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
Overcoming Referential Ambiguity in Language-Guided Goal-Conditioned Reinforcement Learning
Hugo Caselles-Dupré, Olivier Sigaud, Mohamed Chetouani
Knowledge Representation for Conceptual, Motivational, and Affective Processes in Natural Language Communication
Seng-Beng Ho, Zhaoxia Wang, Boon-Kiat Quek, Erik Cambria
Factual and Informative Review Generation for Explainable Recommendation
Zhouhang Xie, Sameer Singh, Julian McAuley, Bodhisattwa Prasad Majumder
A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural Language
Bing Su, Dazhao Du, Zhao Yang, Yujie Zhou, Jiangmeng Li, Anyi Rao, Hao Sun, Zhiwu Lu, Ji-Rong Wen