Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research
School of Computing, The University of Georgia（佐治亚大学计算机学院）；Department of Mathematical and Statistical Sciences, University of Alberta（阿尔伯塔大学数学与统计科学系）；University of California, Los Angeles（加州大学洛杉矶分校）；Department of Radiology, Massachusetts General Hospital and Harvard Medical School（麻省总医院放射科和哈佛医学院）
Low-resource languages serve as invaluable repositories of human history, embodying cultural evolution and intellectual diversity. Despite their significance, these languages face critical challenges, including data scarcity and technological limitations, which hinder their comprehensive study and preservation. Recent advancements in large language models (LLMs) offer transformative opportunities for addressing these challenges, enabling innovative methodologies in linguistic, historical, and cultural research. This study systematically evaluates the applications of LLMs in low-resource language research, encompassing linguistic variation, historical documentation, cultural expressions, and literary analysis. By analyzing technical frameworks, current methodologies, and ethical considerations, this paper identifies key challenges such as data accessibility, model adaptability, and cultural sensitivity. Given the cultural, historical, and linguistic richness inherent in low-resource languages, this work emphasizes interdisciplinary collaboration and the development of customized models as promising avenues for advancing research in this domain. By underscoring the potential of integrating artificial intelligence with the humanities to preserve and study humanity's linguistic and cultural heritage, this study fosters global efforts towards safeguarding intellectual diversity.
Bridging Technology and Humanities: Evaluating the Impact of Large Language Models on Social Sciences Research with DeepSeek-R1
School of Physics and Information Technology, Shaanxi Normal University（陕西师范大学物理与信息技术学院）；School of Foreign Languages, Northwest University（西北大学外国语学院）；School of Computing, University of Georgia（佐治亚大学计算学院）
Can LLMs Augment Low-Resource Reading Comprehension Datasets? Opportunities and Challenges
University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Carnegie Mellon University（卡内基梅隆大学）；Georgia Institute of Technology（佐治亚理工学院）；Stanford University（斯坦福大学）；Amazon AI（亚马逊人工智能）
Do LLM hallucination detectors suffer from low-resource effect?
Indian Institute of Technology Kharagpur（印度理工学院卡拉格普尔分校）；Ruhr University Bochum（波鸿鲁尔大学）；UAR Research Center for Trustworthy Data Science and Security（UAR可信数据科学与安全研究中心）
Ground Truth Generation for Multilingual Historical NLP using LLMs
ARTFL Project, Romance Languages and Literatures, University of Chicago（ARTFL项目， Romance语言与文学系，芝加哥大学）；Department of History, University of Chicago（历史系，芝加哥大学）；Libraries and School of Information Studies, Purdue University（图书馆与信息科学学院，普渡大学）
Cultural Biases of Large Language Models and Humans in Historical Interpretation
Research & Development Department of Information Security and Communication Technology（信息安全和通信技术研发部）；Maggioli SpA（Maggioli股份公司）；Norwegian University of Science and Technology - NTNU（挪威科技大学）
A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities
State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences（多模态人工智能系统国家重点实验室，自动化研究所，中国科学院）
Academic Vibe Coding: Opportunities for Accelerating Research in an Era of Resource Constraint
Massachusetts Eye & Ear（麻省眼耳医院）；Harvard Medical School（哈佛医学院）；Beth Israel Deaconess Medical Center（贝斯以色列女执事医疗中心）；Massachusetts Institute of Technology（麻省理工学院）；Harvard T.H. Chan School of Public Health（哈佛大学陈曾熙公共卫生学院）
From ChatGPT, DALL-E 3 to Sora: How has Generative AI Changed Digital Humanities Research and Services?
