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
Large Models of What? Mistaking Engineering Achievements for Human Linguistic Agency
Abeba Birhane, Marek McGann
Investigating LLMs as Voting Assistants via Contextual Augmentation: A Case Study on the European Parliament Elections 2024
Ilias Chalkidis
Natural language is not enough: Benchmarking multi-modal generative AI for Verilog generation
Kaiyan Chang, Zhirong Chen, Yunhao Zhou, Wenlong Zhu, kun wang, Haobo Xu, Cangyuan Li, Mengdi Wang, Shengwen Liang, Huawei Li, Yinhe Han, Ying Wang
Automated Question Generation on Tabular Data for Conversational Data Exploration
Ritwik Chaudhuri, Rajmohan C, Kirushikesh DB, Arvind Agarwal
ESM+: Modern Insights into Perspective on Text-to-SQL Evaluation in the Age of Large Language Models
Benjamin G. Ascoli, Yasoda Sai Ram Kandikonda, Jinho D. Choi