Paper Citation Record · LEDGER

Multi-Task Consistency-based Detection of Adversarial Attacks

As of 19 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2608.07750.

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

pith.paper-citation-record.v1
2608.07750 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:21:52.486049Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

43 of 43 outbound references displayed

verified exact1
verified fuzzy35
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3803f8a1-5231-402d-8f2f-d2cef80e0a8a · outbound

This paper cites Object detection in 20 years: A survey,.

Multi-Task Consistency-based Detection of Adversarial Attacks Object detection in 20 years: A survey,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T00:21:52.168412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1346b2b6-4cf7-492f-98c6-67cdec013818 · outbound

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

Multi-Task Consistency-based Detection of Adversarial Attacks Towards deep learning models resistant to adversarial attacks,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T00:21:52.176566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c18d666-bc7e-42c8-9c57-1b1822f57a7d · outbound

This paper cites Adversarial objectness gradient attacks in real- time object detection systems,.

Multi-Task Consistency-based Detection of Adversarial Attacks Adversarial objectness gradient attacks in real- time object detection systems,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.550750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 27442dc1-22f5-4950-acee-3b6c1d718509 · outbound

This paper cites Adversarial training for free!.

Multi-Task Consistency-based Detection of Adversarial Attacks Adversarial training for free!

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.516402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 82b90fac-0f0b-49aa-89f1-e388f9ac17e9 · outbound

This paper cites {PatchCURE}: Improving certifiable robustness, model utility, and computation effi- ciency of adversarial patch defenses,.

Multi-Task Consistency-based Detection of Adversarial Attacks {PatchCURE}: Improving certifiable robustness, model utility, and computation effi- ciency of adversarial patch defenses,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.478999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b50805c5-26e7-47ea-9234-db9b9cc9c149 · outbound

This paper cites PatchCleanser: Certifiably robust defense against adversarial patches for any image classifier,.

Multi-Task Consistency-based Detection of Adversarial Attacks PatchCleanser: Certifiably robust defense against adversarial patches for any image classifier,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.457734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dd69b589-a0e9-4bff-8910-d2db64c7d4cc · outbound

This paper cites Compression to the rescue: Defending from adversarial attacks across modalities,.

Multi-Task Consistency-based Detection of Adversarial Attacks Compression to the rescue: Defending from adversarial attacks across modalities,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.428504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7f1fa289-933c-4afc-b17e-ec7d391dce97 · outbound

This paper cites Detecting adversarial perturbations in multi-task perception,.

Multi-Task Consistency-based Detection of Adversarial Attacks Detecting adversarial perturbations in multi-task perception,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.405121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2226b2f8-dcac-41f9-8e72-527da171e408 · outbound

This paper cites Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges,.

Multi-Task Consistency-based Detection of Adversarial Attacks Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.378354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f7724b3b-51a5-4978-ac02-532f852b08ad · outbound

This paper cites A survey on 3d object detection methods for autonomous driving applications,.

Multi-Task Consistency-based Detection of Adversarial Attacks A survey on 3d object detection methods for autonomous driving applications,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T00:21:52.258717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbb33c70-5f47-4370-b5f4-222b49efa30a · outbound

This paper cites Joint 3d instance segmentation and object detection for autonomous driving,.

Multi-Task Consistency-based Detection of Adversarial Attacks Joint 3d instance segmentation and object detection for autonomous driving,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.327593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 35f1e97e-bc55-4599-bdcc-a586075a5392 · outbound

This paper cites Multi-Task Adversarial Attack.

Multi-Task Consistency-based Detection of Adversarial Attacks Multi-Task Adversarial Attack

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-11T00:21:52.634197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation aac4fc04-9993-4e2c-af21-47abb5708c50 · outbound

This paper cites Real-time memory efficient multitask learning model for autonomous driving,.

Multi-Task Consistency-based Detection of Adversarial Attacks Real-time memory efficient multitask learning model for autonomous driving,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.307349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 38754caa-da34-4881-a562-57340e75baad · outbound

This paper cites Multitask learning,.

Multi-Task Consistency-based Detection of Adversarial Attacks Multitask learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.281585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ff48f7ac-c548-4105-83b3-3a596b526093 · outbound

This paper cites Ubernet: Training a universal convolutional neural network for low-, mid-, and high-level vision using diverse datasets and limited memory,.

