Pith. sign in

Paper Citation Record · LEDGER

Edge-Based Learning for Improved Classification Under Adversarial Noise

As of 17 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2504.20077.

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

pith.paper-citation-record.v1
2504.20077 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:28:48.930897Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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 exact1
  • verified fuzzy8
  • unresolved21
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 677784ad-e74f-4b98-992d-fd67f1b928af · outbound

This paper cites Ieee Access6, 14410–14430 (2018).

Edge-Based Learning for Improved Classification Under Adversarial Noise Ieee Access6, 14410–14430 (2018)

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:28:49.198222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T10:28:48.832450Z digest=sha256:0c8c8f551a90af702fd67c20e8492f6a0b545f38232da7435bb5b16924667d3b

Observation 807060e6-c3d7-4ab2-b332-e91c9271a1ac · outbound

This paper cites In: International confer- ence on machine learning.

Edge-Based Learning for Improved Classification Under Adversarial Noise In: International confer- ence on machine learning

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.836547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.836547Z digest=sha256:7c1d94acc0e396a5cdeb4fbfd870cddebcf3d9ee62833992db281d324666d258

Observation 6f265507-9e7b-4d93-b23c-38f11b6e83fe · outbound

This paper cites In: 2022 45th International Conference on Telecommunications and Signal Processing (TSP).

Edge-Based Learning for Improved Classification Under Adversarial Noise In: 2022 45th International Conference on Telecommunications and Signal Processing (TSP)

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:28:49.182762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T10:28:48.839846Z digest=sha256:9af7516db50396e1e446d03eb639f111b7350722ddc5cca9fd2f61797d9a2d6d

Observation a807d973-40c0-4048-9f79-f5c1a66015f8 · outbound

This paper cites Adversarial Patch.

Edge-Based Learning for Improved Classification Under Adversarial Noise Adversarial Patch

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.843207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.843207Z digest=sha256:b2aec14295c3f650acd7fbaa7aa5fd2d247841ae58f3ca883b21494d9b36d00b

Observation 32760ace-1b5d-4789-90d6-f5e63c3ea41f · outbound

This paper cites IEEE Transactions on pattern analysis and machine intelligence (6), 679–698 (1986).

Edge-Based Learning for Improved Classification Under Adversarial Noise IEEE Transactions on pattern analysis and machine intelligence (6), 679–698 (1986)

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.846974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.846974Z digest=sha256:54e2a4f5416c13370ea368c4c5c4389e79ec7a7f08e2871ce8591d5a5115f369

Observation 4d0b8266-e4d0-471e-b018-9d22a2f6580e · outbound

This paper cites In: 2017 ieee symposium on security and privacy (sp).

Edge-Based Learning for Improved Classification Under Adversarial Noise In: 2017 ieee symposium on security and privacy (sp)

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.850281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.850281Z digest=sha256:fa2b3098f73465d4a827ec8c6b869996f754a54f72ac770b8b28ccceec1dd1d1

Observation f74ab13e-5fb5-4df8-8cc6-35eb32f4b454 · outbound

This paper cites IEEE Dataport10 (2020).

Edge-Based Learning for Improved Classification Under Adversarial Noise IEEE Dataport10 (2020)

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:28:49.161648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T10:28:48.853584Z digest=sha256:12f442f7f24379da9e6f1ec965a8dd493da1444c49be80c4b7102c9b0397cdff

Observation 01d32143-1223-4639-ba3d-0df7210c8213 · outbound

This paper cites COVID-19 Image Data Collection.

Edge-Based Learning for Improved Classification Under Adversarial Noise COVID-19 Image Data Collection

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.856701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.856701Z digest=sha256:fbd367f9112eb27c8698c666c08b4ba3cf159eadcc312a19312777444b1c3ae0

Observation 5661be85-fa06-42da-8390-2496b559f216 · outbound

This paper cites Attacking Large Language Models with Projected Gradient Descent.

Edge-Based Learning for Improved Classification Under Adversarial Noise Attacking Large Language Models with Projected Gradient Descent

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.859908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.859908Z digest=sha256:d6ada5c9116510abea8147a2befcb7adcffab8834823a1c9e3ad7db13aa1198b

Observation 98c706c4-7131-4f07-8f09-7780088878cc · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Edge-Based Learning for Improved Classification Under Adversarial Noise Explaining and Harnessing Adversarial Examples

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.863313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.863313Z digest=sha256:17accb59c55005098c1eb4a35c273e7f11e5819dd634cd52bf7bdd44653532ed

Observation 9e1beb87-600e-4a1d-9400-8efef2a3c113 · outbound

This paper cites On the (Statistical) Detection of Adversarial Examples.

