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LLMs can generate better features from tabular data when deployed as a multi-agent system with explicit memory of past procedures, feedback, and concepts.
Existing defenses against talking-head manipulation are easily bypassed: SyncBreaker shows how to effectively degrade lip sync and facial dynamics by jointly perturbing audio and video.