3 papers
cs.LG2026
Embracing Biased Transition Matrices for Complementary-Label Learning with Many Classes
Tan-Ha Mai, Chao-Kai Chiang, Han-Hwa Shih +3
Complementary-label learning (CLL) is a weakly supervised paradigm where instances are labeled with classes they do not belong to. Despite a decade of research, CLL methods remain…
cs.LG2025
LLM Routing with Dueling Feedback
Chao-Kai Chiang, Takashi Ishida, Masashi Sugiyama
We study LLM routing, the problem of selecting the best model for each query while balancing user satisfaction, model expertise, and inference cost. We formulate routing as context…
cs.LG2025
Domain Adaptation and Entanglement: an Optimal Transport Perspective
Okan Koç, Alexander Soen, Chao-Kai Chiang +1
Current machine learning systems are brittle in the face of distribution shifts (DS), where the target distribution that the system is tested on differs from the source distributio…