Preprint Open access
Exploiting answer-invariant redundancies in satellite imagery for efficient VLM inference on edge
Onboard vision-language models could enable satellites to answer queries directly, but exhaustive tiled inference over high-resolution imagery is slow and energy-intensive. We identify answer-invariant token redundancy (AITR): image tiles and vision tokens that can be removed without changing the final answer. We prese …