M3-Embedding is a single model for multi-lingual, multi-functional, and multi-granular text embeddings trained via self-knowledge distillation that achieves new state-of-the-art results on multilingual, cross-lingual, and long-document retrieval benchmarks.
D u R eader: a C hinese Machine Reading Comprehension Dataset from Real-world Applications
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ML-Embed releases open multilingual embedding models trained with a new 3D-ML framework that reportedly set new MTEB records on 9 of 17 benchmarks, especially in low-resource languages.
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M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation
M3-Embedding is a single model for multi-lingual, multi-functional, and multi-granular text embeddings trained via self-knowledge distillation that achieves new state-of-the-art results on multilingual, cross-lingual, and long-document retrieval benchmarks.
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ML-Embed: Inclusive and Efficient Embeddings for a Multilingual World
ML-Embed releases open multilingual embedding models trained with a new 3D-ML framework that reportedly set new MTEB records on 9 of 17 benchmarks, especially in low-resource languages.