ACL

MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models

Zhongzhan Huang, Guoming Ling, Shanshan Zhong, Hefeng Wu, Liang Lin

机构 * Sun Yat-sen University（中山大学） ； Peng Cheng Laboratory（鹏城实验室） ； Guangdong Key Laboratory of Big Data Analysis and Processing（广东省大数据分析与处理重点实验室） 纠错

Comments Accepted by ACL'25 main track

Past Meets Present: Creating Historical Analogy with Large Language Models

Nianqi Li, Siyu Yuan, Jiangjie Chen, Jiaqing Liang, Feng Wei, Zujie Liang, Deqing Yang, Yanghua Xiao

Comments Accepted to ACL 2025 (Outstanding Paper Award)

Towards the Law of Capacity Gap in Distilling Language Models

Chen Zhang, Qiuchi Li, Dawei Song, Zheyu Ye, Yan Gao, Yan Hu

机构 * Beijing Institute of Technology（北京理工大学） ； University of Copenhagen（哥本哈根大学） ； The Open University（开放大学） ； Xiaohongshu（小红书） 纠错

Comments 32 pages, 10 figures, 15 tables, accepted to ACL 2025. Code and checkpoints are available at https://github.com/GeneZC/MiniMA

Basic Reading Distillation

Zhi Zhou, Sirui Miao, Xiangyu Duan, Hao Yang, Min Zhang

机构 * School of Computer Science and Technology, Soochow University（苏州大学计算机科学与技术学院） ； Huawei Translation Services Center（华为翻译服务中心） 纠错

Comments Accepted by ACL2025