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| title: README | |
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| Welcome to the LCO-Embedding project - Scaling Language-centric Omnimodal Representation Learning. | |
| ### Highlights: | |
| - We introduce LCO-Embedding, a language-centric omnimodal representation learning method and the LCO-Embedding model families, setting a new state-of-the-art on MIEB (Massive Image Embedding Benchmark) while supporting audio and videos. | |
| - We introduce Generation-Representation Scaling law, and connect models' generative capabilities and their representation upper bound. | |
| - We introduce SeaDoc, a challenging visual document retrieval task in southeast Asian languages; and show that continual generative pretraining before contrastive learning raises the representation upper bound. | |
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