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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…
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…
ContrastScore: Towards Higher Quality, Less Biased, More Efficient Evaluation Metrics with Contrastive Evaluation
Xiao Wang, Daniil Larionov, Siwei Wu +4
Evaluating the quality of generated text automatically remains a significant challenge. Conventional reference-based metrics have been shown to exhibit relatively weak correlation…
BatchGEMBA: Token-Efficient Machine Translation Evaluation with Batched Prompting and Prompt Compression
Daniil Larionov, Steffen Eger
Recent advancements in Large Language Model (LLM)-based Natural Language Generation evaluation have largely focused on single-example prompting, resulting in significant token over…
TikZero: Zero-Shot Text-Guided Graphics Program Synthesis
Jonas Belouadi, Eddy Ilg, Margret Keuper +5
Automatically synthesizing figures from text captions is a compelling capability. However, achieving high geometric precision and editability requires representing figures as graph…
PromptOptMe: Error-Aware Prompt Compression for LLM-based MT Evaluation Metrics
Daniil Larionov, Steffen Eger
Evaluating the quality of machine-generated natural language content is a challenging task in Natural Language Processing (NLP). Recently, large language models (LLMs) like GPT-4 h…