MME-RealWorld is the largest manually annotated high-resolution benchmark for MLLMs, where even the best models achieve less than 60% accuracy on challenging real-world tasks.
A survey for foundation mod- els in autonomous driving.arXiv preprint arXiv:2402.01105
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SCP defines a new benchmark task for predicting spatial causal outcomes beyond direct observation and shows that 23 leading models lag far behind humans on it.
SoccerMaster is the first soccer-specific vision foundation model that unifies tasks from player detection to event classification via multi-task pretraining and outperforms task-specific models on downstream evaluations.
citing papers explorer
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MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?
MME-RealWorld is the largest manually annotated high-resolution benchmark for MLLMs, where even the best models achieve less than 60% accuracy on challenging real-world tasks.
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SCP: Spatial Causal Prediction in Video
SCP defines a new benchmark task for predicting spatial causal outcomes beyond direct observation and shows that 23 leading models lag far behind humans on it.
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SoccerMaster: A Vision Foundation Model for Soccer Understanding
SoccerMaster is the first soccer-specific vision foundation model that unifies tasks from player detection to event classification via multi-task pretraining and outperforms task-specific models on downstream evaluations.