Collection of Multimodal Rerankers Released
CShorten30 · x · 2026-07-16
The post introduces a set of multimodal rerankers capable of processing both text and document images, supported by the work of @coreprinciple.
Key information includes:
- The 2B version performs outstandingly among open-source rerankers of the same size
- Achieved 62.66 NDCG@10 on ViDoRe V3
- The author also attached a thread summarizing their experiences
These models are well-suited for scenarios like document retrieval and mixed image-text ranking.
Related event: LightOn-rerank Targets Mixed-Corpus RAG With Multimodal Rerankers(10 posts)→
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