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
Universal Domain Adaptation for Robust Handling of Distributional Shifts in NLP
Hyuhng Joon Kim, Hyunsoo Cho, Sang-Woo Lee, Junyeob Kim, Choonghyun Park, Sang-goo Lee, Kang Min Yoo, Taeuk Kim
ALCUNA: Large Language Models Meet New Knowledge
Xunjian Yin, Baizhou Huang, Xiaojun Wan
SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research
Dimosthenis Antypas, Asahi Ushio, Francesco Barbieri, Leonardo Neves, Kiamehr Rezaee, Luis Espinosa-Anke, Jiaxin Pei, Jose Camacho-Collados