Paper Citation Record · LEDGER

Human Aligned Compression for Robust Models

As of 21 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2504.12255.

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

pith.paper-citation-record.v1
2504.12255 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:37:36.959594Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

31 of 31 outbound references displayed

verified exact0
verified fuzzy19
unresolved11
parse uncertain0
malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 79334dbf-a76b-4a9a-858c-26b78f65466b · outbound

This paper cites Generative adversar- ial networks for extreme learned image compression.

Human Aligned Compression for Robust Models Generative adversar- ial networks for extreme learned image compression

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.423635Z

Source-reported events for the cited work

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Observation 22bff719-0d97-45e0-ab82-b5b209745127 · outbound

This paper cites Towards evaluating the robustness of neural networks, 2017.

Human Aligned Compression for Robust Models Towards evaluating the robustness of neural networks, 2017

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.408734Z

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Observation e13fd9a5-69a9-45d0-adfa-41727dcb88df · outbound

This paper cites Learned image compression with discretized gaussian mixture likelihoods and attention modules, 2020.

Human Aligned Compression for Robust Models Learned image compression with discretized gaussian mixture likelihoods and attention modules, 2020

Reference 3

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Source-reported events for the cited work

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Observation 68258034-3429-4c1d-9b95-bc5b1f6ace37 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Human Aligned Compression for Robust Models Imagenet: A large-scale hierarchical image database

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T12:37:36.829701Z

Source-reported events for the cited work

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Observation a51a40c6-9dd0-4703-b86b-41436eb5bb80 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale, 2021.

Human Aligned Compression for Robust Models An image is worth 16x16 words: Transformers for image recognition at scale, 2021

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T12:37:36.834865Z

Source-reported events for the cited work

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Observation 654a1106-c313-4a7b-9092-eb454fcdddff · outbound

This paper cites an unresolved cited work.

Human Aligned Compression for Robust Models Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-16T12:37:37.365090Z

Source-reported events for the cited work

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Observation 6227002f-dac7-45b8-9a55-0d49efaa8009 · outbound

This paper cites Exploring the landscape of spatial robustness, 2019.

Human Aligned Compression for Robust Models Exploring the landscape of spatial robustness, 2019

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.350452Z

Source-reported events for the cited work

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Observation f2f31d35-df1c-4245-9fd3-e8b421d7580c · outbound

This paper cites Deep universal generative adversarial compression artifact removal.

Human Aligned Compression for Robust Models Deep universal generative adversarial compression artifact removal

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.335233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2da4a8b5-f2b0-4d97-80cd-d815cfcc9dd0 · outbound

This paper cites Adams, Ian Goodfellow, David An- dersen, and George E.

Human Aligned Compression for Robust Models Adams, Ian Goodfellow, David An- dersen, and George E

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.320166Z

Source-reported events for the cited work

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Observation 19c1dc09-6549-48cb-9471-917c08a75080 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Human Aligned Compression for Robust Models Explaining and Harnessing Adversarial Examples

Reference 10

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Source-reported events for the cited work

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Observation 526565eb-4144-4021-80ef-199d73ab14be · outbound

This paper cites Checkerboard context model for effi- cient learned image compression.

Human Aligned Compression for Robust Models Checkerboard context model for effi- cient learned image compression

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T12:37:36.866926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 067c46b6-a213-41bc-9058-e9f986652e45 · outbound

This paper cites Elic: Efficient learned image compres- sion with unevenly grouped space-channel contextual adap- tive coding, 2022.

Human Aligned Compression for Robust Models Elic: Efficient learned image compres- sion with unevenly grouped space-channel contextual adap- tive coding, 2022

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.294749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e173c1af-af42-429b-844f-f44c674c6d7b · outbound

This paper cites Deep residual learning for image recognition, 2015.

Human Aligned Compression for Robust Models Deep residual learning for image recognition, 2015

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.279709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a4897a33-eb93-4ec9-8c9a-b5618019d165 · outbound

This paper cites Distilling the knowledge in a neural network, 2015.

Human Aligned Compression for Robust Models Distilling the knowledge in a neural network, 2015

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T12:37:36.879587Z

Source-reported events for the cited work

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Observation 15610fb5-add1-4a14-9f7a-161556b3bc6a · outbound

This paper cites Adversar- ial examples are not bugs, they are features.

Human Aligned Compression for Robust Models Adversar- ial examples are not bugs, they are features

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.255517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2cb2630c-b388-4a5b-8f9e-fa2f42c081f7 · outbound

This paper cites Torchattacks: A PyTorch Repository for Adversarial Attacks.

