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Paper Citation Record · LEDGER

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm

As of 13 August 2026, this Paper Citation Record lists 85 of 85 outbound references and 0 inbound Pith citation observations for arXiv:2411.19075.

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

pith.paper-citation-record.v1
2411.19075 v1

Coverage vector

measured 85 of 85 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:39:22.734016Z

measured 85 of 85 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

85 of 85 outbound references displayed

  • verified exact0
  • verified fuzzy62
  • unresolved21
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b9c48c1c-145c-4548-a6dc-008ab9f710cd · outbound

This paper cites Sneaky spikes: Uncovering stealthy backdoor attacks in spiking neural networks with neuromorphic data,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Sneaky spikes: Uncovering stealthy backdoor attacks in spiking neural networks with neuromorphic data,

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.322503Z digest=sha256:ff1c0e072815ae585a762f5121bd2fd38e5ed6bd1030369234020ddcfc63dc44

Observation d158f612-1e8e-4bbe-bf04-369c7cca63fa · outbound

This paper cites Discrete cosine transform,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Discrete cosine transform,

Reference 2

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source=pdf_text observed=2026-08-12T10:39:22.328062Z digest=sha256:e21bc2ca2fe0dd24e49404cbcf3a7b1539543b7c084ec1ce9f4a12757d95a0e0

Observation 56ef9456-9196-4bf5-8d07-c71d3a82f818 · outbound

This paper cites Backpropagation and stochastic gradient descent method,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Backpropagation and stochastic gradient descent method,

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.333747Z digest=sha256:ca2174a7e6695450860e868e8651bd3acb6d03f256fad9d2a9497c36fb5afb77

Observation ae66f31c-027d-4226-8696-9b9072dcba5d · outbound

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

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm A new backdoor attack in cnns by training set corruption without label poisoning,

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.339235Z digest=sha256:cdf9b4d736c35f0c8111a0071f518dcd79fa904a1ff583c06b3b7d67512b7fcf

Observation 5195d491-93f5-4a99-89bb-282abb119be8 · outbound

This paper cites End to End Learning for Self-Driving Cars.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm End to End Learning for Self-Driving Cars

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.344173Z digest=sha256:437f153267e80e867a49e0c601b5686f387a9cfd04cfc4a6c6b31b7663df96c8

Observation 3f7b2314-93eb-4619-864f-8ca2be8739a5 · outbound

This paper cites Color and spatial structure in natural scenes,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Color and spatial structure in natural scenes,

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.348972Z digest=sha256:c9916818927e68bc67fb5415ac20099a68b7071a55c4178901e00b8fc840ccde

Observation 4ede1510-bfb8-4c13-bef6-4f0d666db9bd · outbound

This paper cites Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.353968Z digest=sha256:c41ffe9e8df41b3400ff0f88d15d4a8a4721dcc1b953bf046f9de8fb5308e57b

Observation 90b3ba8f-38fc-482d-9996-e4f0f773a86d · outbound

This paper cites Deepin- spect: A black-box trojan detection and mitigation frame- work for deep neural networks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Deepin- spect: A black-box trojan detection and mitigation frame- work for deep neural networks,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.358503Z digest=sha256:5de307129a8bd272f7c4f7874be6efea04b59365de252b27f1e75f54f49b6b62

Observation 66f5e49a-5d61-4e6d-993f-5b36a706980d · outbound

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

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.362768Z digest=sha256:d0563a29380e4c8c8c8f739f06bc3552635cd598be7cc490d0897957fdd72167

Observation 61971897-25fb-48f6-809a-edbad378c5b1 · outbound

This paper cites Deep feature space trojan attack of neural networks by controlled detoxification,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Deep feature space trojan attack of neural networks by controlled detoxification,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.368713Z digest=sha256:a29a812db161aceba32a2e7eb04146630e9064452a092fe66284d3158a1f5896

Observation c55d93f4-fbdc-46ba-b3c4-bfdb70f26d02 · outbound

This paper cites Secure spread spectrum watermarking for multimedia,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Secure spread spectrum watermarking for multimedia,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.373357Z digest=sha256:550ef5e584fcad4bf1c3c4d5f4794e58e32e60d1f1da3cc2f024e008875a0a11

Observation 209555cc-a8d2-4ef2-83cb-25844c839513 · outbound

This paper cites A fast and elitist multiobjective genetic algorithm: Nsga-ii,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm A fast and elitist multiobjective genetic algorithm: Nsga-ii,

