Paper Citation Record · LEDGER

Prototype-Guided Robust Learning against Backdoor Attacks

As of 4 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2509.08748.

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

pith.paper-citation-record.v1
2509.08748 v2

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-18T19:32:49.650689Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+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

46 of 46 outbound references displayed

verified exact9
verified fuzzy36
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 127b0590-7eae-44bc-a5b3-369aa3d10131 · outbound

This paper cites Evasion attacks against machine learning at test time.

Prototype-Guided Robust Learning against Backdoor Attacks Evasion attacks against machine learning at test time

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.483683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5590df51-af74-40c1-9535-4e4015031309 · outbound

This paper cites Goodfellow, Jonathon Shlens, and Christian Szegedy.

Prototype-Guided Robust Learning against Backdoor Attacks Goodfellow, Jonathon Shlens, and Christian Szegedy

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.553437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation adab3adc-9558-471e-a4cd-bf12a121c846 · outbound

This paper cites LESSON: multi-label adversarial false data injection attack for deep learning locational detection.

Prototype-Guided Robust Learning against Backdoor Attacks LESSON: multi-label adversarial false data injection attack for deep learning locational detection

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.470956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6ebc646d-50a0-4565-b69c-71dd52e2a29b · outbound

This paper cites Poisoning attacks against support vector machines.

Prototype-Guided Robust Learning against Backdoor Attacks Poisoning attacks against support vector machines

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.442533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b4f34efd-fd66-4882-bdc3-b6250049208a · outbound

This paper cites BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain.

Prototype-Guided Robust Learning against Backdoor Attacks BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-05-18T19:36:48.209647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9a537ff7-1d26-400f-9898-8395202bca2b · outbound

This paper cites Joint adversarial example and false data injection attacks for state estimation in power systems.IEEE Transactions on Cybernetics, 52(12):13699–13713.

Prototype-Guided Robust Learning against Backdoor Attacks Joint adversarial example and false data injection attacks for state estimation in power systems.IEEE Transactions on Cybernetics, 52(12):13699–13713

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-18T19:36:47.391062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 76d95260-43fc-4db5-b532-e30742f4f1a3 · outbound

This paper cites When federated learning meets privacy-preserving computation.ACM Computing Surveys, 56(12):1–36.

Prototype-Guided Robust Learning against Backdoor Attacks When federated learning meets privacy-preserving computation.ACM Computing Surveys, 56(12):1–36

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.516875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 63385805-bc46-497f-bf47-0691444f6601 · outbound

This paper cites Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review.

Prototype-Guided Robust Learning against Backdoor Attacks Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-18T19:36:48.200549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 83f6d024-633a-4386-bb08-955903aa93bc · outbound

This paper cites Wild patterns reloaded: A survey of machine learning security against training data poisoning.ACM Computing Surveys, 55(13s):1–39.

Prototype-Guided Robust Learning against Backdoor Attacks Wild patterns reloaded: A survey of machine learning security against training data poisoning.ACM Computing Surveys, 55(13s):1–39

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.528328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6a85cedd-eb62-452c-a585-619a3a5cfad8 · outbound

This paper cites Evade: Targeted adversarial false data injection attacks for state estimation in smart grid.IEEE Transactions on Sustainable Computing.

Prototype-Guided Robust Learning against Backdoor Attacks Evade: Targeted adversarial false data injection attacks for state estimation in smart grid.IEEE Transactions on Sustainable Computing

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-18T19:36:47.412569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c72204c5-903d-4030-a33e-fbcbc9fdffb6 · outbound

This paper cites An overview of backdoor attacks against deep neural networks and possible defences.IEEE Open Journal of Signal Processing, 3:261–287.

Prototype-Guided Robust Learning against Backdoor Attacks An overview of backdoor attacks against deep neural networks and possible defences.IEEE Open Journal of Signal Processing, 3:261–287

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.502626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5d4b1361-0631-434a-a184-e3d3343018ff · outbound

This paper cites Molloy, and Biplav Srivastava.

Prototype-Guided Robust Learning against Backdoor Attacks Molloy, and Biplav Srivastava

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.450223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3c788749-0aa7-42e6-ba3e-0204acacdd03 · outbound

This paper cites Miller, and George Kesidis.

Prototype-Guided Robust Learning against Backdoor Attacks Miller, and George Kesidis

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.524848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6b945cde-3a78-4676-8c60-d123989602ae · outbound

This paper cites Demon in the variant: Statistical analysis of dnns for robust backdoor contamination detection.

