Paper Citation Record · LEDGER

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers

As of 12 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2501.06831.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.06831 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:55:44.424508Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

verified exact2
verified fuzzy0
unresolved12
parse uncertain0
malformed identifier1
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 685abfd8-83f9-4f0a-aa02-bf8c48688964 · outbound

This paper cites What do we need to build explainable AI systems for the medical domain?.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers What do we need to build explainable AI systems for the medical domain?

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T20:55:44.372098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a938fb2e-4805-41f4-b0df-260933eeb090 · outbound

This paper cites Interpretable Neural Network Decoupling.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Interpretable Neural Network Decoupling

Reference 5

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T20:55:44.572596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation aef3c276-df79-4977-9fd8-6318fcfc5224 · outbound

This paper cites Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:55:44.559309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 19308dc8-e7c0-48db-83ed-1ddb10fd89d9 · outbound

This paper cites EfficientPS: Efficient Panoptic Segmentation.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers EfficientPS: Efficient Panoptic Segmentation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T20:55:44.391285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd921d19-9396-4c92-87ca-58a212ef390f · outbound

This paper cites RISE: Randomized Input Sampling for Explanation of Black-box Models.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers RISE: Randomized Input Sampling for Explanation of Black-box Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T20:55:44.395054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f06ed93-953b-4317-a534-1abc78b88a0d · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T20:55:44.402203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a6b7034-a670-4846-ad1e-c7913204ea63 · outbound

This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T20:55:44.409894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3472a9cf-a935-4040-afa8-38c6c8781020 · outbound

This paper cites an unresolved cited work.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:55:44.621493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e05e596f-bbc8-4af1-9e26-9593bfbdbfce · outbound

This paper cites Explainability of deep vision-based autonomous driving systems: Review and challenges.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Explainability of deep vision-based autonomous driving systems: Review and challenges

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T20:55:44.417523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77b6f0e8-260b-4419-88f6-9cb804bee2d9 · outbound

This paper cites Object Detectors Emerge in Deep Scene CNNs.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Object Detectors Emerge in Deep Scene CNNs

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T20:55:44.424508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9a7ccf4-6fe0-4326-8fa8-c2e60a4688dd · outbound

This paper cites Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-10T20:55:44.406067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b25b665-2504-41ea-85ab-a1d04bee4830 · outbound

This paper cites Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models

Reference 2015

Resolution: malformed identifier; no resolver link, observed 2026-08-10T20:55:44.398771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68b5456c-aafb-47ee-a4b6-c1ffd7b39db7 · outbound

This paper cites Architecture Disentanglement for Deep Neural Networks.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Architecture Disentanglement for Deep Neural Networks

Reference 2017

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:55:44.585990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ccc55f74-f3f4-4ca1-b393-335f0037c91c · outbound

This paper cites Metrics for Explainable AI: Challenges and Prospects.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Metrics for Explainable AI: Challenges and Prospects

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-10T20:55:44.368186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42ff8666-81d5-4e99-aa05-41615d0ab691 · outbound

This paper cites Neuron Shapley: Discovering the Responsible Neurons.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Neuron Shapley: Discovering the Responsible Neurons

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-10T20:55:44.363789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29241fd4-7915-498b-abcb-10e761824c8b · outbound

This paper cites Generative Counterfactual Introspection for Explainable Deep Learning.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Generative Counterfactual Introspection for Explainable Deep Learning

Reference 2020

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T20:55:44.545166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 03f1c90a-cf45-4f89-9459-0d8b22d83880 · outbound

This paper cites ResNeSt: Split-Attention Networks.

Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers ResNeSt: Split-Attention Networks

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-10T20:55:44.421105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.