From Behavior to Kinematics: A Hierarchical Motion-Language Benchmark for Rodent Motion Generation

Mice and rats are central to experimental studies of brain function and behavior, where brief changes in posture and local movement carry information that broad activity labels can miss. Studying language-conditioned generation of rodent motion requires motion–language pairs that preserve these observed details. We introduce RodentBEK, a benchmark built from real mouse and rat recordings with a shared 25-landmark skeleton and 8,195 motion windows. Its Behavior–Event–Kinematics (BEK) framework connects whole-window behavior captions, half-second event descriptions, and pose-derived kinematic evidence. Events are described from video and summarized into behavior captions; kinematic measurements support verification and revision of movement claims. The benchmark contains 24,585 behavior captions and 46,679 nonempty event descriptions, with source-time-separated training, validation, and test partitions. We evaluate diffusion, autoregressive, and masked-token generators with species-specific motion–text evaluators, comparing behavior-only and behavior-plus-event inputs to the same trained model. Event conditioning improves local event correspondence across all three models and both species, while its effects on global behavior alignment and motion distributions depend on the model. RodentBEK provides a benchmark for studying how generative models use fine-grained language to represent rodent movement.