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Keio University
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Rigel achieves over 10-point improvements in image and video captioning evaluation by aligning automatic metrics with human judgment without relying on large vocabulary sets.
Turns out, your MLLM judge is probably biased: MLLMs tend to prefer their own generations and those from similar architectures, potentially skewing benchmark results.