OmniCompass: A Holistic Benchmark for Omni-Modal Video Grounding and Understanding
With the rapid development of multimodal large language models (MLLMs), evaluating their video understanding capabilities has become increasingly important. Existing video understanding benchmarks cover only part of the evaluation dimensions, limiting systematic diagnosis of omni-modal video understanding. We introduce OmniCompass, a holistic benchmark for omni-modal video grou
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With the rapid development of multimodal large language models (MLLMs), evaluating their video understanding capabilities has become increasingly important. Existing video understanding benchmarks cover only part of the evaluation dimensions, limiting systematic diagnosis of omni-modal video understanding. We introduce OmniCompass, a holistic benchmark for omni-modal video grou
This benchmark addresses a critical need for systematically evaluating the rapidly evolving capabilities of multimodal large language models in video understanding. For ML engineers, understanding such benchmarks is crucial for developing and assessing the performance of next-generation AI systems, particularly in complex real-world applications requiring joint audio-visual reasoning.