Natural Language Processing
Natural Language Processing (NLP) focuses on enabling computers to understand, interpret, and generate human language. Current research heavily emphasizes large language models (LLMs), exploring their capabilities in various tasks like question answering, text classification, and translation, while also addressing challenges such as bias, efficiency, and the need for better evaluation metrics. The field's significance lies in its potential to revolutionize numerous applications, from improving healthcare and education to enhancing information access and facilitating more effective human-computer interaction.
Papers
SUPER: Evaluating Agents on Setting Up and Executing Tasks from Research Repositories
Ben Bogin, Kejuan Yang, Shashank Gupta, Kyle Richardson, Erin Bransom, Peter Clark, Ashish Sabharwal, Tushar Khot
Enhancing adversarial robustness in Natural Language Inference using explanations
Alexandros Koulakos, Maria Lymperaiou, Giorgos Filandrianos, Giorgos Stamou
Native vs Non-Native Language Prompting: A Comparative Analysis
Mohamed Bayan Kmainasi, Rakif Khan, Ali Ezzat Shahroor, Boushra Bendou, Maram Hasanain, Firoj Alam
Decomposition of surprisal: Unified computational model of ERP components in language processing
Jiaxuan Li, Richard Futrell
DA-MoE: Towards Dynamic Expert Allocation for Mixture-of-Experts Models
Maryam Akhavan Aghdam, Hongpeng Jin, Yanzhao Wu
NLP4PBM: A Systematic Review on Process Extraction using Natural Language Processing with Rule-based, Machine and Deep Learning Methods
William Van Woensel, Soroor Motie
Questioning Internal Knowledge Structure of Large Language Models Through the Lens of the Olympic Games
Juhwan Choi, YoungBin Kim
NLP-Powered Repository and Search Engine for Academic Papers: A Case Study on Cyber Risk Literature with CyLit
Linfeng Zhang, Changyue Hu, Zhiyu Quan
SubRegWeigh: Effective and Efficient Annotation Weighing with Subword Regularization
Kohei Tsuji, Tatsuya Hiraoka, Yuchang Cheng, Tomoya Iwakura
Towards Safe Multilingual Frontier AI
Artūrs Kanepajs, Vladimir Ivanov, Richard Moulange
Protein sequence classification using natural language processing techniques
Huma Perveen (1), Julie Weeds (2) ((1) School of Mathematical and Physical Sciences, University of Sussex, Brighton, UK, (2) School of Engineering and Informatics, University of Sussex, Brighton, UK)
Combining LLMs and Knowledge Graphs to Reduce Hallucinations in Question Answering
Larissa Pusch, Tim O. F. Conrad
Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers
Chenglei Si, Diyi Yang, Tatsunori Hashimoto