ICML

Roll the dice & look before you leap: Going beyond the creative limits of next-token prediction

Vaishnavh Nagarajan, Chen Henry Wu, Charles Ding, Aditi Raghunathan

机构 * Google Research, US（谷歌研究） ； Carnegie Mellon University, Pittsburgh, US（卡内基梅隆大学） 纠错

Comments ICML 2025 (oral)

Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity, and Convergence

Yinbin Han, Meisam Razaviyayn, Renyuan Xu

Comments 31 pages; first version: Dec 2024; this version: Aug 2025

Journal ref Forty-Second International Conference on Machine Learning 2025

Revisiting Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model

Kaito Ariu, Alexandre Proutiere, Se-Young Yun

Comments Accepted for presentation at the Forty-Second International Conference on Machine Learning (ICML 2025)