arXiv:2608.27782v1 Announce Type: cross
Abstract: Memorization in large language models is measured through a zoo of definitions whose formal relations are unknown, and differential privacy (DP) is t...
By Xujun Che, Depeng Xu, Shuhan Yuan
arXiv:2607. 03436v1 Announce Type: new Abstract: Routing among large language models (LLMs) promises better quality at lower cost, motivated by the reported gap between learned routers and a per-instance oracle.
By Teng-Ruei Chen
arXiv:2609.37841v1 Announce Type: new
Abstract: Masked generative models offer parallel token prediction, but accurate parallel sampling must account for dependencies among tokens. When dependencies...
By Ryotaro Kawata, Satoshi Hayakawa, Taiji Suzuki
arXiv:2609.10196v1 Announce Type: cross
Abstract: Attias, Hanneke and Ramaswami (NeurIPS 2025) asked whether randomization provably reduces the oracle calls needed for online learning when the class...
By Xuan Li
arXiv:2606. 25170v1 Announce Type: cross Abstract: We study PAC learning in tabular discounted Markov decision processes with exogenous i.
By Corentin Pla, Hugo Richard, Marc Abeille, Vianney Perchet
arXiv:2608. 06762v1 Announce Type: new Abstract: Bisimulation metrics quantify behavioral similarity in Markov decision processes, but their Wasserstein fixed-point operator updates every state pair and incurs quadratic pairwise work.
By Ibne Farabi Shihab, Joyanta Jyoti Mondal