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Flow Splatting achieves superior image quality and faster rendering speeds by efficiently modeling dynamic scenes with 4D Gaussian representations.
Current vision-language models falter in streaming interaction understanding, with alarming mis-calibration leading to confidently incorrect predictions.
MLLMs struggle to juggle proactive tasks and reactive queries in dynamic video streams, but a simple agentic framework can significantly improve their coordination without any training.
Get constant-factor approximations of Pareto frontiers in stochastic multi-objective optimization with only poly-logarithmic SAT oracle queries, bypassing the prohibitive costs of existing methods.
