3 papers
cs.IT2026
Minimax bounds for watermarked and masked recursive discrete distribution estimation
Millen Kanabar, Michael Gastpar
Watermarking has been proposed as a way to identify synthetic samples in estimation settings where no metadata is available to distinguish them from real samples, but its precise e…
cs.AI2026
Joint Consistency: A Unified Test-Time Aggregation Framework via Energy Minimization
Yunzhen Yao, Hongye Wang, Yahong Wang +3
This paper studies test-time aggregation, an approach that generates multiple reasoning traces and aggregates them into a final answer. Most existing methods rely on evaluation sig…
cs.LG2026
Block-Sample MAC-Bayes Generalization Bounds
Matthias Frey, Jingge Zhu, Michael C. Gastpar
We present a family of novel block-sample MAC-Bayes bounds (mean approximately correct). While PAC-Bayes bounds (probably approximately correct) typically give bounds for the gener…