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
Fine Tuning with Abnormal Examples
Will Rieger
Multimodal Grounding for Embodied AI via Augmented Reality Headsets for Natural Language Driven Task Planning
Selma Wanna, Fabian Parra, Robert Valner, Karl Kruusamäe, Mitch Pryor
Exploring the Curious Case of Code Prompts
Li Zhang, Liam Dugan, Hainiu Xu, Chris Callison-Burch
Using Large Language Models for (De-)Formalization and Natural Argumentation Exercises for Beginner's Students
Merlin Carl
ReDWINE: A Clinical Datamart with Text Analytical Capabilities to Facilitate Rehabilitation Research
David Oniani, Bambang Parmanto, Andi Saptono, Allyn Bove, Janet Freburger, Shyam Visweswaran Nickie Cappella, Brian McLay, Jonathan C. Silverstein, Michael J. Becich, Anthony Delitto, Elizabeth Skidmore, Yanshan Wang
WildRefer: 3D Object Localization in Large-scale Dynamic Scenes with Multi-modal Visual Data and Natural Language
Zhenxiang Lin, Xidong Peng, Peishan Cong, Yuenan Hou, Xinge Zhu, Sibei Yang, Yuexin Ma