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
Code Pretraining Improves Entity Tracking Abilities of Language Models
Najoung Kim, Sebastian Schuster, Shubham Toshniwal
Enhancing Vision Models for Text-Heavy Content Understanding and Interaction
Adithya TG, Adithya SK, Abhinav R Bharadwaj, Abhiram HA, Dr. Surabhi Narayan
Robust Planning with LLM-Modulo Framework: Case Study in Travel Planning
Atharva Gundawar, Mudit Verma, Lin Guan, Karthik Valmeekam, Siddhant Bhambri, Subbarao Kambhampati
UniBias: Unveiling and Mitigating LLM Bias through Internal Attention and FFN Manipulation
Hanzhang Zhou, Zijian Feng, Zixiao Zhu, Junlang Qian, Kezhi Mao
Automatic detection of cognitive impairment in elderly people using an entertainment chatbot with Natural Language Processing capabilities
Francisco de Arriba-Pérez, Silvia García-Méndez, Francisco J. González-Castaño, Enrique Costa-Montenegro
VeLoRA: Memory Efficient Training using Rank-1 Sub-Token Projections
Roy Miles, Pradyumna Reddy, Ismail Elezi, Jiankang Deng
A FAIR and Free Prompt-based Research Assistant
Mahsa Shamsabadi, Jennifer D'Souza
Exploring the use of a Large Language Model for data extraction in systematic reviews: a rapid feasibility study
Lena Schmidt, Kaitlyn Hair, Sergio Graziozi, Fiona Campbell, Claudia Kapp, Alireza Khanteymoori, Dawn Craig, Mark Engelbert, James Thomas