NeoMME: Efficient Multimodal-Multilingual Encoder Released
Researchers introduced NeoMME, a family of 260M and 800M-parameter multimodal-multilingual bidirectional encoders that process text and raw image patches in a single Transformer. Fine-tuned for visual document retrieval, NeoMME-Retriever outperforms models under 800M on ViDoRe v3, achieves 2x throughput of ModernVBERT, and compresses embeddings 255x. Released under Apache 2.0.
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