MICE, a mouse-behavior foundation model, handles one to four cage mates from a single checkpoint: its social stage sharpens multi-animal behavior
Mouse behavior analysis has relied on self-supervised pose models that encode each animal independently, yet aggression, courtship, mounting and allogrooming are inherently multi-animal. MICE aligns six mouse-pose datasets to a universal 12-keypoint vocabulary and pretrains jointly, pairing a hierarchical individual encoder for per-mouse kinematics with a Perceiver-style social encoder whose learned latent codebook handles any group size, so one checkpoint serves different animal counts without retraining. Across six datasets and four evaluation protocols, MICE matches or exceeds prior keypoint-based baselines, and layer-wise probing shows the social stage improves discriminability beyond the individual encoder.