Prototype-Guided Robust Learning against Backdoor Attacks Demon in the variant: Statistical analysis of dnns for robust backdoor contamination detection

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.533029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 22db3434-ed62-4631-819d-269b15efeb4b · outbound

This paper cites Training with more confidence: Mitigating injected and natural backdoors during training.

Prototype-Guided Robust Learning against Backdoor Attacks Training with more confidence: Mitigating injected and natural backdoors during training

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.538397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 48b28b6b-ba39-4b65-8669-b53657047119 · outbound

This paper cites Universal detection of backdoor attacks via density- based clustering and centroids analysis.IEEE TIFS.

Prototype-Guided Robust Learning against Backdoor Attacks Universal detection of backdoor attacks via density- based clustering and centroids analysis.IEEE TIFS

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-18T19:36:47.427078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 374d2c0d-df32-4f56-bbab-5bf1725b82b2 · outbound

This paper cites The "beatrix" resurrections: Robust backdoor detection via gram matrices.

Prototype-Guided Robust Learning against Backdoor Attacks The "beatrix" resurrections: Robust backdoor detection via gram matrices

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.464469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0253d047-6619-49a0-a1de-e43a0a9d7ba8 · outbound

This paper cites Anti-backdoor learning: Training clean models on poisoned data.

Prototype-Guided Robust Learning against Backdoor Attacks Anti-backdoor learning: Training clean models on poisoned data

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.542576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e5c79d20-3539-41eb-97a3-ecd010e5a16a · outbound

This paper cites Progressive poisoned data isolation for training-time backdoor defense.

Prototype-Guided Robust Learning against Backdoor Attacks Progressive poisoned data isolation for training-time backdoor defense

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.492447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 853f5de6-84c8-4b01-956b-1e33ae67f934 · outbound

This paper cites Backdoor defense via adaptively splitting poisoned dataset.

Prototype-Guided Robust Learning against Backdoor Attacks Backdoor defense via adaptively splitting poisoned dataset

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.453581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 53da56fc-1130-4be6-b035-207577abb12d · outbound

This paper cites Backdoor defense via deconfounded representation learning.

Prototype-Guided Robust Learning against Backdoor Attacks Backdoor defense via deconfounded representation learning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.556442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e39ea733-6096-4491-863f-0ec71f768a91 · outbound

This paper cites Backdoor defense via decoupling the training process.

Prototype-Guided Robust Learning against Backdoor Attacks Backdoor defense via decoupling the training process

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.477125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation adef28e8-3824-4746-9f6c-a61f18244b31 · outbound

This paper cites Effective backdoor defense by exploiting sensitivity of poisoned samples.

Prototype-Guided Robust Learning against Backdoor Attacks Effective backdoor defense by exploiting sensitivity of poisoned samples

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.431304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a12e9c79-e9c7-43b3-b451-452a0fe9a446 · outbound

This paper cites Towards a proactive{ML} approach for detecting backdoor poison samples.

Prototype-Guided Robust Learning against Backdoor Attacks Towards a proactive{ML} approach for detecting backdoor poison samples

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.434268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ecd8e335-2105-495f-9e7d-5576dae44689 · outbound

This paper cites The victim and the beneficiary: Exploiting a poisoned model to train a clean model on poisoned data.

Prototype-Guided Robust Learning against Backdoor Attacks The victim and the beneficiary: Exploiting a poisoned model to train a clean model on poisoned data

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.498657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1c3cd6d3-fa28-4a03-8fec-4bc79c123b98 · outbound

This paper cites Bypassing backdoor detection algorithms in deep learning.

Prototype-Guided Robust Learning against Backdoor Attacks Bypassing backdoor detection algorithms in deep learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.447527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8e67b022-e916-435f-9109-614d4e25ef1f · outbound

This paper cites An embarrassingly simple backdoor attack on self-supervised learning.

Prototype-Guided Robust Learning against Backdoor Attacks An embarrassingly simple backdoor attack on self-supervised learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.479974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bdc84830-c72c-4f5b-bcf3-f8b003399cd5 · outbound

This paper cites The perils of learning from unlabeled data: Backdoor attacks on semi-supervised learning.

Prototype-Guided Robust Learning against Backdoor Attacks The perils of learning from unlabeled data: Backdoor attacks on semi-supervised learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.495495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 75eb1818-5128-4494-b6fa-2d10837bb736 · outbound

This paper cites Revisiting the assumption of latent separability for backdoor defenses.

Prototype-Guided Robust Learning against Backdoor Attacks Revisiting the assumption of latent separability for backdoor defenses

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.437643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 405cf7f7-8fd3-419c-910f-66c8fa4a3c94 · outbound

This paper cites Sinkhorn distances: Lightspeed computation of optimal transport.

