GUARD: Glocal Uncertainty-Aware Robust Decoding for Effective and Efficient Open-Ended Text Generation
机构 * Henan University(河南大学) ; Department of Statistics, LMU Munich(慕尼黑大学统计系) ; Munich Center for Machine Learning (MCML)(慕尼黑机器学习中心) ; CISPA Helmholtz Center for Information Security, Saarbrücken(萨尔布吕肯亥姆霍尔兹信息安全中心) ; University of California, San Diego(加州大学圣地亚哥分校)
Comments Accepted at Findings of the Association for Computational Linguistics: EMNLP 2025