Reference 12

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raw_fallback, observed 2026-08-12T10:39:23.989914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.378687Z digest=sha256:9482626f83094c3c2c8d48fa0781e1c2d71dd04159c5826d0566a82502d94099

Observation 21ef826e-1a72-48fd-ad23-6b34496b1d88 · outbound

This paper cites Simulated binary crossover for continuous search space,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Simulated binary crossover for continuous search space,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.383725Z digest=sha256:6f4b05648f0d1fee2ed5bef89af55d83d285eb2cd4ff163dc8d92274186e69b3

Observation a3ea97dc-c855-4807-a627-707591ba17d2 · outbound

This paper cites A combined genetic adaptive search (geneas) for engineering design,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm A combined genetic adaptive search (geneas) for engineering design,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.389502Z digest=sha256:e5895e2136f1490128808fe091afa113ad1114291ff0fab9bbcc0a326cf3c38b

Observation 7c939360-f5f0-48cc-9705-611ac41e9d95 · outbound

This paper cites Backdoor attack with imperceptible input and latent modification,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Backdoor attack with imperceptible input and latent modification,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.394477Z digest=sha256:d351e07e8a7528080a0c5b285093f8823c9d484199e7a13ae4aaa80845ce73db

Observation 8bd3acaf-4a50-447e-bd2c-aa711d592871 · outbound

This paper cites Lira: Learnable, imperceptible and robust backdoor attacks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Lira: Learnable, imperceptible and robust backdoor attacks,

Reference 16

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raw_fallback, observed 2026-08-12T10:39:23.922894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.399700Z digest=sha256:a47acde9b45ab266af50505303f470c0812bf6265751446dc413cb29aabb4387

Observation bcb26def-1f12-4270-9a79-72260268bcde · outbound

This paper cites Marksman backdoor: Backdoor attacks with arbitrary target class,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Marksman backdoor: Backdoor attacks with arbitrary target class,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.404425Z digest=sha256:e3267dc437505b666fa00bd71ec94c2eb22076fe4f51fab14f9edb81d6c7a3f5

Observation 77d26c29-489c-459d-af3f-cd9e88b5698c · outbound

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

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.409418Z digest=sha256:1d4f247ff0b60c2e7eba9d54a4a8d98d15b4624410990853f80590729dbbda44

Observation 4f9df884-cd52-4196-9822-e51ac0b3bf48 · outbound

This paper cites Dermatologist-level classifi- cation of skin cancer with deep neural networks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Dermatologist-level classifi- cation of skin cancer with deep neural networks,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.414463Z digest=sha256:f5206c66593627d74004050be902a0f4a1bd0d0afa9ee60c3fab503c46c23291

Observation e4cc9541-35b4-4fda-9df2-65a8e5b8a48b · outbound

This paper cites Fiba: Frequency-injection based backdoor attack in med- ical image analysis,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Fiba: Frequency-injection based backdoor attack in med- ical image analysis,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.419517Z digest=sha256:468a1f1d33af1e1946700e7ae447bae339d72c18fabded64dab4f595e7217b36

Observation a885f010-2f75-411e-9c13-f4e3bc80b0bf · outbound

This paper cites Backdoor defense via adaptively splitting poisoned dataset,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Backdoor defense via adaptively splitting poisoned dataset,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.425315Z digest=sha256:1cb0321b09bab0f8e5f95913ad5954e1772f5bd36e16cfbbe0eb9c0bf165b980

Observation f339cd8e-a6e5-4460-844e-8cae8900543c · outbound

This paper cites Strip: A defence against trojan attacks on deep neural networks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Strip: A defence against trojan attacks on deep neural networks,

Reference 22

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.430126Z digest=sha256:d85e48bb21485b5ef1edd6150b2930ab651ab88df83752c348b5d6733688b9e3

Observation ed591b3e-a1a1-462e-a8a4-0e1ed710826b · outbound

This paper cites A dual stealthy backdoor: From both spatial and frequency perspectives,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm A dual stealthy backdoor: From both spatial and frequency perspectives,

Reference 23

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raw_fallback, observed 2026-08-12T10:39:23.812710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.434949Z digest=sha256:d9c57d78a1618e40c26b934a00e1d10bde3082220b7099936b4138f137571db8

Observation 8b7a5d5f-1803-455e-8544-effc77bf064f · outbound

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

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.439689Z digest=sha256:ba0d0b8626cdd1cee7673334c423d367c65a1cbc3761f93e35063a514a224c95

