Paper Citation Record · LEDGER

Attention Alignment Between Humans and Vision-Language Models

As of 24 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2606.17410.

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

pith.paper-citation-record.v1
2606.17410 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T02:13:09.264228Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

53 of 53 outbound references displayed

verified exact0
verified fuzzy0
unresolved48
parse uncertain0
malformed identifier0
metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e3244d64-885b-49d8-9bff-baa89797f9c5 · outbound

This paper cites 1967 , publisher=.

Attention Alignment Between Humans and Vision-Language Models 1967 , publisher=

Reference 1

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Source-reported events for the cited work

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Attention Alignment Between Humans and Vision-Language Models Vision Research , volume=

Reference 2

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Observation c5020f5b-5000-4322-9fd7-6b3fe3e50895 · outbound

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Attention Alignment Between Humans and Vision-Language Models IEEE Transactions on Pattern Analysis and Machine Intelligence , volume=

Reference 3

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Attention Alignment Between Humans and Vision-Language Models Advances in Neural Information Processing Systems , volume=

Reference 4

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Source-reported events for the cited work

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Observation 52536840-fdeb-4020-9013-91c233ad0f74 · outbound

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Attention Alignment Between Humans and Vision-Language Models Unresolved cited work

Reference 5

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Observation 06a27180-334c-4f26-a654-29c872c25883 · outbound

This paper cites DeepGaze II: Reading fixations from deep features trained on object recognition.

Attention Alignment Between Humans and Vision-Language Models DeepGaze II: Reading fixations from deep features trained on object recognition

Reference 6

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Attention Alignment Between Humans and Vision-Language Models IEEE Transactions on Pattern Analysis and Machine Intelligence , volume=

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Source-reported events for the cited work

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Attention Alignment Between Humans and Vision-Language Models International Conference on Machine Learning , pages=

Reference 8

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Source-reported events for the cited work

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Observation 92c20b67-f3ab-44e3-9ab8-c2e342880a5f · outbound

This paper cites Predicting human eye fixations via an.

Attention Alignment Between Humans and Vision-Language Models Predicting human eye fixations via an

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-27T02:13:09.264228Z

Source-reported events for the cited work

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Attention Alignment Between Humans and Vision-Language Models Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages=

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Resolution: unresolved; no resolver link, observed 2026-06-27T02:13:09.264228Z

Source-reported events for the cited work

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Attention Alignment Between Humans and Vision-Language Models Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages=

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-27T02:13:09.264228Z

Source-reported events for the cited work

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Observation 32cb6698-b39c-471d-af75-8de4a948929d · outbound

This paper cites Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth.

Attention Alignment Between Humans and Vision-Language Models Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth

Reference 12

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Source-reported events for the cited work

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Observation f78976e4-2f94-4494-a0aa-7e24f801c049 · outbound

This paper cites Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics , pages=.

Attention Alignment Between Humans and Vision-Language Models Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics , pages=

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-27T02:13:09.264228Z

Source-reported events for the cited work

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Attention Alignment Between Humans and Vision-Language Models Advances in Neural Information Processing Systems , volume=

Reference 14

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Observation 8c33b505-34f4-4e89-bf8e-aeaf0969a5d1 · outbound

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Attention Alignment Between Humans and Vision-Language Models Unresolved cited work

Reference 15

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Source-reported events for the cited work

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Observation 2a01ede9-b419-4cc6-bc4c-59be7e3aa922 · outbound

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Attention Alignment Between Humans and Vision-Language Models Unresolved cited work

Reference 16

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Attention Alignment Between Humans and Vision-Language Models Molmo and

Reference 17

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This paper cites Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages=.

Attention Alignment Between Humans and Vision-Language Models Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages=

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-27T02:13:09.264228Z

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Observation 47debffb-9e86-4a84-86c2-d5d91a6a430d · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Attention Alignment Between Humans and Vision-Language Models An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 19

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Source-reported events for the cited work

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Observation 3cbb6f4d-57bb-480f-abb4-aa8a8fb08cc4 · outbound

This paper cites International Conference on Learning Representations , year=.

Attention Alignment Between Humans and Vision-Language Models International Conference on Learning Representations , year=

Reference 20

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Source-reported events for the cited work

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Observation 178ad028-c2cc-4553-a05f-278b170a8cde · outbound

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Attention Alignment Between Humans and Vision-Language Models Sentence-

Reference 21

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Observation 230ac9ad-dc69-4552-b13d-3243aaf67d77 · outbound

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Attention Alignment Between Humans and Vision-Language Models Nature Communications , volume=

Reference 22

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Source-reported events for the cited work

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Observation c2e63b4f-fff2-4b40-91da-858d8ff98044 · outbound

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Attention Alignment Between Humans and Vision-Language Models Are Convolutional Neural Networks or Transformers more like human vision?

Reference 23

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Observation f955efc8-5e16-4c52-ae6a-686a2a432160 · outbound

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Attention Alignment Between Humans and Vision-Language Models Nature Machine Intelligence , volume=

Reference 24

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Attention Alignment Between Humans and Vision-Language Models bioRxiv , year=

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Attention Alignment Between Humans and Vision-Language Models Nature Machine Intelligence , pages=

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Attention Alignment Between Humans and Vision-Language Models The American Statistician , volume=

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Attention Alignment Between Humans and Vision-Language Models Advances in Neural Information Processing Systems , volume=

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Attention Alignment Between Humans and Vision-Language Models Trends in Cognitive Sciences , year=

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Attention Alignment Between Humans and Vision-Language Models Proceedings of the IEEE International Conference on Computer Vision , pages=

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Attention Alignment Between Humans and Vision-Language Models Journal of Vision , volume=

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Attention Alignment Between Humans and Vision-Language Models Cognitive Psychology , volume=

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Attention Alignment Between Humans and Vision-Language Models Nature Human Behaviour , volume=

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Attention Alignment Between Humans and Vision-Language Models Frontiers in Computer Science , volume=

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Attention Alignment Between Humans and Vision-Language Models Neural Networks , year=

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Attention Alignment Between Humans and Vision-Language Models Frontiers in Computational Neuroscience , volume=

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Attention Alignment Between Humans and Vision-Language Models Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics , pages=

Reference 39

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Reference 40

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Attention Alignment Between Humans and Vision-Language Models Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

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Attention Alignment Between Humans and Vision-Language Models Proceedings of the Conference on Empirical Methods in Natural Language Processing , pages=

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Attention Alignment Between Humans and Vision-Language Models Proceedings of the 25th Conference on Computational Natural Language Learning , pages=

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Attention Alignment Between Humans and Vision-Language Models Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages=

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Attention Alignment Between Humans and Vision-Language Models Nature Reviews Neuroscience , volume=

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Attention Alignment Between Humans and Vision-Language Models Analysis of Visual Behavior , editor=

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Attention Alignment Between Humans and Vision-Language Models Trends in Neurosciences , volume=

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Attention Alignment Between Humans and Vision-Language Models Trends in Cognitive Sciences , volume=

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Attention Alignment Between Humans and Vision-Language Models Microsoft

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Attention Alignment Between Humans and Vision-Language Models Learning what and where to attend

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Attention Alignment Between Humans and Vision-Language Models Journal of cognitive neuroscience , volume=

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Attention Alignment Between Humans and Vision-Language Models NeuroImage , volume=

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Attention Alignment Between Humans and Vision-Language Models Nature Machine Intelligence , pages=

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Pith citing papers

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