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OpenCompass Hub
OmniAlign-V
OmniAlign-V datasets mainly focus on improving the alignment of Multi-modal Large Language Models(MLLMs) with human preference. It contains 205k high-quality Image-Quetion-Answer pairs with open-ended, creative quetions and long, knowledge-rich, comprehensive answers.
Evaluation context and evidence
- Source
- OpenCompass Hub
- Publisher
- Shanghai Jiaotong University, Shanghai AI Laboratory, etc.
- Benchmark release
- 2025-02-18
- Collected
- 2026-08-18
- Modality
- multimodal
These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.
Original sources
Reported results 0
This source record has no numeric results in our collection. That does not mean a score of zero or that no public results exist. Consult the original resources above.