Edge-Based Learning for Improved Classification Under Adversarial Noise On the (Statistical) Detection of Adversarial Examples

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.866752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.866752Z digest=sha256:9145ddf9b9996c11ee9b632f721a651573f7e1f621f2c369a975bbca6dafa1de

Observation d8686df2-f4e3-46cb-9e3f-0696fb81b293 · outbound

This paper cites Towards Deep Neural Network Architectures Robust to Adversarial Examples.

Edge-Based Learning for Improved Classification Under Adversarial Noise Towards Deep Neural Network Architectures Robust to Adversarial Examples

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.870127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.870127Z digest=sha256:ce2b2dbef3b658557fae382cee63b7a40b3e44b2c879c6a29dc88aaa06e828cb

Observation 494c88d2-a117-4988-92fe-234a52aaf589 · outbound

This paper cites an unresolved cited work.

Edge-Based Learning for Improved Classification Under Adversarial Noise Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-16T10:28:49.152726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T10:28:48.873335Z digest=sha256:d478289b35704a1a711dff4c03a09dfcb310ca6987afcc7eb2c23d885b511324

Observation ffee8070-bc11-43b9-94d5-a912f6fd3b16 · outbound

This paper cites an unresolved cited work.

Edge-Based Learning for Improved Classification Under Adversarial Noise Unresolved cited work

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.876542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.876542Z digest=sha256:c19d7cd3d01a2dc6538329b711172da89d5ec17b716617a24bdf256081b1578c

Observation 88387d0e-6ab6-455b-b93c-7a472917750b · outbound

This paper cites In: proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

Edge-Based Learning for Improved Classification Under Adversarial Noise In: proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:28:49.137956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T10:28:48.879517Z digest=sha256:9ae916a32eb8e670d209d0fb0fadf077324e2320dca41b9cfe5f3f916dbebcfd

Observation 94f36e4b-f9b2-4405-9952-492e4aab2074 · outbound

This paper cites In: Proceedings of the IEEE conference on computer vision and pattern recognition.

Edge-Based Learning for Improved Classification Under Adversarial Noise In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:28:49.127173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T10:28:48.883481Z digest=sha256:9d31dabb5d9780d260767c1ceed2ebe497007e5a723a8912ddab234839307ab7

Observation d26a9143-7a5f-4247-8719-4e1f03d6c816 · outbound

This paper cites Adversarial Attacks on Neural Network Policies.

Edge-Based Learning for Improved Classification Under Adversarial Noise Adversarial Attacks on Neural Network Policies

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.886510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.886510Z digest=sha256:e9728d5ae0d3d7a42ff45885671ed8a8c770e1c3e1c51274b1187a1f2dd19044

Observation 35e4ee32-b245-4f2f-a969-c22551ebbc5e · outbound

This paper cites Mendeley Data3(10.17632) (2018).

Edge-Based Learning for Improved Classification Under Adversarial Noise Mendeley Data3(10.17632) (2018)

Reference 18

Resolution
malformed identifier
raw_fallback, observed 2026-08-16T10:28:49.117723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T10:28:48.889781Z digest=sha256:1b16c66118d3d014109230d2ff5c7deed71fd7fccfda5701f2c0da9aa2ad4018

Observation 5753f73f-2814-407b-9918-785f6ccb3347 · outbound

This paper cites In: Artificial intelligence safety and security, pp.

Edge-Based Learning for Improved Classification Under Adversarial Noise In: Artificial intelligence safety and security, pp

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.892609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.892609Z digest=sha256:3924d531b6454fc04860ebb4764f9e4d4a46f156c9fc747733fe259629b80035

Observation e6aacb22-da50-46ff-bd08-72e0ce96d66c · outbound

This paper cites Proceedings of the IEEE86(11), 2278–2324 (1998).

Edge-Based Learning for Improved Classification Under Adversarial Noise Proceedings of the IEEE86(11), 2278–2324 (1998)

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.895619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.895619Z digest=sha256:c688f0181594ddbcb46f967788e498aeb95ef80ccbcdfbaf2233fce4b92a32a2

Observation 5b3731c1-d2cb-4686-8021-2f2f714f7e8f · outbound

This paper cites In: 2019 IEEE symposium on security and privacy (SP).

