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
A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions
Bowen Qin, Binyuan Hui, Lihan Wang, Min Yang, Jinyang Li, Binhua Li, Ruiying Geng, Rongyu Cao, Jian Sun, Luo Si, Fei Huang, Yongbin Li
NL2GDPR: Automatically Develop GDPR Compliant Android Application Features from Natural Language
Faysal Hossain Shezan, Yingjie Lao, Minlong Peng, Xin Wang, Mingming Sun, Ping Li
Human-guided Collaborative Problem Solving: A Natural Language based Framework
Harsha Kokel, Mayukh Das, Rakibul Islam, Julia Bonn, Jon Cai, Soham Dan, Anjali Narayan-Chen, Prashant Jayannavar, Janardhan Rao Doppa, Julia Hockenmaier, Sriraam Natarajan, Martha Palmer, Dan Roth
Benchmarking Transformers-based models on French Spoken Language Understanding tasks
Oralie Cattan, Sahar Ghannay, Christophe Servan, Sophie Rosset
Explaining Chest X-ray Pathologies in Natural Language
Maxime Kayser, Cornelius Emde, Oana-Maria Camburu, Guy Parsons, Bartlomiej Papiez, Thomas Lukasiewicz
Towards Highly Expressive Machine Learning Models of Non-Melanoma Skin Cancer
Simon M. Thomas, James G. Lefevre, Glenn Baxter, Nicholas A. Hamilton