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cs.CL2026

Encoded but Not Routed: Explaining the Table-Chart Gap in Scientific Claim Verification

Sunisth Kumar, Xanh Ho, Tim Schopf +3

Multimodal LLMs are increasingly used to assist scientific peer review, where a core requirement is verifying whether claims in a paper are supported by its evidence. Prior work ha…

cs.CL20262 cited

SciClaimEval: Cross-modal Claim Verification in Scientific Papers

Xanh Ho, Yun-Ang Wu, Sunisth Kumar +4

We present SciClaimEval, a new scientific dataset for the claim verification task. Unlike existing resources, SciClaimEval features authentic claims, including refuted ones, direct…

cs.CL2026

Overview of PAN 2026: Voight-Kampff Generative AI Detection, Text Watermarking, Multi-Author Writing Style Analysis, Generative Plagiarism Detection, and Reasoning Trajectory Detection

Janek Bevendorff, Maik Fröbe, André Greiner-Petter +9

The goal of the PAN workshop is to advance computational stylometry and text forensics via objective and reproducible evaluation. In 2026, we run the following five tasks: (1) Voig…

cs.CL2025

Overview of the Plagiarism Detection Task at PAN 2025

André Greiner-Petter, Maik Fröbe, Jan Philip Wahle +4

The generative plagiarism detection task at PAN 2025 aims at identifying automatically generated textual plagiarism in scientific articles and aligning them with their respective s…

cs.CL2025

The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias Detection

Tomas Horych, Christoph Mandl, Terry Ruas +4

High annotation costs from hiring or crowdsourcing complicate the creation of large, high-quality datasets needed for training reliable text classifiers. Recent research suggests u…

cs.CL2024

SKT5SciSumm -- Revisiting Extractive-Generative Approach for Multi-Document Scientific Summarization

Huy Quoc To, Ming Liu, Guangyan Huang +4

Summarization for scientific text has shown significant benefits both for the research community and human society. Given the fact that the nature of scientific text is distinctive…