23 citations · 48 across the 17 of their papers we have counts for
6 papers · 1 filter
VisExMEM: Visual Evidence-Based Explainable Multimodal Evaluation Metric
Subhadeep Roy, Christoph Leiter, Steffen Eger
Current image-text evaluation often relies on a global score, which gives limited insight into which semantic details are supported by the image. Explainable metrics provide ration…
When Writing Style Drifts: Benchmarking Authorship Verification under Distribution Shifts in Genre, Time and the AI-Era
Lotta Kiefer, Brisca Balthes, Christoph Leiter +3
Authorship verification (AV) assumes that an author's writing style remains sufficiently stable to distinguish it from that of other writers. In practice, however, this assumption…
Who Annotates in NLP? A Large-scale Assessment of Human Annotation Reporting between 2018 and 2025
Maria Kunilovskaya, Gagan Bhatia, Lisa Sophie Albertelli +10
Human annotation is the empirical foundation of much NLP research, from dataset construction to model evaluation, but papers often leave unclear who produced the annotations and ho…
ValueGround: Evaluating Culture-Conditioned Visual Value Grounding in MLLMs
Zhipin Wang, Christoph Leiter, Christian Frey +3
Cultural values are expressed not only through language but also through visual scenes and everyday social practices. Yet existing evaluations of cultural values in language models…
ExCAM: Explainable Cultural Awareness Metrics
Christoph Leiter, Haiyue Song, Hour Kaing +4
Evaluating the cultural awareness of large language models is crucial to ensure the fairness of generated text and the generalizability of applications across the world. Recent ben…
GerAV: Towards New Heights in German Authorship Verification using Fine-Tuned LLMs on a New Benchmark
Lotta Kiefer, Christoph Leiter, Sotaro Takeshita +2
Authorship verification (AV) is the task of determining whether two texts were written by the same author and has been studied extensively, predominantly for English data. In contr…