Which Way Did It Move? Diagnosing and Overcoming Directional Motion Blindness in Video-LLMs

The paper identifies a new failure mode in Video Large Language Models (Video‑LLMs) called directional motion blindness, where models struggle to correctly interpret basic signed image‑plane motion directions. By tracing motion signals through the model pipeline, the authors reveal a binding gap between motion information and verbal output, and propose MoDirect, a motion‑direction instruction‑tuning dataset, and DeltaDirect, a projector‑level objective that predicts 2‑D motion vectors from frame deltas. Experiments show that DeltaDirect dramatically boosts motion‑direction accuracy on both synthetic and real‑world benchmarks while maintaining overall video‑understanding performance.

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• llms
• fine-tuning