Taehyeong Kim

FRAME is proposed, which turns language into query-relevant attribute weights, uses learned readouts to estimate per-attribute evidence from object embeddings, and ranks objects by aggregating this evidence according to the query, showing that persistent object attributes can be exposed as composable evidence for accurate and efficient multi-attribute retrieval.