Network Interpretation

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

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Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

9 shown of 9 papers with code (26 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Plug-and-Play VQA: Zero-shot VQA by Conjoining Large Pretrained Models with Zero Training
  17 Oct 2022 3 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  Visual question answering (VQA) is a hallmark of vision and language reasoning and a challenging task under the zero-shot setting.
• Fooling Neural Network Interpretations via Adversarial Model Manipulation
  6 Feb 2019 3 repositories listed
  We ask whether the neural network interpretation methods can be fooled via adversarial model manipulation, which is defined as a model fine-tuning step that aims to radically alter the explanations without hurting the…
• Perturbation on Feature Coalition: Towards Interpretable Deep Neural Networks
  23 Aug 2024 1 repository listed
  The inherent "black box" nature of deep neural networks (DNNs) compromises their transparency and reliability.
• Towards More Robust Interpretation via Local Gradient Alignment
  29 Nov 2022 1 repository listed
  However, the lack of considering the normalization of the attributions, which is essential in their visualizations, has been an obstacle to understanding and improving the robustness of feature attribution methods.
• Reflash Dropout in Image Super-Resolution
  22 Dec 2021 1 repository listed
  Dropout is designed to relieve the overfitting problem in high-level vision tasks but is rarely applied in low-level vision tasks, like image super-resolution (SR).
• DeepEverest: Accelerating Declarative Top-K Queries for Deep Neural Network Interpretation
  6 Apr 2021 1 repository listed
  We design, implement, and evaluate DeepEverest, a system for the efficient execution of interpretation by example queries over the activation values of a deep neural network.
• Attribution Preservation in Network Compression for Reliable Network Interpretation
  28 Oct 2020 1 repository listed
  Neural networks embedded in safety-sensitive applications such as self-driving cars and wearable health monitors rely on two important techniques: input attribution for hindsight analysis and network compression to…
• Proper Network Interpretability Helps Adversarial Robustness in Classification
  26 Jun 2020 1 repository listed Syntology ran 6 of 17 samples · 11 unverified · 1 pointer-only (licence)
  Recent works have empirically shown that there exist adversarial examples that can be hidden from neural network interpretability (namely, making network interpretation maps visually similar), or interpretability is…
• An Empirical Study on the Relation between Network Interpretability and Adversarial Robustness
  7 Dec 2019 1 repository listed
  We demonstrate that training the networks to have interpretable gradients improves their robustness to adversarial perturbations.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.