SciFigPlag-Bench: A Benchmark for Provenance-Aware Scientific Figure Plagiarism Detection
Scientific figures often encode the visual evidence behind scientific findings, yet figure plagiarism remains underexplored as a benchmarked multimodal evaluation problem. We present SciFigPlag-Bench, a benchmark for provenance-aware reasoning over scientific figures in scholarly documents. Unlike general image-similarity or image-forensics benchmarks, SciFigPlag-Bench evaluates whether a suspicious figure reuses evidence from a specific source figure, how the reused content has been transformed, and where the reused evidence appears. We introduce a factorized taxonomy that separates what is reused from how it is transformed, covering material-preserving reuse, such as full-figure and sub...
| Authors | Zhiying Cui, Minghao Yang, Linlin Gao et al. |
|---|---|
| Primary category | cs.CV |
| Published | 31 July 2026 |
| Last updated at source | 31 July 2026 |
Models and datasets referencing this paper
- FreeLand123/SciFigPlag-BenchDataset
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.