{"schema_version":"onlylabs.public_signal.v1","title":"Mistral AI Model: mistralai/LIDstral-Arabic","description":"Mistral AI model signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/66bc2fe5-557f-452b-8004-5dd5d9af1c23","json_url":"https://onlylabs.fyi/signals/66bc2fe5-557f-452b-8004-5dd5d9af1c23/signal.json","generated_at":"2026-10-24T20:20:49.366Z","evidence_latest_fetched_at":"2026-10-10T07:20:23.510584+00:00","signal_first_seen_at":"2026-10-10T07:20:08.166813+00:00","org":{"slug":"mistral","name":"Mistral AI","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/mistral","dossier_json_url":"https://onlylabs.fyi/labs/mistral/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/66bc2fe5-557f-452b-8004-5dd5d9af1c23","signal_json":"https://onlylabs.fyi/signals/66bc2fe5-557f-452b-8004-5dd5d9af1c23/signal.json","source":"https://huggingface.co/mistralai/LIDstral-Arabic","lab_dossier":"https://onlylabs.fyi/labs/mistral","lab_dossier_json":"https://onlylabs.fyi/labs/mistral/dossier.json","analysis":"https://onlylabs.fyi/analysis/mistral","analysis_json":"https://onlylabs.fyi/analysis/mistral/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/mistral/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":"https://onlylabs.fyi/topics/releases","topic_signals_json":"https://onlylabs.fyi/topics/releases/signals.json","topic_feed":"https://onlylabs.fyi/topics/releases/feed.xml","data_business":null},"answer_pack":{"answer":"Mistral AI published mistralai/LIDstral-Arabic. 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It identifies Modern Standard Arabic, all Arabic dialects, and non-Arabic languages that use the same script. We include these non-Arabic languages in training to help the model distinguish languages that share a script and avoid classifying text as Arabic based on its script alone. Method The model combines a fastText one-vs-all (OVA) classifier, an MLP stacker, and per-class isotonic calibration: 1. **fastText OVA**: produces independent scores for each class, preserving evidence for competing languages and dialects. 2. **MLP stacker**: A 64-unit LayerNorm MLP maps these scores to probabilities over the classes. It uses 144 features derived from raw scores, prior corrections, confidence margins, entropy, and regional summaries. The checkpoint stores feature normalization and label ordering. 3. **Per-class isotonic regressors**: fitted on development predictions calibrate the MLP probabilities. The pipeline then renormalizes them across classes. 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