Inverting Multi-Vector Visual Document Indices
Stored multi-vector document indices can be inverted to recover page words and sensitive tokens.
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Stored multi-vector document indices can be inverted to recover page words and sensitive tokens.
RenderRank reranks documents from compressed visual tokens, using 16.5-35.5% fewer tokens and beating sub-4B text baselines.

H Company released NeoMME, 260M/800M single-tower multimodal encoders matching 3.75B ColQwen2.5 on ViDoRe v3 while being 14.4x smaller, under Apache 2.0.
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