EMNLP

Watermark under Fire: A Robustness Evaluation of LLM Watermarking

Jiacheng Liang, Zian Wang, Lauren Hong, Shouling Ji, Ting Wang

Comments 25 pages. Accepted by The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025)

Preemptive Detection and Correction of Misaligned Actions in LLM Agents

Haishuo Fang, Xiaodan Zhu, Iryna Gurevych

机构 * Ubiquitous Knowledge Processing Lab, Department of Computer Science, TU Darmstadt（图宾根大学计算机科学系） ； National Research Center for Applied Cybersecurity ATHENE, Germany（德国应用网络安全国家研究中心ATHENE） ； Department of Electrical and Computer Engineering & Ingenuity Labs Research Institute, Queen’s University, Canada（加拿大女王大学电气与计算机工程系及创新实验室研究院） 纠错

Comments Accepted by EMNLP 2025

Hardware-Aware Parallel Prompt Decoding for Memory-Efficient Acceleration of LLM Inference

Hao Mark Chen, Wayne Luk, Ka Fai Cedric Yiu, Rui Li, Konstantin Mishchenko, Stylianos I. Venieris, Hongxiang Fan

机构 * Imperial College London, UK（伦敦帝国学院） ； Hong Kong Polytechnic University, Hong Kong（香港理工大学） ； Samsung AI Center, Cambridge, UK（三星人工智能中心） 纠错

Comments Accepted at EMNLP 2025. The code for this implementation is available at https://github.com/hmarkc/parallel-prompt-decoding

Multi-level Diagnosis and Evaluation for Robust Tabular Feature Engineering with Large Language Models

Yebin Lim, Susik Yoon

机构 * Computer Science and Engineering Korea University（计算机科学与工程韩国大学） 纠错

Comments Accepted to Findings of EMNLP 2025