Edge-Based Learning for Improved Classification Under Adversarial Noise In: 2019 IEEE symposium on security and privacy (SP)

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:28:49.098219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T10:28:48.898542Z digest=sha256:089f0c0b726b65418391f5868b8d4d1090f41c641a27db9b303103507aa8e9be

Observation c5ab916a-c26c-4a9f-97b7-0c1fe66ab0bf · outbound

This paper cites In: Proceedings of the IEEE conference on computer vision and pattern recognition.

Edge-Based Learning for Improved Classification Under Adversarial Noise In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:28:49.088391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T10:28:48.901799Z digest=sha256:5a8b78ee0e6579a357dda418f51de82f16dd4eab99593f7d49fa98b7fe276afd

Observation 40f52bda-254f-4aab-bba6-5a6470694051 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Edge-Based Learning for Improved Classification Under Adversarial Noise Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.904749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.904749Z digest=sha256:794888d99ebfe8b8e52a566d23f8d1194d373a9a8e2e383535aeced14c793fd8

Observation bbc3da21-9aa7-4b8f-b1e5-936acf5f8485 · outbound

This paper cites On Detecting Adversarial Perturbations.

Edge-Based Learning for Improved Classification Under Adversarial Noise On Detecting Adversarial Perturbations

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.908173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.908173Z digest=sha256:9f10a5f8ab48aa915d9ab4bdd91bf6d3a1745394cc6fe257983cb50963173f34

Observation dfd2e5e8-48c5-4fd7-a7e9-7a754c035d4a · outbound

This paper cites In: 2016 IEEE European sym- posium on security and privacy (EuroS&P).

Edge-Based Learning for Improved Classification Under Adversarial Noise In: 2016 IEEE European sym- posium on security and privacy (EuroS&P)

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.911418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.911418Z digest=sha256:dc8ee415f13a4074ffd0b2fe6b163260accbd1935219a379ee41837db19520e2

Observation 92526eee-4d37-4f90-b14f-b3bf654edbcb · outbound

This paper cites https://doi.org/10.21227/s7pw-jr18, https://dx.doi.org/10.21227/ s7pw-jr18.

Edge-Based Learning for Improved Classification Under Adversarial Noise https://doi.org/10.21227/s7pw-jr18, https://dx.doi.org/10.21227/ s7pw-jr18

Reference 26

Resolution
verified exact
doi, observed 2026-08-16T10:28:48.958750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T10:28:48.914374Z digest=sha256:523af4e3df41e865fef1c54ec57cfc825bd885f36947d282a253d82c9d62f680

Observation f6a6677b-838a-4605-adeb-30e00dcf6f23 · outbound

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

Edge-Based Learning for Improved Classification Under Adversarial Noise Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.917411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.917411Z digest=sha256:69234af25bac15589c4f880870b2340c49aba186e6c9450988871c0cc93afdf8

Observation 6694e727-77fd-4113-98a0-f6e62cc321b9 · outbound

This paper cites In: Proceedings of the IEEE conference on computer vision and pattern recognition.

Edge-Based Learning for Improved Classification Under Adversarial Noise In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.920467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.920467Z digest=sha256:629db043ff07f72e961d26289eb49f7c6be4fe2f5afd29d3659129a1a3576042

Observation 25bcf319-b3a2-4293-b6a3-1d9746210f7e · outbound

This paper cites Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks.

Edge-Based Learning for Improved Classification Under Adversarial Noise Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.923597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.923597Z digest=sha256:9c3a1b59c68d8776074959d636e484fad632c831024f87ac81c99ae07422ef42

Observation aa5b2ea4-a823-4cc3-8ad3-e232b8213b82 · outbound

This paper cites IEEE/ACM Transactions on Networking30(3), 1294–1311 (2022).

Edge-Based Learning for Improved Classification Under Adversarial Noise IEEE/ACM Transactions on Networking30(3), 1294–1311 (2022)

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:48.927059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:28:48.927059Z digest=sha256:b9321dc33bee7721144dde74a940edf461339635a559f34aaa94d78d006271f2

Observation 6260781a-8a88-45bf-87f2-38ac0659285b · outbound

This paper cites Advances in neural information processing systems31 (2018).

Edge-Based Learning for Improved Classification Under Adversarial Noise Advances in neural information processing systems31 (2018)

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:28:49.060937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T10:28:48.930897Z digest=sha256:18ba87e0ee254a709f54aa1e488266a323c29b860a51297202de28f4aace1b85

Pith citing papers

No inbound Pith citation observations are available.