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20232026
most citedScImage: How Good Are Multimodal Large Language Models at Scientific Text-to-Image Generation?

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cs.CL2026

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…

cs.CL2026

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024

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…