Research Seminar

Our research seminar takes place on Wednesdays at 10:00 am, usually in hybrid mode (online and on site in GU13), but not every week. It consists of presentations by invited researchers, presentations by researchers from our group and students presenting their Bachelor and Master theses. If you are interested in being invited to these presentations, please send an e-mail to roman.klinger(at)uni-bamberg.de or register on the IAM portal for the mailing list bamnlp-research-seminar.nlproc. This applies to students from the various degree programs at the University of Bamberg as well as to researchers from the WIAI and other faculties. We expect students who are writing their final thesis at our chair to participate in lectures by other students and external guests.

 

Winter Term 2024/2025

DateNameTitleType
2024-10-30Aswathy VelutharambathHow entangled is factuality and deception in GermanInternal
2024-11-06Ulrich Heid (University of Hildesheim)NLP applications and development in interdisciplinary projects: an overview of research at University of HildesheimInvited Talk
2024-12-04Jiahui Li
Nadine Probol
Interactive Prompt Optimization with Human in the Loop
Autism Markers in Spoken Language
Internal
2024–12–18Aidan CombsThe Vibe Shifts of the U.S. Presidential Race: Measuring the Affective Cultural Meaning of Actors at the Sentence LevelInternal
2025–01–08Esra Dönmez (IMS, Uni Stuttgart)How well do LLMs capture the dynamics of persuasion?Invited Talk
2025–01–29Diego Frassinelli (MaiNLP, LMU München) Invited Talk
2025–02–12Michael Franke (Uni Tübingen)Pragmatic reasoning about indirect answers to polar questions: humans, probabilistic pragmatics, and LMs.Invited Talk

Summer Term 2024

DateNameTitleType
2024–04–15Christopher Bagdon“You are an expert annotator”: Automatic Best–Worst-Scaling Annotations for Emotion Intensity ModelingInternal
2024–06–05Christopher Bagdon
Lynn Greschner
User’s Choice of Images and Text to Express Emotions in Twitter and Reddit
The Interplay of Emotions and Convincingness in Argument Mining for NLP
Internal