arXiv Computer Vision August 27, 2026 By Xiaolong Sun, Qichao Wang, Hangyu Li, Liang Chen

CVE-SAI: Counterfactual Visual Evidence-Guided Selective Attribute Indexing for Risk-Controlled E-commerce Search

Read the original on arXiv Computer Vision →

CVE‑SAI is a method for e‑commerce product attribute indexing that first infers a candidate attribute from the primary image and question, then uses counterfactual visual evidence to decide whether to admit that candidate into the index. It employs Focus‑Zone Distortion to create an attribute‑specific visual‑dependence proxy and Evidence‑Guided Attention Redistribution to refine scoring, ensuring that only visually supported and risk‑controlled attributes are indexed. Experiments on Amazon Berkeley Objects demonstrate improved attribute inference, evidence localization, and controlled retrieval performance with minimal unsafe exposure.

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