DialSeg-Ar - OPUS News: leaderboard

Linear topic segmentation of conversational Arabic from the DialSeg-Ar benchmark (Chirkunov et al., ACL 2026): the model splits an ordered list of utterances into topic-coherent segments. Test split of OPUS News Commentary texts in Modern Standard Arabic. WindowDiff on a 0-1 scale, the share of sliding windows where the predicted boundary count differs from the gold count; lower is better.

Metric: WindowDiff (0-1, lower is better; share of sliding windows over the utterance sequence whose predicted boundary count differs from the gold count; test split of OPUS News Commentary in Modern Standard Arabic; LLMs prompted zero-shot, DialSeg-Ar-Gemma3-4B fine-tuned on the training split). Source: arxiv.org. Saturation forecast: Estimated already saturated. 5 models tracked.

Top models

#ModelScoreOverall rank
1Fanar-1-9B-Instruct0.57#1765
2ALLaM-7B-Instruct-preview0.65#1861
3Gemma 3 4B (IT)0.75#3848

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

Interactive version: theaggregate.ai/benchmark?slug=dialseg-ar-opus-news · How It Works · Data refreshed daily, snapshot 2026-11-12.