MERLIN introduces multilingual multimodal dataset for smarter AI entity linking
MERLIN launches dataset merging images and text to enhance multilingual AI entity linking accuracy.
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2 days agoMERLIN introduces multilingual multimodal dataset for smarter AI entity linking
Researchers unveiled MERLIN, a benchmark dataset combining text and image data across Hindi, Tamil, Japanese, Vietnamese, and Indonesian to improve multilingual entity linking. Containing over 7,000 entity mentions connected to 2,500 Wikidata entries, MERLIN demonstrates how adding visual cues enhances entity disambiguation in low-resource languages. It supports models like LLaMA-2 and Aya-23 and aims to advance cross-lingual AI systems that require contextual visual understanding, enabling better global search, translation, and knowledge graph applications.
positive
2 days agoMERLIN introduces multilingual multimodal dataset for smarter AI entity linking
Researchers unveiled MERLIN, a benchmark dataset combining text and image data across Hindi, Tamil, Japanese, Vietnamese, and Indonesian to improve multilingual entity linking. Containing over 7,000 entity mentions connected to 2,500 Wikidata entries, MERLIN demonstrates how adding visual cues enhances entity disambiguation in low-resource languages. It supports models like LLaMA-2 and Aya-23 and aims to advance cross-lingual AI systems that require contextual visual understanding, enabling better global search, translation, and knowledge graph applications.
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MERLIN introduces multilingual multimodal dataset for smarter AI entity linking
2 days ago
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MERLIN launches dataset merging images and text to enhance multilingual AI entity linking accuracy.
Researchers unveiled MERLIN, a benchmark dataset combining text and image data across Hindi, Tamil, Japanese, Vietnamese, and Indonesian to improve multilingual entity linking. Containing over 7,000 entity mentions connected to 2,500 Wikidata entries, MERLIN demonstrates how adding visual cues enhances entity disambiguation in low-resource languages. It supports models like LLaMA-2 and Aya-23 and aims to advance cross-lingual AI systems that require contextual visual understanding, enabling better global search, translation, and knowledge graph applications.
Researchers unveiled MERLIN, a benchmark dataset combining text and image data across Hindi, Tamil, Japanese, Vietnamese, and Indonesian to improve multilingual entity linking. Containing over 7,000 entity mentions connected to 2,500 Wikidata entries, MERLIN demonstrates how adding visual cues enhances entity disambiguation in low-resource languages. It supports models like LLaMA-2 and Aya-23 and aims to advance cross-lingual AI systems that require contextual visual understanding, enabling better global search, translation, and knowledge graph applications.
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Oct 17, 2025 • 17:50 IST