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Paper Citation Record · LEDGER

Enhancing Vision Transformer Explainability Using Artificial Astrocytes

As of 8 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2505.21513.

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

pith.paper-citation-record.v1
2505.21513 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:29:46.134125Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

28 of 28 outbound references displayed

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External citation measurements

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Outbound references

Observation c113f38b-34ac-473d-bd0f-a177b18bdcd4 · outbound

This paper cites Learning deep features for discrimina- tive localization.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Learning deep features for discrimina- tive localization

Reference 1

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Observation 069ff92f-fa32-4386-afd4-aa6c4cf1fb60 · outbound

This paper cites The explainability of transformers: Current status and directions.Computers, 13(4):92, 2024.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes The explainability of transformers: Current status and directions.Computers, 13(4):92, 2024

Reference 2

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Observation 6156428f-fd46-466c-b492-6a815dd88877 · outbound

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

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models

Reference 3

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Observation d5094f5b-f09a-498f-b478-c646f54be0bb · outbound

This paper cites Towards A Rigorous Science of Interpretable Machine Learning.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Towards A Rigorous Science of Interpretable Machine Learning

Reference 4

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Observation 1b289c66-6d95-4b0b-afa5-548fa223cc5a · outbound

This paper cites Learning what and where to attend.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Learning what and where to attend

Reference 5

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Source-reported events for the cited work

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Observation 54f236b8-a22e-40ad-b84e-cc90010fa451 · outbound

This paper cites Multi- layer perceptron with chaos glial network.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Multi- layer perceptron with chaos glial network

Reference 6

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Observation 235ac1fa-27a2-4ade-a98c-b0933c19e34b · outbound

This paper cites Artificial astrocytes improve neu- ral network performance.PloS one, 6(4):e19109, 2011.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Artificial astrocytes improve neu- ral network performance.PloS one, 6(4):e19109, 2011

Reference 7

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Observation 96e92bc4-11c8-49b9-8240-243aa5565882 · outbound

This paper cites Training-free approach of convolutional neu- ral networks with astrocyte-inspired architectures.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Training-free approach of convolutional neu- ral networks with astrocyte-inspired architectures

Reference 8

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Source-reported events for the cited work

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Observation 3128eacf-5722-41e6-9a45-5651d786a12e · outbound

This paper cites Modeling work- ing memory in a spiking neuron network accompanied by astrocytes.Frontiers in Cellular Neuroscience, 15:631485,.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Modeling work- ing memory in a spiking neuron network accompanied by astrocytes.Frontiers in Cellular Neuroscience, 15:631485,

Reference 9

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Observation f32537af-2329-4aeb-819d-a5a018775e33 · outbound

This paper cites Astronet: When astrocyte meets artificial neural network.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Astronet: When astrocyte meets artificial neural network

Reference 10

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Observation 34234c05-08eb-4cba-a53d-1bfe9d4e191a · outbound

This paper cites Ma-net: Re- thinking neural unit in the light of astrocytes.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Ma-net: Re- thinking neural unit in the light of astrocytes

Reference 11

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Observation 39ad6707-5c58-44f7-9960-43587406323c · outbound

This paper cites Building transformers from neurons and astro- cytes.Proceedings of the National Academy of Sciences, 120(34):e2219150120, 2023.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Building transformers from neurons and astro- cytes.Proceedings of the National Academy of Sciences, 120(34):e2219150120, 2023

Reference 12

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Observation 61bba7d3-3749-4f51-8cd9-26744aff0869 · outbound

This paper cites Transformer inter- pretability beyond attention visualization.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Transformer inter- pretability beyond attention visualization

Reference 13

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Observation f0aff59c-82e8-4681-a0c4-b53648af10e1 · outbound

This paper cites Class-Discriminative Attention Maps for Vision Transformers.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Class-Discriminative Attention Maps for Vision Transformers

Reference 14

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Observation 4dbf6dbc-20a2-4193-823a-394bee3f815b · outbound