Multi-Task Consistency-based Detection of Adversarial Attacks Ubernet: Training a universal convolutional neural network for low-, mid-, and high-level vision using diverse datasets and limited memory,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.255520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f9cc6cc0-6dff-40bf-8173-3c86ee6b9cc2 · outbound

This paper cites Fully- adaptive feature sharing in multi-task networks with applications in person attribute classification,.

Multi-Task Consistency-based Detection of Adversarial Attacks Fully- adaptive feature sharing in multi-task networks with applications in person attribute classification,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.231817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7ccdb898-4768-48c5-95b5-524c3946f000 · outbound

This paper cites Adversarial examples for semantic segmentation and object detection,.

Multi-Task Consistency-based Detection of Adversarial Attacks Adversarial examples for semantic segmentation and object detection,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.208255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 11ab3aba-a982-42c8-ac1a-fe6f3e0a749d · outbound

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

Multi-Task Consistency-based Detection of Adversarial Attacks Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T00:21:52.320466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abb98b8d-15d2-49ad-9c97-a748bddad590 · outbound

This paper cites A novel industrial intrusion detection method based on threshold-optimized cnn-bilstm-attention using roc curve,.

Multi-Task Consistency-based Detection of Adversarial Attacks A novel industrial intrusion detection method based on threshold-optimized cnn-bilstm-attention using roc curve,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.183796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 20bfc2c5-951a-4c99-86bc-24ca53d26e63 · outbound

This paper cites Adversarial robustness in multi-task learning: Promises and illusions,.

Multi-Task Consistency-based Detection of Adversarial Attacks Adversarial robustness in multi-task learning: Promises and illusions,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.152295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 195a68d3-fa07-46db-b2e9-435d767bbd2e · outbound

This paper cites Bdd100k Model Zoo,.

Multi-Task Consistency-based Detection of Adversarial Attacks Bdd100k Model Zoo,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.127068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e0bb81b9-8ef1-4014-8c4e-4b573dc4881d · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

Multi-Task Consistency-based Detection of Adversarial Attacks MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T00:21:52.352988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f40b163b-5aab-447c-87fe-62f53ad0f8e7 · outbound

This paper cites Adversarially-aware robust object detector,.

Multi-Task Consistency-based Detection of Adversarial Attacks Adversarially-aware robust object detector,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.103254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2ea7d87d-6c9b-4cac-89b1-b8eadd49ec1f · outbound

This paper cites A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks.

Multi-Task Consistency-based Detection of Adversarial Attacks A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T00:21:52.367035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16c8a98a-b241-48af-9a9c-7d7516857c00 · outbound

This paper cites Detection based defense against adversarial examples from the steganalysis point of view,.

Multi-Task Consistency-based Detection of Adversarial Attacks Detection based defense against adversarial examples from the steganalysis point of view,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.079059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 97cea521-556c-476c-9b03-e01645cfc0fb · outbound

This paper cites Detecting adversarial examples from sensitivity inconsistency of spatial-transform domain,.

Multi-Task Consistency-based Detection of Adversarial Attacks Detecting adversarial examples from sensitivity inconsistency of spatial-transform domain,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.055203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 51b2ff8f-86d5-4afd-bdeb-1101fb9cb514 · outbound

This paper cites Dla: dense- layer-analysis for adversarial example detection,.

Multi-Task Consistency-based Detection of Adversarial Attacks Dla: dense- layer-analysis for adversarial example detection,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:53.025817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 654f4690-b3e5-455f-b5fa-cdcadc49bd88 · outbound

This paper cites Using self- supervised learning can improve model robustness and uncertainty,.

Multi-Task Consistency-based Detection of Adversarial Attacks Using self- supervised learning can improve model robustness and uncertainty,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T00:21:52.397365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d13829af-82c2-4a56-855a-2418bfae7498 · outbound

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

Multi-Task Consistency-based Detection of Adversarial Attacks Towards deep learning models resistant to adversarial attacks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.986819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4ceeec10-384b-4039-b5eb-a4e198611b4a · outbound

This paper cites Multi-task learning using uncertainty to weigh losses for scene geometry and semantics,.