Observation 352244b1-1ea4-4985-9c78-e5fa35ac94fb · outbound

This paper cites Low frequency adversarial perturbation,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Low frequency adversarial perturbation,

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.444739Z digest=sha256:d63267aa0883d948221436c424a3088abd8be2826ed185fcaa6cf3241af3fe22

Observation f50e3bd8-c316-4832-b1f6-0145faf44589 · outbound

This paper cites Check Your Other Door! Creating Backdoor Attacks in the Frequency Domain.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Check Your Other Door! Creating Backdoor Attacks in the Frequency Domain

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.449073Z digest=sha256:ddbc58fd4aca3e1079e8027b6739dd18de728a0088c4dc3508d13eb74f49c9f2

Observation d30c3314-7cf5-45c0-8ab6-530f1a6a6dfd · outbound

This paper cites Deep residual learning for image recognition,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Deep residual learning for image recognition,

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.453843Z digest=sha256:18d28a8a7e1605347d274c1e39861019364a206c1f5205854bb7c23e6607af62

Observation 4e579c23-9a4a-49a2-b91e-9fa77e152c26 · outbound

This paper cites A stealthy and robust backdoor attack via frequency domain transform,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm A stealthy and robust backdoor attack via frequency domain transform,

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.768685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.458413Z digest=sha256:001f192808d1f9644901fc0ee41809dbbf130a207bf63f0f4079675102a97ee8

Observation 399eead4-2c08-4962-80cf-19465a6940a1 · outbound

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

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Detection of traffic signs in real-world images: The german traffic sign detection benchmark,

Reference 29

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raw_fallback, observed 2026-08-12T10:39:23.752911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.462764Z digest=sha256:891dc1e0b40baa6c5a683288fdd1148be2514dd9caac52694cdb2c0d60b3f2dc

Observation 0f0b3e24-8b83-4ce4-b390-d6e180c9927f · outbound

This paper cites Backdoor defense via decoupling the training process,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Backdoor defense via decoupling the training process,

Reference 30

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raw_fallback, observed 2026-08-12T10:39:23.736259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.467479Z digest=sha256:15042b31747c414ac7677bcd0a10eba74eaa3bf8a358af2f4f465372d95116de

Observation 63bca9ea-c245-4df8-911f-627fda841a6b · outbound

This paper cites J ¨ahne, Digital Image Processing.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm J ¨ahne, Digital Image Processing

Reference 31

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raw_fallback, observed 2026-08-12T10:39:23.717598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.472758Z digest=sha256:954ab2849ebf2487977012f92ec2692056ff10dc6a194e41f961495ed962821c

Observation 324497c1-3179-4477-bd30-98fc8f9a446e · outbound

This paper cites Color backdoor: A robust poisoning attack in color space,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Color backdoor: A robust poisoning attack in color space,

Reference 32

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raw_fallback, observed 2026-08-12T10:39:23.701295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.477384Z digest=sha256:78f134e9bf1cdc0f3ec0a4c13ce67a58ce7e1c42057e7a6602a44942df015bf4

Observation 99cccb6c-d4bf-4671-908e-42127583caa6 · outbound

This paper cites Fisher information guided purification against backdoor attacks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Fisher information guided purification against backdoor attacks,

Reference 33

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raw_fallback, observed 2026-08-12T10:39:23.684665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.482063Z digest=sha256:b936a162383d228b0677fad5b9946ebb745ad6768d5789458adaf016f9462dde

Observation ded3140a-b42a-44b7-b559-ba66169188a5 · outbound

This paper cites Dual-domain image de- noising,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Dual-domain image de- noising,

Reference 34

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raw_fallback, observed 2026-08-12T10:39:23.669336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.486600Z digest=sha256:a11817029654f26c7f24be215a68be67350973810c3c7d46cd254e18dc3819cb

Observation 3ab1c5fa-e59f-4e35-ac7b-f6fbbf62be8d · outbound

This paper cites Universal litmus patterns: Revealing backdoor attacks in cnns,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Universal litmus patterns: Revealing backdoor attacks in cnns,

Reference 35

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raw_fallback, observed 2026-08-12T10:39:23.653048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.491729Z digest=sha256:82dcf7f8fafbdfd36ad2deb3b022d533fa0e9a4aa26cb735179e295fb02e9719

Observation f2d2b9b0-b4ae-4cab-9eaa-56e4c607003e · outbound

This paper cites Learning multiple layers of features from tiny images,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Learning multiple layers of features from tiny images,