This paper cites Harmonizing the object recognition strategies of deep neu- ral networks with humans.Advances in neural information processing systems, 35:9432, 2022.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Harmonizing the object recognition strategies of deep neu- ral networks with humans.Advances in neural information processing systems, 35:9432, 2022

Reference 15

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Observation e97ad295-9b8d-4160-b8f0-563cece46072 · outbound

This paper cites Improving vit interpretability with patch-level mask prediction.Pattern Recognition Letters, 187:73–79, 2025.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Improving vit interpretability with patch-level mask prediction.Pattern Recognition Letters, 187:73–79, 2025

Reference 16

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Observation 56da94be-da35-4d8b-8fdc-95ca1756f13e · outbound

This paper cites Sanzgiri, and Philip G.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Sanzgiri, and Philip G

Reference 17

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Observation da61f1e8-419d-4430-a3e4-60aff530e42d · outbound

This paper cites Astrocyte–synapse interactions and cell adhesion molecules.The FEBS journal, 290(14):3512–3526, 2023.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Astrocyte–synapse interactions and cell adhesion molecules.The FEBS journal, 290(14):3512–3526, 2023

Reference 18

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Observation 0f19af85-0f64-406e-8148-144c2f491790 · outbound

This paper cites Human as- trocytes: structure and functions in the healthy brain.Brain Structure and Function, 222(5):2017–2029, 2017.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Human as- trocytes: structure and functions in the healthy brain.Brain Structure and Function, 222(5):2017–2029, 2017

Reference 19

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Observation 98932740-95b2-4bbb-b2c4-a498ed44a9e4 · outbound

This paper cites Loose excitation–secretion coupling in astrocytes.Glia, 64(5):655– 667, 2016.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Loose excitation–secretion coupling in astrocytes.Glia, 64(5):655– 667, 2016

Reference 20

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This paper cites Pytorch library for cam methods.https://github.com/jacobgil/ pytorch-grad-cam, 2021.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Pytorch library for cam methods.https://github.com/jacobgil/ pytorch-grad-cam, 2021

Reference 21

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Observation bf798950-2afb-48d5-b2e7-0c51c24cc18a · outbound

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Enhancing Vision Transformer Explainability Using Artificial Astrocytes Grad-CAM: Why did you say that?

Reference 22

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Observation 5a7d74fb-e77d-45d9-b158-4e3ef00d32eb · outbound

This paper cites Grad-cam++: General- ized gradient-based visual explanations for deep convolu- tional networks.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Grad-cam++: General- ized gradient-based visual explanations for deep convolu- tional networks

Reference 23

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Observation e1cf50b4-da1c-45a3-90b1-aa5e33e4647f · outbound

This paper cites Pytorch image models.https : / / github.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Pytorch image models.https : / / github

Reference 24

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Observation deb9a8c7-4727-44b1-94e0-66f2b4eed887 · outbound

This paper cites Towards explain- able deep visual saliency models.Computer Vision and Im- age Understanding, 235:103782, 2023.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Towards explain- able deep visual saliency models.Computer Vision and Im- age Understanding, 235:103782, 2023

Reference 25

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Observation de390e20-23b6-47e0-b2db-2f184325e39f · outbound

This paper cites The proof and measurement of association between two things.The American Journal of Psychology, 15(1):72–101, 1904.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes The proof and measurement of association between two things.The American Journal of Psychology, 15(1):72–101, 1904

Reference 26

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Observation 3e8e2786-a308-4fe3-9087-32d5b511f3e9 · outbound

This paper cites Measures of the amount of ecologic association between species.Ecology, 26(3):297–302, 1945.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Measures of the amount of ecologic association between species.Ecology, 26(3):297–302, 1945

Reference 27

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Observation c8a29e8a-1e07-406b-b8f4-9dff72c5b38a · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.IEEE transactions on image processing, 13(4):600–612, 2004.

Enhancing Vision Transformer Explainability Using Artificial Astrocytes Image quality assessment: from error visibility to structural similarity.IEEE transactions on image processing, 13(4):600–612, 2004

Reference 28

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Pith citing papers

No inbound Pith citation observations are available.