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arXiv AI By Mohamed Bayan Kmainasi, Ali Ezzat Shahroor, Elisa Sartori, Giovanni Da San Martino, Firoj Alam

ProBel: Propaganda Detection with Techniques, Spans, and Explanations

Read the original on arXiv AI →

ProBel is a bilingual Arabic and English resource for propaganda detection that aligns binary labels, multi-label annotations for 23 propaganda techniques grouped into six categories, technique-labeled spans, and reference explanations for news sentences. The dataset supports matched binary, coarse-grained, multi-label, and span-level tasks in both languages, and the authors evaluate zero‑shot prompting, task‑specific fine‑tuning, and joint training. A single bilingual multi‑task model achieves the best overall performance, with cross‑task analysis revealing that joint classification preserves binary performance while span‑only training can weaken sentence‑level prediction, and that joint bilingual training yields the most stable results.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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