AI RESEARCH
MLLM-based Textual Explanations for Face Comparison
arXiv CS.AI
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ArXi:2603.16629v1 Announce Type: cross Multimodal Large Language Models (MLLMs) have recently been proposed as a means to generate natural-language explanations for face recognition decisions. While such explanations facilitate human interpretability, their reliability on unconstrained face images remains underexplored. In this work, we systematically analyze MLLM-generated explanations for the unconstrained face verification task on the challenging IJB-S dataset, with a particular focus on extreme pose variation and surveillance imagery.