
can you present other people's results :-)
March 4, 2025 at 2:18 PM
can you present other people's results :-)
that makes sense to me.... i should go to bed....
February 6, 2025 at 12:51 AM
that makes sense to me.... i should go to bed....
Reposted by Steven Wu
@gswamy.bsky.social et al propose SPO which builds a game from a preferences, solving for the minimax winner. Handles non-Markovian, intransitive, and stochastic preferences. Nice empirical eval ranging from small demonstrative domains to huge RL domain (Mujoco).
arxiv.org/abs/2401.04056
2/3.
arxiv.org/abs/2401.04056
2/3.
A Minimaximalist Approach to Reinforcement Learning from Human Feedback
We present Self-Play Preference Optimization (SPO), an algorithm for reinforcement learning from human feedback. Our approach is minimalist in that it does not require training a reward model nor unst...
arxiv.org
November 21, 2024 at 12:30 PM
@gswamy.bsky.social et al propose SPO which builds a game from a preferences, solving for the minimax winner. Handles non-Markovian, intransitive, and stochastic preferences. Nice empirical eval ranging from small demonstrative domains to huge RL domain (Mujoco).
arxiv.org/abs/2401.04056
2/3.
arxiv.org/abs/2401.04056
2/3.