SciFigPlag-Bench - Reuse Localization: leaderboard

SciFigPlag-Bench (2026) reuse localization: box the reused subfigure in both the source and the suspicious figure; a pair counts when both boxes reach IoU of at least 0.5. Accuracy in percent, higher is better.

Metric: Paired localization accuracy (%; both the source-side and the suspicious-side boxes of a reused subfigure must reach IoU of at least 0.5; SciFigPlag-Bench pairs of source and suspicious scientific figures (2,582 plagiarized pairs from documented real cases and taxonomy-guided synthesis, 2,541 visually similar negatives); the same task-specific prompts for every model, temperature 0). Source: arxiv.org. Saturation forecast: Around February 2027. 16 models tracked.

Top models

#ModelScoreOverall rank
1Gemma 4 31B (IT)75.2#342
2GPT-5.473.5#123
3Gemini 3 Flash71#164
4Qwen 3.6 35B A3B69#462
5Claude Sonnet 4.664.2#161
6Qwen 3.5 35B A3B64.1#482
7Gemma 4 26B A4B (IT)5.8#549
8Mistral Small 41.2#1201
9Qwen 3.5 2B0.8#4810
10Gemma 3 4B (IT)0.2#3831

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=scifigplag-bench-reuse-localization · How It Works · Data refreshed daily, snapshot 2026-11-13.