Paper Citation Record · LEDGER

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach

As of 9 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2505.14531.

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

pith.paper-citation-record.v1
2505.14531 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:37:55.151302Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

39 of 39 outbound references displayed

verified exact0
verified fuzzy26
unresolved12
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e6b03d15-69cd-461d-873e-adb676185b59 · outbound

This paper cites A new backdoor attack in CNNS by training set corruption without label poisoning.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach A new backdoor attack in CNNS by training set corruption without label poisoning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:02.379146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 51f00c75-1e5d-4d42-8765-308e492de4e8 · outbound

This paper cites Deepinspect: A black-box trojan detection and mitigation framework for deep neural networks.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Deepinspect: A black-box trojan detection and mitigation framework for deep neural networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:02.187260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d4cb2ba2-3643-47fa-96b0-f93cc0ed0208 · outbound

This paper cites Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:52.211981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9c7739a-b30f-4e2e-a5cb-d6f2db617629 · outbound

This paper cites Sentinet: Detecting localized universal attacks against deep learning systems.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Sentinet: Detecting localized universal attacks against deep learning systems

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:01.945859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9c9ada43-d922-45d6-be73-c0b4ba526b52 · outbound

This paper cites G., Abbasnejad, E., and Ranasinghe, D.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach G., Abbasnejad, E., and Ranasinghe, D

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:01.740168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation df5fde9f-5262-441b-a0f4-3b2c02bb5f92 · outbound

This paper cites Black-box detection of backdoor attacks with limited information and data.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Black-box detection of backdoor attacks with limited information and data

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:01.582137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cb01f4e3-cd29-43de-8876-de078df08084 · outbound

This paper cites Differential analysis of triggers and benign features for black-box DNN backdoor detection.IEEE Trans.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Differential analysis of triggers and benign features for black-box DNN backdoor detection.IEEE Trans

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:01.416743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d8224b7f-df79-4833-aa5e-2b9b75f1bc92 · outbound

This paper cites C., and Nepal, S.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach C., and Nepal, S

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:01.197974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3a104a68-9a0a-42f2-9894-b994ad61e328 · outbound

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

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:52.922253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bb673fc-fe84-4541-b05e-c7d6b147929c · outbound

This paper cites SCALE-UP: an efficient black-box input-level backdoor detection via analyzing scaled prediction consistency.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach SCALE-UP: an efficient black-box input-level backdoor detection via analyzing scaled prediction consistency

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:01.019558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 748303ec-39ce-4762-884d-bb7a7fa4e280 · outbound

This paper cites SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:53.115468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d31457d-ca1c-45b6-9931-b57d962e2254 · outbound

This paper cites O.The Organization of Behavior: A Neuropsychological Theory.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach O.The Organization of Behavior: A Neuropsychological Theory

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:00.866802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d6b7111f-1f29-4798-b106-7d05a95b1918 · outbound

This paper cites an unresolved cited work.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:38:00.665268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 23f4dee1-0b1f-4db7-976c-e11af0970005 · outbound

This paper cites an unresolved cited work.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:38:00.491247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9d32ecd8-17a6-4109-b7ce-36a279368338 · outbound

This paper cites Detection of traffic signs in real-world images: The german traffic sign detection benchmark.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Detection of traffic signs in real-world images: The german traffic sign detection benchmark

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:00.291872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3e9ec9da-055f-4eb0-88b6-2591d17172f4 · outbound

This paper cites Backdoor defense via decoupling the training process.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Backdoor defense via decoupling the training process

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:00.149603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a64a67b9-1273-459b-9e65-3adf0f45d6af · outbound

This paper cites Beitrag zur theorie des ferro-und paramagnetismus.Zeitschrift für Physik, 31(1): 253–258, 1925.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Beitrag zur theorie des ferro-und paramagnetismus.Zeitschrift für Physik, 31(1): 253–258, 1925

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:59.954847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a7532cb6-21ff-424c-8af4-c00ad1da5993 · outbound

This paper cites Ising ferromagnets and antiferromagnets in an imaginary magnetic field.Physical Review E, 105(5):054112, 2022.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Ising ferromagnets and antiferromagnets in an imaginary magnetic field.Physical Review E, 105(5):054112, 2022

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:59.760072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ea99c7d8-6eeb-4cdb-9b92-bb3e24cd153a · outbound

This paper cites and Hinton, G.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach and Hinton, G

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:53.677198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c6affb8-b389-4481-b621-675fdf855b9d · outbound

