EMNLP

Linear-Time Demonstration Selection for In-Context Learning via Gradient Estimation

Ziniu Zhang, Zhenshuo Zhang, Dongyue Li, Lu Wang, Jennifer Dy, Hongyang R. Zhang

机构 * Northeastern University（东北大学） ； University of Michigan（密歇根大学） 纠错

Comments 19 pages. EMNLP'25

Identifying Aspects in Peer Reviews

Sheng Lu, Ilia Kuznetsov, Iryna Gurevych

机构 * Ubiquitous Knowledge Processing Lab (UKP Lab)（通用知识处理实验室） ； Department of Computer Science（计算机科学系） ； Hessian Center for AI (hessian.AI)（黑森人工智能中心） 纠错

Comments EMNLP 2025 Findings

Beyond Contrastive Learning: Synthetic Data Enables List-wise Training with Multiple Levels of Relevance

Reza Esfandiarpoor, George Zerveas, Ruochen Zhang, Macton Mgonzo, Carsten Eickhoff, Stephen H. Bach

机构 * Brown University（布朗大学） ； Microsoft（微软） ； University of Tübingen（图宾根大学） 纠错

Comments Findings of the EMNLP 2025

IG-Pruning: Input-Guided Block Pruning for Large Language Models

Kangyu Qiao, Shaolei Zhang, Yang Feng

机构 * Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences (ICT/CAS)（智能信息处理重点实验室，计算技术研究所，中国科学院） ； Key Laboratory of AI Safety, Chinese Academy of Sciences（人工智能安全重点实验室，中国科学院） ； University of Chinese Academy of Sciences, Beijing, China（中国科学院大学，北京，中国） 纠错

Comments Accepted to EMNLP 2025. Code is available at https://github.com/ictnlp/IG-Pruning

Journal ref https://aclanthology.org/2025.emnlp-main.537/

Visual Program Distillation with Template-Based Augmentation

Michal Shlapentokh-Rothman, Yu-Xiong Wang, Derek Hoiem

机构 * University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校） 纠错

Comments EMNLP Camera Ready