NLP Field
Natural Language Processing (NLP) focuses on enabling computers to understand, interpret, and generate human language. Current research emphasizes improving model performance across diverse tasks, including question answering, text classification, and information extraction, often leveraging large language models (LLMs) and transformer architectures. These advancements are significantly impacting various fields, from healthcare (e.g., dementia detection, clinical data analysis) and legal (e.g., document processing, legal reasoning) to education and cybersecurity, by automating tasks and providing new analytical capabilities. A key challenge remains ensuring fairness, mitigating biases, and addressing privacy concerns within these powerful models.
Papers
IL-TUR: Benchmark for Indian Legal Text Understanding and Reasoning
Abhinav Joshi, Shounak Paul, Akshat Sharma, Pawan Goyal, Saptarshi Ghosh, Ashutosh Modi
Advancing Prompt Recovery in NLP: A Deep Dive into the Integration of Gemma-2b-it and Phi2 Models
Jianlong Chen, Wei Xu, Zhicheng Ding, Jinxin Xu, Hao Yan, Xinyu Zhang
Using LLMs to Aid Annotation and Collection of Clinically-Enriched Data in Bipolar Disorder and Schizophrenia
Ankit Aich, Avery Quynh, Pamela Osseyi, Amy Pinkham, Philip Harvey, Brenda Curtis, Colin Depp, Natalie Parde
From Insights to Actions: The Impact of Interpretability and Analysis Research on NLP
Marius Mosbach, Vagrant Gautam, Tomás Vergara-Browne, Dietrich Klakow, Mor Geva