Multi-Task Consistency-based Detection of Adversarial Attacks Multi-task learning using uncertainty to weigh losses for scene geometry and semantics,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.962912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 382d785c-dd0b-4f2f-9fd2-b1a6ac14ef9d · outbound

This paper cites Multitask learning strengthens adversarial robustness,.

Multi-Task Consistency-based Detection of Adversarial Attacks Multitask learning strengthens adversarial robustness,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.939317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 308e3d12-912b-41aa-8154-75bed8d68b93 · outbound

This paper cites Improved noise and attack robustness for semantic segmentation by using multi-task training with self-supervised depth estimation,.

Multi-Task Consistency-based Detection of Adversarial Attacks Improved noise and attack robustness for semantic segmentation by using multi-task training with self-supervised depth estimation,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.916353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 64f39daf-cfe1-440a-b435-570498d17979 · outbound

This paper cites Defending against adversarial attack towards deep neural networks via collaborative multi-task training,.

Multi-Task Consistency-based Detection of Adversarial Attacks Defending against adversarial attack towards deep neural networks via collaborative multi-task training,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.894686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 16e498d2-772a-4e09-9623-922dbde5135a · outbound

This paper cites Syndistnet: Self-supervised monocular fisheye cam- era distance estimation synergized with semantic segmentation for autonomous driving,.

Multi-Task Consistency-based Detection of Adversarial Attacks Syndistnet: Self-supervised monocular fisheye cam- era distance estimation synergized with semantic segmentation for autonomous driving,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.868634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c7ae92bd-25fc-4025-bbfb-ed1e3f854e60 · outbound

This paper cites Uninet: A unified scene understanding network and exploring multi-task relationships through the lens of adversarial attacks,.

Multi-Task Consistency-based Detection of Adversarial Attacks Uninet: A unified scene understanding network and exploring multi-task relationships through the lens of adversarial attacks,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.838859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 60fb7ebf-21bf-4bfc-a6e1-54ff00990010 · outbound

This paper cites Multitask adversarial attack with dispersion amplification,.

Multi-Task Consistency-based Detection of Adversarial Attacks Multitask adversarial attack with dispersion amplification,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.814206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 156ab7f3-ff29-46f1-b145-e1d484b265f7 · outbound

This paper cites A survey of robust adversarial training in pattern recognition: Fundamental, theory, and methodologies,.

Multi-Task Consistency-based Detection of Adversarial Attacks A survey of robust adversarial training in pattern recognition: Fundamental, theory, and methodologies,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.789103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e5b4426f-c3c7-46f4-8ebb-86e8d48bff5c · outbound

This paper cites Adversarial robustness vs. model compression, or both?.

Multi-Task Consistency-based Detection of Adversarial Attacks Adversarial robustness vs. model compression, or both?

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.766867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c0089b23-ed1c-46c7-ac55-defc94fe05e8 · outbound

This paper cites When nas meets robustness: In search of robust architectures against adversarial attacks,.

Multi-Task Consistency-based Detection of Adversarial Attacks When nas meets robustness: In search of robust architectures against adversarial attacks,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.746783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7a438bde-a83a-4b2e-8cac-38d0a70c1073 · outbound

This paper cites Towards adversarially robust object detection,.

Multi-Task Consistency-based Detection of Adversarial Attacks Towards adversarially robust object detection,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.726116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0997edea-ecd9-4ffa-a900-23af637dc23c · outbound

This paper cites Class-aware robust ad- versarial training for object detection,.

Multi-Task Consistency-based Detection of Adversarial Attacks Class-aware robust ad- versarial training for object detection,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.704251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d24c658e-5fcb-4652-a395-5c8ca08aaa9e · outbound

This paper cites Shapeshifter: Robust physical adversarial attack on faster r-cnn object detector,.

Multi-Task Consistency-based Detection of Adversarial Attacks Shapeshifter: Robust physical adversarial attack on faster r-cnn object detector,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.683686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 69b99916-1d15-447c-a9cc-82427a16567f · outbound

This paper cites As the perturbation strength increases, it results in stronger impact on the target model and causes higher inconsistency between model pairs.

Multi-Task Consistency-based Detection of Adversarial Attacks As the perturbation strength increases, it results in stronger impact on the target model and causes higher inconsistency between model pairs

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:52.663304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.