This paper cites Baybfed: Bayesian backdoor defense for federated learning.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Baybfed: Bayesian backdoor defense for federated learning

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:59.540548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3db47071-07fa-40f5-83f0-e1b5c47e026b · outbound

This paper cites Gradient-based learning applied to document recognition.Proceedings of the IEEE, 86(11):2278–2324, 1998.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Gradient-based learning applied to document recognition.Proceedings of the IEEE, 86(11):2278–2324, 1998

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:59.346406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2adcdc25-c215-424f-8221-c8b9eea924c0 · outbound

This paper cites and Lin, S.-L.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach and Lin, S.-L

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:59.141144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a74a5b24-c3cf-4c03-9a73-de67c7b1247d · outbound

This paper cites and Yuan, S.-K.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach and Yuan, S.-K

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:58.966139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fae2b70e-4c1d-4161-9d2f-b14ed8d47ffe · outbound

This paper cites Detecting backdoors during the inference stage based on corruption robustness consistency.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Detecting backdoors during the inference stage based on corruption robustness consistency

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:58.753381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b2ed6f59-4f1b-4ff8-9dce-a53079cd5c29 · outbound

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

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach The "beatrix" resurrections: Robust backdoor detection via gram matrices

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:58.564459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1cd9a62c-0df0-4e35-aef9-df7b24d73d7d · outbound

This paper cites an unresolved cited work.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:37:58.465964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 05dec05b-9f1d-4887-a29c-b7d4f467e974 · outbound

This paper cites an unresolved cited work.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:37:58.304713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation aa93670f-9d34-4d50-a487-4e5a6d218676 · outbound

This paper cites an unresolved cited work.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:37:58.123629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fdc9f123-46a2-400b-a75c-2ad326356a34 · outbound

This paper cites D., Rieger, P., Chen, H., Yalame, H., Möllering, H., Fereidooni, H., Marchal, S., Miettinen, M., Mirhoseini, A., Zeitouni, S., Koushanfar, F., Sadeghi, A., and Schneider, T.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach D., Rieger, P., Chen, H., Yalame, H., Möllering, H., Fereidooni, H., Marchal, S., Miettinen, M., Mirhoseini, A., Zeitouni, S., Koushanfar, F., Sadeghi, A., and Schneider, T

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:57.875986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 648371ab-1646-415a-ae4d-bc22b577f57b · outbound

This paper cites A threshold selection method from gray-level histograms.IEEE Transactions on Systems, Man, and Cybernetics, 9(1):62–66, 1979.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach A threshold selection method from gray-level histograms.IEEE Transactions on Systems, Man, and Cybernetics, 9(1):62–66, 1979

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:57.643248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ebc43943-3a80-4b87-90b9-e750eceb7987 · outbound

This paper cites T., Wu, T., Mahloujifar, S., and Mittal, P.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach T., Wu, T., Mahloujifar, S., and Mittal, P

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:57.368777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 91d16cc9-6c73-4409-ad6b-0d551a002adb · outbound

This paper cites P., Kopp, M.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach P., Kopp, M

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:57.115557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 23c90e6a-461b-402e-86be-d19adfef4a52 · outbound

This paper cites Backdoor suppression in neural networks using input fuzzing and majority voting.IEEE Des.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Backdoor suppression in neural networks using input fuzzing and majority voting.IEEE Des

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:56.820787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 87c62a88-82d7-43e6-ad37-f60a06cb7adc · outbound

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

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Demon in the variant: Statistical analysis of dnns for robust backdoor contamination detection

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:56.511162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6a1cc961-3635-4f23-90ef-c6600af99a4a · outbound

This paper cites Spectral signatures in backdoor attacks.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Spectral signatures in backdoor attacks

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:56.170929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1cc02d98-6940-4827-8b5b-74a5f7009088 · outbound

This paper cites an unresolved cited work.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:37:55.890636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2cba6008-4cb1-4895-8938-098b6b53832f · outbound

This paper cites BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:54.876072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ae5fb4f-28a0-44be-8a37-ccb7bb8a8427 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:55.002297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 501d6c92-3305-41bf-a945-02e386bfdb66 · outbound

This paper cites Activation Gradient based Poisoned Sample Detection Against Backdoor Attacks.

SifterNet: A Generalized and Model-Agnostic Trigger Purification Approach Activation Gradient based Poisoned Sample Detection Against Backdoor Attacks

Reference 39

Resolution: malformed identifier; local_arxiv, observed 2026-08-07T15:37:55.500774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.