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
Leveraging Natural Language and Item Response Theory Models for ESG Scoring
César Pedrosa Soares
Language-driven Grasp Detection with Mask-guided Attention
Tuan Van Vo, Minh Nhat Vu, Baoru Huang, An Vuong, Ngan Le, Thieu Vo, Anh Nguyen
Prometheus Chatbot: Knowledge Graph Collaborative Large Language Model for Computer Components Recommendation
Yunsheng Wang, Songhao Chen, Kevin Jin
LLMs' Understanding of Natural Language Revealed
Walid S. Saba
A Benchmark Dataset for Multimodal Prediction of Enzymatic Function Coupling DNA Sequences and Natural Language
Yuchen Zhang, Ratish Kumar Chandrakant Jha, Soumya Bharadwaj, Vatsal Sanjaykumar Thakkar, Adrienne Hoarfrost, Jin Sun
Towards Automated Data Sciences with Natural Language and SageCopilot: Practices and Lessons Learned
Yuan Liao, Jiang Bian, Yuhui Yun, Shuo Wang, Yubo Zhang, Jiaming Chu, Tao Wang, Kewei Li, Yuchen Li, Xuhong Li, Shilei Ji, Haoyi Xiong
Large Models of What? Mistaking Engineering Achievements for Human Linguistic Agency
Abeba Birhane, Marek McGann
Investigating LLMs as Voting Assistants via Contextual Augmentation: A Case Study on the European Parliament Elections 2024
Ilias Chalkidis
Natural language is not enough: Benchmarking multi-modal generative AI for Verilog generation
Kaiyan Chang, Zhirong Chen, Yunhao Zhou, Wenlong Zhu, kun wang, Haobo Xu, Cangyuan Li, Mengdi Wang, Shengwen Liang, Huawei Li, Yinhe Han, Ying Wang