Prototype-Guided Robust Learning against Backdoor Attacks Sinkhorn distances: Lightspeed computation of optimal transport

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.489748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d94044dc-d9e0-48af-90f3-ec6864e23da2 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Prototype-Guided Robust Learning against Backdoor Attacks UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-18T19:36:48.218037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d755d38a-3ae4-49a3-a661-d9d45d2bc629 · outbound

This paper cites Deep residual learning for image recognition.

Prototype-Guided Robust Learning against Backdoor Attacks Deep residual learning for image recognition

Reference 32

Resolution: verified exact; doi, observed 2026-05-18T19:36:47.400476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c1583bea-c538-4722-bab1-981b7bc24208 · outbound

This paper cites Unsupervised learning of visual features by contrasting cluster assignments.

Prototype-Guided Robust Learning against Backdoor Attacks Unsupervised learning of visual features by contrasting cluster assignments

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.550498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 558dbc3d-5d76-4de6-be44-9a09a4379798 · outbound

This paper cites Progressive poisoned data isolation for training-time backdoor defense.

Prototype-Guided Robust Learning against Backdoor Attacks Progressive poisoned data isolation for training-time backdoor defense

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.487083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 67c3289b-afe8-482a-9498-f8dec55f0edd · outbound

This paper cites Very deep convolutional networks for large-scale image recognition.

Prototype-Guided Robust Learning against Backdoor Attacks Very deep convolutional networks for large-scale image recognition

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.505734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f898f685-c033-4617-b2ce-13a22f8af5ad · outbound

This paper cites Weinberger.

Prototype-Guided Robust Learning against Backdoor Attacks Weinberger

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.458926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6280be4d-a7c5-4557-8c43-330889cf8f30 · outbound

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

Prototype-Guided Robust Learning against Backdoor Attacks An image is worth 16x16 words: Transformers for image recognition at scale

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.461654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 69e88d7a-8e75-4ee7-b4cd-fe0e1df90eff · outbound

This paper cites Wanet - imperceptible warping-based backdoor attack.

Prototype-Guided Robust Learning against Backdoor Attacks Wanet - imperceptible warping-based backdoor attack

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.509551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9dc933e9-2d39-4a73-b716-6644459060f6 · outbound

This paper cites Can you hear it? backdoor attacks via ultrasonic triggers.

Prototype-Guided Robust Learning against Backdoor Attacks Can you hear it? backdoor attacks via ultrasonic triggers

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.456363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 56f4b7bd-e753-43ab-9007-757f584937e5 · outbound

This paper cites COMBAT: alternated training for effective clean-label backdoor attacks.

Prototype-Guided Robust Learning against Backdoor Attacks COMBAT: alternated training for effective clean-label backdoor attacks

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.473597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0d9d7a46-ced7-417a-96b5-4166c6a35133 · outbound

This paper cites Lotus: Evasive and resilient backdoor attacks through sub-partitioning.

Prototype-Guided Robust Learning against Backdoor Attacks Lotus: Evasive and resilient backdoor attacks through sub-partitioning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.547255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 233332f1-222d-47c4-93ef-4289868b9bc9 · outbound

This paper cites Narcissus: A practical clean-label backdoor attack with limited information.

Prototype-Guided Robust Learning against Backdoor Attacks Narcissus: A practical clean-label backdoor attack with limited information

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.521588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 36425ec6-f3bb-4d2a-be66-46788fd0b3af · outbound

This paper cites an unresolved cited work.

Prototype-Guided Robust Learning against Backdoor Attacks Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-05-18T19:42:50.513147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 369b2986-6add-4fe2-9bf7-ed70b4aafe08 · outbound

This paper cites Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition.

Prototype-Guided Robust Learning against Backdoor Attacks Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-05-18T19:36:48.223547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9639dbfd-a51c-40de-9fa1-35e4d3e8c631 · outbound

This paper cites A temporal chrominance trigger for clean-label backdoor attack against anti-spoof rebroadcast detection.IEEE TDSC, 20(6):4752–4762.

Prototype-Guided Robust Learning against Backdoor Attacks A temporal chrominance trigger for clean-label backdoor attack against anti-spoof rebroadcast detection.IEEE TDSC, 20(6):4752–4762

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:42:50.467891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 17679dfb-5f84-45bd-8688-bd21703de4c6 · outbound

This paper cites Backdoor Contrastive Learning via Bi-level Trigger Optimization.

Prototype-Guided Robust Learning against Backdoor Attacks Backdoor Contrastive Learning via Bi-level Trigger Optimization

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-18T19:36:48.195662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Pith citing papers

No inbound Pith citation observations are available.