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Relational Knowledge Distillation Brings DNN Representations Close Enough to Humans to Be Aligned Without Supervision

arXiv · AI, language, vision and robotics · article · Aug 28, 2026 · UTC

Linking the internal representations of deep neural networks (DNNs) to human mental representations is important for using DNNs as computational models of human vision. Existing DNN representations remain insufficiently similar to human mental representations, which are not directly observable and are therefore commonly measured through large-scale similarity judgments of object images. A natural approach to narrowing this gap is to directly transfer the relational structure of human representations into DNNs, and previous studies have reported improved human-DNN representational similarity. H

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