Reference 36

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unresolved
no resolver link, observed 2026-08-12T10:39:22.496895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.496895Z digest=sha256:df026cf71f3e62991d6fc71f4172bd9d7e16dd6a6023f5a58ed5b5637f27809b

Observation de7da43c-13b9-4512-b25e-4f0428ab064e · outbound

This paper cites Flow- mur: A stealthy and practical audio backdoor attack with limited knowledge,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Flow- mur: A stealthy and practical audio backdoor attack with limited knowledge,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.625532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.501770Z digest=sha256:506adefac0afea6a0d9997166d4803f5310ec471259bd7194d2d37b7bf89fc06

Observation 0d302eea-9310-49fc-afda-8b92fc8de63c · outbound

This paper cites Tiny imagenet visual recognition challenge,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Tiny imagenet visual recognition challenge,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-12T10:39:22.506655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.506655Z digest=sha256:db7530892f52ce0b95c57f95786140fc7512e158d0ede4057b4ab4128df97247

Observation fbc1a712-6fc3-47fc-bafc-8580bfd59d60 · outbound

This paper cites A theoretical analysis of backdoor poisoning attacks in convolutional neural networks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm A theoretical analysis of backdoor poisoning attacks in convolutional neural networks,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.596780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.511974Z digest=sha256:9a08f53f0f211cb69da3b0c8898e63e53e6f755deb4ca1e35f79bca11a68c19d

Observation 547fe407-0ecf-41d5-98a7-a8646c1843d8 · outbound

This paper cites Invisible backdoor attacks on deep neural networks via steganography and regularization,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Invisible backdoor attacks on deep neural networks via steganography and regularization,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.579976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.516630Z digest=sha256:8e3c6382c98d998a2b499658c194c9ac96a390c10a29027b9072b46c5298a5c7

Observation 00062c7e-7784-4fad-aac8-4cac60b21318 · outbound

This paper cites Neural attention distillation: Erasing backdoor triggers from deep neural networks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Neural attention distillation: Erasing backdoor triggers from deep neural networks,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.563626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.521561Z digest=sha256:480ad1efd9959532fd17b2a747dffedf665ff59622fa60fe555ff368d6966bc4

Observation 96380ba2-2488-4f99-90a9-64c5b958c044 · outbound

This paper cites Rethinking the Trigger of Backdoor Attack.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Rethinking the Trigger of Backdoor Attack

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-12T10:39:22.526785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.526785Z digest=sha256:b5642eb016b9ad4f201697e4667e13af59e0077ae24079d2aabeee37498cd520

Observation 00e80af7-8e1c-4c02-8e6d-bb211350a056 · outbound

This paper cites Invisible backdoor attack with sample-specific triggers,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Invisible backdoor attack with sample-specific triggers,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.547493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.532096Z digest=sha256:7c7f138f7d7eb6e549c8538d3fdcfb2ea61ea1ae5f15d44ccb2eb70061c4b0e0

Observation 65e1eceb-101c-4ee6-a5ae-4e4414ba206f · outbound

This paper cites Fine-pruning: Defending against backdooring attacks on deep neural networks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Fine-pruning: Defending against backdooring attacks on deep neural networks,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.532465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.536968Z digest=sha256:5d8145b0797e4b6ea605aa869918013381e3b5181bfa823197e91f49d53a3c51

Observation 6009df7d-dedb-4bee-b147-4a05e66c9e07 · outbound

This paper cites Reflection backdoor: A natural backdoor attack on deep neural networks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Reflection backdoor: A natural backdoor attack on deep neural networks,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.516668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.541701Z digest=sha256:c51aab3b06708eec40183adf63b378d10953079d5c1631378b71df02b3610edd

Observation 6bf725d6-feff-4817-bf26-2caaf74f46af · outbound

This paper cites Deep learn- ing face attributes in the wild,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Deep learn- ing face attributes in the wild,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.499851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.545793Z digest=sha256:8d514d284f2fc294259730c7b61ad6d87acafea82127d6dec4400b3073443a92

Observation 23005fdb-ad56-473f-99d4-c2d2e58c44b8 · outbound

This paper cites A data-free backdoor injection approach in neural networks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm A data-free backdoor injection approach in neural networks,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.484154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.549967Z digest=sha256:d4ce641f9933d4345ddee9c1334369eb0d1e8e8fbfa8e8a0af1cf0cd767f4751

