Natural Language
Natural language processing (NLP) focuses on enabling computers to understand, interpret, and generate human language. Current research heavily utilizes large language models (LLMs), such as BERT and others, to tackle diverse tasks including text-to-SQL translation, semantic analysis of images, and even controlling robots via natural language commands. The field's impact spans various sectors, from improving search engines and e-commerce platforms to advancing healthcare diagnostics and facilitating more efficient scientific research through automated literature analysis and data extraction.
Papers
Text2Loc: 3D Point Cloud Localization from Natural Language
Yan Xia, Letian Shi, Zifeng Ding, João F. Henriques, Daniel Cremers
YUAN 2.0: A Large Language Model with Localized Filtering-based Attention
Shaohua Wu, Xudong Zhao, Shenling Wang, Jiangang Luo, Lingjun Li, Xi Chen, Bing Zhao, Wei Wang, Tong Yu, Rongguo Zhang, Jiahua Zhang, Chao Wang
A Material Lens on Coloniality in NLP
William Held, Camille Harris, Michael Best, Diyi Yang
How Well Do Large Language Models Understand Syntax? An Evaluation by Asking Natural Language Questions
Houquan Zhou, Yang Hou, Zhenghua Li, Xuebin Wang, Zhefeng Wang, Xinyu Duan, Min Zhang
Human-Centric Autonomous Systems With LLMs for User Command Reasoning
Yi Yang, Qingwen Zhang, Ci Li, Daniel Simões Marta, Nazre Batool, John Folkesson
Spot: A Natural Language Interface for Geospatial Searches in OSM
Lynn Khellaf, Ipek Baris Schlicht, Julia Bayer, Ruben Bouwmeester, Tilman Miraß, Tilman Wagner