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News/Non-identifiability of Explanations from Model Behavior in Deep Networks of Image Authenticity Judgments
arxiv
PublishedApril 9, 2026 at 4:00 AM
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Non-identifiability of Explanations from Model Behavior in Deep Networks of Image Authenticity Judgments

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arxiv.orgfull article ↗
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Publisher summary· verbatim

arXiv:2604.07254v1 Announce Type: cross Abstract: Deep neural networks can predict human judgments, but this does not imply that they rely on human-like information or reveal the cues underlying those judgments. Prior work has addressed this issue using attribution heatmaps, but their explanatory va

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Discussion
Mentioned models
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    VGG
  • 02
    EfficientNetB3
  • 03
    Barlow Twins
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Tags
04
#computer-vision#machine-learning#explanability#robustness

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Mentioned models
03
  • 01
    VGG
  • 02
    EfficientNetB3
  • 03
    Barlow Twins
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#computer-vision#machine-learning#explanability#robustness

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arxivPerturbation-Based Data Selection for Medical Question Answering1harxivAdaptive Transfer of Representational Signatures for LLM Reliability Detection1harxivPropasafe-Hybrid: A Text-Based Hybrid Propaganda Detection Tool1harxivIncremental Predictive Value of LLM Tutoring Interactions for Student Performance1h
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