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Visual agents consistently falter at detecting procedural errors, but a new framework shows how to enhance their comprehension capabilities dramatically.
Real-robot trials are costly and slow, but DataLadder enables scalable evaluations and data generation through a seamless interplay between robots, simulations, and human feedback.
Adaptive expert collaboration and holistic token learning can significantly boost performance in fine-grained multimodal visual analytics tasks like driver action recognition.
