April 18, 2024, 4:47 a.m. | Stefanie Urchs, Veronika Thurner, Matthias A{\ss}enmacher, Christian Heumann, Stephanie Thiemichen

cs.CL updates on arXiv.org arxiv.org

arXiv:2310.03031v2 Announce Type: replace
Abstract: With the introduction of ChatGPT, OpenAI made large language models (LLM) accessible to users with limited IT expertise. However, users with no background in natural language processing (NLP) might lack a proper understanding of LLMs. Thus the awareness of their inherent limitations, and therefore will take the systems' output at face value. In this paper, we systematically analyse prompts and the generated responses to identify possible problematic issues with a special focus on gender biases, …

abstract arxiv bias chatgpt chatgpt responses cs.ai cs.cl cs.cy cs.lg english expertise gender gender bias german however introduction language language models language processing large language large language models llm llms natural natural language natural language processing nlp openai processing responses type understanding

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Data Scientist

@ Publicis Groupe | New York City, United States

Bigdata Cloud Developer - Spark - Assistant Manager

@ State Street | Hyderabad, India