Language and AI Colloquium: Insights, Findings, and Recommendations to Paraphrasing and Plagiarism in the Age of LLMs

This is the first of a new series of initiatives related to the Language and AI theme of the Jantina Tammes School.
Speaker: Jan Philip Wahle - University of Gottingen
Title: Insights, Findings, and Recommendations to Paraphrasing and Plagiarism in the Age of LLMs

Abstract:

Natural Language Processing (NLP) stands at a critical juncture as it is poised to substantially influence the world. Yet, with this potential comes the imperative to navigate ethical, technical, and scholarly challenges accompanying these advancements. This talk goes into how recent innovations in NLP can be used and misused (to perform paraphrase plagiarism). We take a deep dive into paraphrases and what has changed since large language models (LLMs) can generate texts almost indistinguishable from human writing. We present a narrative on the evolving dynamics between NLP technologies and their broader societal implications. The discourse extends to broader questions of the current path the NLP community is paving and its sustainability. Through additional perspectives about the main actors within NLP research, cross-field trends, and the shifting paradigms of knowledge exchange, the talk aims to encourage our self-evaluation through which NLP can foster more inclusive and responsible progress. Finally, the talk invites you to a dialogue on the future of NLP.

Bio:

Jan Philip Wahle is a third-year Ph.D. candidate in computer science at the University of Göttingen in Germany under the guidance of Prof. Gipp and Dr. Ruas. He received his Master’s degree in computer science from the University of Wuppertal and worked for two years for the automotive company Aptiv PLC before continuing with his Ph.D. studies. During his Ph.D., Jan has been a visiting researcher at the National Research Council Canada and the University of Toronto. His research has been presented at ACL, EMNLP, EACL, and LREC (among others). One of his primary interests is to understand how NLP research can be performed sustainably and responsibly. His research is most concerned with how we influence the broader exchange of ideas, who the main actors of our field are, and how we can improve academic integrity through automated methods. Specific to academic integrity, he has been researching paraphrasing and plagiarism detection from human and machine-generated text. Updates about his research can be found on his website.