Citations are a key ingredient of scientific research to relate a paper to others published in the community. Recently, it has been noted that there is a citation age bias in the Natural Language Processing (NLP) community, one of the currently fastest growing AI subfields, in that the mean age of the bibliography of NLP papers has become ever younger in the last few years, leading to `citation amnesia' in which older knowledge is increasingly forgotten. In this work, we put such claims into perspective by analyzing the bibliography of $\sim$300k papers across 15 different scientific fields submitted to the popular preprint server Arxiv in the time period from 2013 to 2022. We find that all AI subfields (in particular: cs.AI, cs.CL, cs.CV, cs.LG) have similar trends of citation amnesia, in which the age of the bibliography has roughly halved in the last 10 years (from above 12 in 2013 to below 7 in 2022), on average. Rather than diagnosing this as a citation age bias in the NLP community, we believe this pattern is an artefact of the dynamics of these research fields, in which new knowledge is produced in ever shorter time intervals.
SECite: Analyzing and Summarizing Citations in Software Engineering Literature
Dept. of Computer Science SUNY Polytechnic Institute（计算机科学系圣尼古拉学院）；Dept. of Information Systems University of Maryland Baltimore County（信息系统系马里兰大学巴尔的摩县）
Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond
School of Computer Science and Technology, Xi’an Jiaotong University（西安交通大学计算机科学与技术学院）；Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering（陕西省大数据知识工程重点实验室）；National Engineering Lab for Big Data Analytics（国家大数据分析工程实验室）；School of Computer Science and Engineering, Nanyang Technological University（南洋理工大学计算机科学与工程学院）
What Do Visual Tokens Really Encode? Uncovering Sparsity and Redundancy in Multimodal Large Language Models
Institute of Digital Twin, Eastern Institute of Technology（数字孪生研究所，东部技术研究所）；Ningbo Key Laboratory of Spatial Intelligence and Digital Derivative（宁波空间智能与数字衍生关键实验室）；Shanghai Jiao Tong University（上海交通大学）；The Hong Kong Polytechnic University（香港理工大学）
One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support
University of Bern（伯尔尼大学）；University of Copenhagen（哥本哈根大学）；Bern University of Applied Sciences（伯尔尼应用科学大学）；University of Fribourg（弗里堡大学）；Stanford University（斯坦福大学）
Assessing the impact of Open Research Information Infrastructures using NLP driven full-text Scientometrics: A case study of the LXCat open-access platform
DA-IICT, Dhirubhai Ambani University（达吉巴伊·安巴尼大学）；Smart Energy Learning Center, DAU（达吉巴伊·安巴尼大学智能能源学习中心）