Data Intelligence and Cross-Innovation Laboratory, Nanjing University（南京大学数据智能与交叉创新实验室）；School of Information Management, Nanjing University（南京大学信息管理学院）；School of Health Economics and Management, Nanjing University of Chinese Medicine（南京中医药大学卫生经济管理学院）
Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges
LMU Munich & Munich Center for Machine Learning（慕尼黑大学及慕尼黑机器学习中心）；University of Cologne（科隆大学）；University of Augsburg（奥格斯堡大学）；Bosch Center for Artificial Intelligence（博世人工智能中心）；Columbia University（哥伦比亚大学）；University of Maryland, College Park（马里兰大学学院市分校）
Towards Privacy-aware Mental Health AI Models: Advances, Challenges, and Opportunities
Ubiquitous Knowledge Processing Lab (UKP Lab) Department of Computer Science and Hessian Center for AI (hessian.AI) Technische Universität Darmstadt National Research Center for Applied Cybersecurity ATHENE, Germany（技术大学达姆施塔特应用网络安全国家研究中心、海森国家人工智能中心（hessian.AI）、计算机科学系、无处不在知识处理实验室（UKP Lab））；Department of Electrical Engineering, Indian Institute of Technology Delhi, India（印度德里印度理工学院电气工程系）；Yardi School of Artificial Intelligence, Indian Institute of Technology Delhi, India（印度德里印度理工学院人工智能学院）
Georgetown University（乔治敦大学）；Catholic University of America（美国天主教大学）
Entity recognition provides semantic access to ancient materials in the Digital Humanities: itexposes people and places of interest in texts that cannot be read exhaustively, facilitates linkingresources and can provide a window into text contents, even for texts with no translations. Inthis paper we present entity recognition for Coptic, the language of Hellenistic era Egypt. Weevaluate NLP approaches to the task and lay out difficulties in applying them to a low-resource,morphologically complex language. We present solutions for named and non-named nested en-tity recognition and semi-automat…
Bahir Dar University（巴赫达尔大学）；Universität Hamburg（汉堡大学）；Wuhan University of Technology（武汉理工大学）；Instituto Politécnico Nacional（国立理工学院）；Wollo University（沃洛大学）；Saarland University（萨尔大学）
This survey delves into the current state of natural language processing (NLP) for four Ethiopian languages: Amharic, Afaan Oromo, Tigrinya, and Wolaytta. Through this paper, we identify key challenges and opportunities for NLP research in Ethiopia. Furthermore, we provide a centralized repository on GitHub that contains publicly available resources for various NLP tasks in these languages. This repository can be updated periodically with contributions from other researchers. Our objective is to identify research gaps and disseminate the information to NLP researchers interested in Ethiopian l…
SinhalaMMLU: A Comprehensive Benchmark for Evaluating Multitask Language Understanding in Sinhala
Nara Institute of Science and Technology (NAIST)（奈良科学技术研究所）；University of Colombo School of Computing (UCSC)（科伦坡大学计算学院）；Informatics Institute of Technology (IIT)（信息技术研究所）
The National Library of Finland has digitized the historical newspapers published in Finland between 1771 and 1910. This collection contains approximately 1.95 million pages in Finnish and Swedish. Finnish part of the collection consists of about 2.40 billion words. The National Library's Digital Collections are offered via the digi.kansalliskirjasto.fi web service, also known as Digi. Part of the newspaper material (from 1771 to 1874) is also available freely downloadable in The Language Bank of Finland provided by the FINCLARIN consortium. The collection can also be accessed through the Korp…
Artificial Intelligence for Public Health Surveillance in Africa: Applications and Opportunities
Université de Sherbrooke（谢布鲁克大学）；University of Kinshasa（金沙萨大学）；University of Mbuji Mayi（姆布吉马伊大学）；Université Pédagogique Nationale（国家教育大学）；Institut Supérieur Pédagogique de Kikwit（基奎特高等教育学院）；Université Paris-Saclay（巴黎萨克雷大学）；University of Ottawa（渥太华大学）；SyntheseAI Inc.（SyntheseAI公司）；Karlstad University（卡尔斯塔德大学）；Hospital Monkole（蒙科勒医院）；University of Florida（佛罗里达大学）
