Query-Conditioned Evidential Keyframe Sampling for MLLM-Based Long-Form Video Understanding
This work proposes an evidence-driven keyframe sampling framework motivated by an information-theoretic perspective, and trains a query-conditioned evidence scoring network using annotated answer-supporting segments to motivate a tractable frame-wise selection criterion.