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
Towards a Probabilistic Framework for Analyzing and Improving LLM-Enabled Software
Juan Manuel Baldonado, Flavia Bonomo-Braberman, Víctor Adrián Braberman
Dafny as Verification-Aware Intermediate Language for Code Generation
Yue Chen Li, Stefan Zetzsche, Siva Somayyajula
Iconicity in Large Language Models
Anna Marklová, Jiří Milička, Leonid Ryvkin, Ľudmila Lacková Bennet, Libuše Kormaníková
AGGA: A Dataset of Academic Guidelines for Generative AI and Large Language Models
Junfeng Jiao, Saleh Afroogh, Kevin Chen, David Atkinson, Amit Dhurandhar
Applications of natural language processing in aviation safety: A review and qualitative analysis
Aziida Nanyonga, Keith Joiner, Ugur Turhan, Graham Wild