# Dyadic Context Prediction

EvolvingAvatar introduces a causal interactive 3D head generator that adapts at inference time via test-time training on user face video and dyadic audio, using a Dyadic Context Prediction self-supervised objective with persistent fast weights and transient jaw adaptation to produce speaking and listening motion, and releases InterHead-Bench, a 455.95-hour benchmark; experiments show improved conversational motion statistics over strong baselines and improvement as conversations unfold on the hardest out-of-distribution split, reducing mismatch with recorded user-avatar expression statistics by up to 11.1% from the first interval.

EvolvingAvatar introduces a causal interactive 3D head generator that adapts at inference time via test-time training on user face video and dyadic audio, using a Dyadic Context Prediction self-supervised objective with persistent fast weights and transient jaw adaptation to produce speaking and listening motion, and releases InterHead-Bench, a 455.95-hour benchmark; experiments show improved conversational motion statistics over strong baselines and improvement as conversations unfold on the hardest out-of-distribution split, reducing mismatch with recorded user-avatar expression statistics by up to 11.1% from the first interval.