MMEB
Not in model cards
Multimodal embedding models are scored on classification, visual question answering, multimodal retrieval and visual grounding, with 16 evaluation datasets in and out of distribution.
Introduced with the VLM2Vec model, ICLR 2025. 36 datasets in total, 20 for training and 16 for evaluation. Repo has 701 stars.
Made by University of Waterloo (TIGER-Lab) + Salesforce Research Released Oct 2024 General visual questions All tasks public
- Level
- Everyday Most adults, without training
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Short answer A number, word or short string matched to a key.
No scores here yet
We have no scores for MMEB yet.
No lab model card reports it yet
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark.
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