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detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "Phoenix-VL 1.5 Medium Technical Report", "url": "https://arxiv.org/abs/2605.10391v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Vincent Maladière", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "Phoenix-VL 1.5 Medium Technical Report", "url": "https://arxiv.org/abs/2605.10391v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Yimu Pan", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "Phoenix-VL 1.5 Medium Technical Report", "url": "https://arxiv.org/abs/2605.10391v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "organization", "name": "HTX × Mistral AI", "note": "Cited historical collaboration, not a platform organization account; individual attribution remains incomplete.", "roles": [ "formulator" ], "source": { "citation": "Phoenix-VL 1.5 Medium Technical Report", "url": "https://arxiv.org/abs/2605.10391v1" } } ], "evidence": [ { "description": "Bibliographic/stated-result source; not a WRS proof verification", "id": "source-0", "kind": "source_reference", "source": { "citation": "Phoenix-VL 1.5 Medium Technical Report", "url": "https://arxiv.org/abs/2605.10391v1" } }, { "description": "Bibliographic/stated-result source; not a WRS proof verification", "id": "source-1", "kind": "source_reference", "source": { "citation": "Mistral research publications index", "url": "https://mistral.ai/research/" } } ], "origin": "HUMAN_LEGACY", "record_profile": "wrs-local-research-notes-0.1", "record_type": "research_note", "rrp_version": "0.1", "scope": { "description": "Inherits MistralMedium and continual pretraining/ODPO. Localized empirical performance does not prove no capability loss, regulatory compliance or correct legal advice.", "domain": "Regional multimodal language-model adaptation" }, "sources": [ { "citation": "Phoenix-VL 1.5 Medium Technical Report", "url": "https://arxiv.org/abs/2605.10391v1" }, { "citation": "Mistral research publications index", "url": "https://mistral.ai/research/" } ], "statement": "# Phoenix-VL: localized multimodal training and evaluation resources\n\nAdapted a pretrained multimodal model using curated regional/general replay data, long-context continued training and local multimodal/alignment data, introducing Singapore-focused evaluation and behavior frameworks.\n\n## Scientific scope\n\nInherits MistralMedium and continual pretraining/ODPO. Localized empirical performance does not prove no capability loss, regulatory compliance or correct legal advice.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nArka Ray; Askar Ali Mohamed Jawad; Biondi Lee; Elijah Seah; Eva Lim; Fiona Teo; Grace Toh; Guang Xiang Teo; Jun En Tan; Jia Hui Bong; Jiale Wang; Jonathan Ng; Justin Tan; Kai Zhe Yew; Matthew Ong; Shun Yi Yeo; Wen Jett Lam; Wen Xiu Tan; Ze Yu Zhang; Adrien Sadé; Guillaume Kunsch; Jia Sin Loh; Nicolas Schuhl; Rupert Menneer; Umar Jamil; Vincent Maladière; Yimu Pan\n\nAll 27 named technical contributors are listed. Two executive sponsors receive separate support credit, not scientific-person associations.\n\n\n\n## Original sources\n\n- [Phoenix-VL 1.5 Medium Technical Report](https://arxiv.org/abs/2605.10391v1)\n- [Mistral research publications index](https://mistral.ai/research/)\n", "summary": "Adapted a pretrained multimodal model using curated regional/general replay data, long-context continued training and local multimodal/alignment data, introducing Singapore-focused evaluation and behavior frameworks.", "title": "Phoenix-VL: localized multimodal training and evaluation resources" }, "record_id": "urn:uuid:5f71ecbb-89a5-493c-a299-05e095e36d69", "version": 1, "source_ref": { "record_id": "urn:uuid:5f71ecbb-89a5-493c-a299-05e095e36d69", "version": 1, "content_hash": "sha256:889e622efe317260893393301312d6bbc702f8621f037e89ad12bf8927bc6d78" }, "export_view": "wrs-public-editorial-view-1", "public_view_hash": "sha256:ab09674ce590c1f19ba2b9b1578a3af7cf8fbd158bfecb25333663484e1090ba" }, "target": { "record_id": "urn:uuid:5f71ecbb-89a5-493c-a299-05e095e36d69", "version": 1, "content_hash": "sha256:889e622efe317260893393301312d6bbc702f8621f037e89ad12bf8927bc6d78" }, "published_grade": { "profile": "wrs-published-grade-1", "edition": "2026-10-28.1", "id": "htx-mistral-phoenix-localized-multimodal-resource-2026", "entry_id": "htx-mistral-phoenix-localized-multimodal-resource-2026", "revision": 1, "title": "Phoenix-VL: localized multimodal training and evaluation resources", "context": "Regional multimodal language-model adaptation", "track": "Human-designed research method or resource", "band": "B", "modifier": null, "status": "PROVISIONAL_EDITORIAL", "assessed_on": "2026-10-16", "evidence_cutoff": "2026-10-16", "achievement_state": "SUPPORTED_SCOPED_RESULT", "what_changed": "Adapted a pretrained multimodal model using curated regional/general replay data, long-context continued training and local multimodal/alignment data, introducing Singapore-focused evaluation and behavior frameworks.", "scope": "Adapted a pretrained multimodal model using curated regional/general replay data, long-context continued training and local multimodal/alignment data, introducing Singapore-focused evaluation and behavior frameworks. Inherits MistralMedium and continual pretraining/ODPO. Localized empirical performance does not prove no capability loss, regulatory compliance or correct legal advice.", "evidence_summary": "The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Inherits MistralMedium and continual pretraining/ODPO. 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