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cs.LG2026
Spectral Souping: A Unified Framework for Online Preference Alignment
Yinlam Chow, Guy Tennenholtz, Ted Yun +4
Reinforcement Learning from Human Feedback (RLHF) effectively aligns Large Language Models (LLMs) with aggregate human preferences but often fails to address the diverse and confli…
cs.LG2026
Diffusion Controller: Framework, Algorithms and Parameterization
Tong Yang, Moonkyung Ryu, Chih-Wei Hsu +4
Controllable diffusion generation often relies on various heuristics that are seemingly disconnected without a unified understanding. We bridge this gap with Diffusion Controller (…
cs.LG2023
Ever Evolving Evaluator (EV3): Towards Flexible and Reliable Meta-Optimization for Knowledge Distillation
Li Ding, Masrour Zoghi, Guy Tennenholtz +1
We introduce EV3, a novel meta-optimization framework designed to efficiently train scalable machine learning models through an intuitive explore-assess-adapt protocol. In each ite…