Human Aligned Compression for Robust Models Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T12:37:36.888409Z

Source-reported events for the cited work

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Observation 792ae008-c337-4c40-897d-fc4885632ea1 · outbound

This paper cites Adver- sarial examples in the physical world, 2017.

Human Aligned Compression for Robust Models Adver- sarial examples in the physical world, 2017

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.240849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3d51275e-ad44-4dfe-a991-08cb1c6c6618 · outbound

This paper cites Learned image compression with mixed transformer-cnn architectures.

Human Aligned Compression for Robust Models Learned image compression with mixed transformer-cnn architectures

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T12:37:36.897986Z

Source-reported events for the cited work

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Observation ed5cee91-1fca-4e29-8c1d-d05acb8b56ba · outbound

This paper cites Towards deep learning models resistant to adversarial attacks, 2019.

Human Aligned Compression for Robust Models Towards deep learning models resistant to adversarial attacks, 2019

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.216257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ecb5c606-ca46-417c-9d30-edd084732489 · outbound

This paper cites High-fidelity generative image compres- sion, 2020.

Human Aligned Compression for Robust Models High-fidelity generative image compres- sion, 2020

Reference 20

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Source-reported events for the cited work

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Observation 66f62e13-799d-46d9-a711-61c1bb3798e9 · outbound

This paper cites Joint autoregressive and hierarchical priors for learned image compression.

Human Aligned Compression for Robust Models Joint autoregressive and hierarchical priors for learned image compression

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.190227Z

Source-reported events for the cited work

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Observation c1c9ed7a-0a8a-453b-8050-22887d94bfe5 · outbound

This paper cites Deepfool: a simple and accurate method to fool deep neural networks, 2016.

Human Aligned Compression for Robust Models Deepfool: a simple and accurate method to fool deep neural networks, 2016

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.174816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation de7586d8-0ab5-4ecd-861a-3b0fdc09f868 · outbound

This paper cites Distillation as a defense to adversar- ial perturbations against deep neural networks, 2016.

Human Aligned Compression for Robust Models Distillation as a defense to adversar- ial perturbations against deep neural networks, 2016

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.158622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ebbd3c25-78b7-4728-a089-a5e434ad693f · outbound

This paper cites Pytorch: An im- perative style, high-performance deep learning library, 2019.

Human Aligned Compression for Robust Models Pytorch: An im- perative style, high-performance deep learning library, 2019

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.141896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0b39c275-2842-49d1-a61d-122af6385ac9 · outbound

This paper cites Kornia: an open source differentiable computer vision library for pytorch.

Human Aligned Compression for Robust Models Kornia: an open source differentiable computer vision library for pytorch

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.125616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2ec6f8fb-da8a-434f-9e98-d3b2789b8435 · outbound

This paper cites Deep learning in medical image analysis.

Human Aligned Compression for Robust Models Deep learning in medical image analysis

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.108411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 443c89cd-38b1-4981-8592-8d2bcd31c8a1 · outbound

This paper cites Jpeg-resistant adversarial im- ages.

Human Aligned Compression for Robust Models Jpeg-resistant adversarial im- ages

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.092651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1ffd592a-af2c-4f7c-bc6c-9994c12ce73d · outbound

This paper cites Deep neural networks for object detection.

Human Aligned Compression for Robust Models Deep neural networks for object detection

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.076810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ee49a049-ecce-42e5-92ac-6277c08363ed · outbound

This paper cites In- triguing properties of neural networks, 2014.

Human Aligned Compression for Robust Models In- triguing properties of neural networks, 2014

Reference 29

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Source-reported events for the cited work

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Observation ee1564fa-76ae-465d-bb32-f095e0228ec3 · outbound

This paper cites Adversarial risk and the dangers of evaluating against weak attacks, 2018.

Human Aligned Compression for Robust Models Adversarial risk and the dangers of evaluating against weak attacks, 2018

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:37:37.050345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation df1e59b3-9c4d-40ed-a227-641e0734371b · outbound

This paper cites Object detection in 20 years: A survey.Proceed- ings of the IEEE, 111(3):257–276, 2023.

Human Aligned Compression for Robust Models Object detection in 20 years: A survey.Proceed- ings of the IEEE, 111(3):257–276, 2023

Reference 31

Resolution: malformed identifier; raw_fallback, observed 2026-08-16T12:37:37.034480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.