Observation d9feb452-a77a-4a3d-a599-67a08f318678 · outbound

This paper cites Watch out! simple horizontal class backdoor can trivially evade defense,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Watch out! simple horizontal class backdoor can trivially evade defense,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.467961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.554252Z digest=sha256:5b04b9c50629d67df375c833772fcf7fe0a300f30993c0796a9097d69ddb604b

Observation 003e466b-151f-4ebb-91fc-326c7345ab0a · outbound

This paper cites Reading digits in natural images with unsupervised feature learning,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Reading digits in natural images with unsupervised feature learning,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.451856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.559014Z digest=sha256:1b39d630ee18d88b3312d39b2d75a01c075f9b817e719057411fed30ec2e733a

Observation 16d8c29d-fdaf-43a8-861d-a9d8eff141c8 · outbound

This paper cites Input-aware dynamic back- door attack,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Input-aware dynamic back- door attack,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.436337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.563908Z digest=sha256:0563cdd71d3f18d4b3716ddd48f12daf4e939dfae9b0c2d73e1634e8bbbf3791

Observation 5ededc13-b74c-4602-b072-5b53d9a38a62 · outbound

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

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Wanet - imperceptible warping-based backdoor attack,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.421421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.568542Z digest=sha256:d4bb59dee14539c34f84c1a93405570aa0ce9718d0581c0b40053205a6d1902a

Observation 50c6fa00-7d45-4eff-ba58-34a3069b0a06 · outbound

This paper cites An Introduction to Convolutional Neural Networks.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm An Introduction to Convolutional Neural Networks

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-12T10:39:22.574325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.574325Z digest=sha256:c43e68ff19ebfc8f48e8fda7c0bc3341ce5076a724b029784859f5817cd22680

Observation b58857fb-ad29-467a-b558-0610daf9e8af · outbound

This paper cites Pytorch: An imperative style, high- performance deep learning library,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Pytorch: An imperative style, high- performance deep learning library,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.406365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.580178Z digest=sha256:952f7f4309a4d796e8b64967e0b9b8bed204cc442959ee1d677ccffe44cde519

Observation 9bd13f37-8bb9-4e08-86ce-16be319b66d5 · outbound

This paper cites Defending neural back- doors via generative distribution modeling,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Defending neural back- doors via generative distribution modeling,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.390737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.584746Z digest=sha256:23e71768ac72700b67ce3eab74429dee22dd90073687ce4dc796b6c03b705448

Observation 9057ae96-3cc8-4379-b672-58fd8d89ce58 · outbound

This paper cites Deepsweep: An evaluation framework for mitigating dnn backdoor attacks using data augmenta- tion,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Deepsweep: An evaluation framework for mitigating dnn backdoor attacks using data augmenta- tion,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.375062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.589486Z digest=sha256:630301b773b2631227f1883bed6082e88436c80c74b72a0f23a8ab65c8450722

Observation e3bcd350-3222-4f50-b92e-e0f5f379a30e · outbound

This paper cites Belt: Old-school backdoor attacks can evade the state-of-the- art defense with backdoor exclusivity lifting,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Belt: Old-school backdoor attacks can evade the state-of-the- art defense with backdoor exclusivity lifting,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.359203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.594292Z digest=sha256:f6e18ee32b018679a7bddf54e04e8a7dbf5f7246c120cfd721d870c95e398674

Observation 31dd24a0-3d19-41c7-9067-47ccf23a62eb · outbound

This paper cites Hidden trigger backdoor attacks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Hidden trigger backdoor attacks,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.342746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.599715Z digest=sha256:d5a6c404dabf0b5ead22b8b74a6156e893f5370edb11daa9402ca1dae3864daa

Observation 3d8eed3e-50fe-452d-ac03-a1a74741e9fa · outbound

This paper cites Dynamic backdoor attacks against machine learning models,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Dynamic backdoor attacks against machine learning models,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.327173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.604455Z digest=sha256:c728bd3bd57ab39d77cccebf213a5eb82aebdcd23270f8927d719a8cbbbbc7f6

Observation dcd4c87e-0d62-4b59-967a-d4c1355c9c2e · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.311476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.609273Z digest=sha256:25364ad67487b1a65ef65a39b081fcf08682feff18464bee29f16ba30dccd8dd

Observation ed569b6d-9f71-44f0-bd85-ba6472c1a7fd · outbound

This paper cites On the effectiveness of low frequency perturbations,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm On the effectiveness of low frequency perturbations,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.296849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.614431Z digest=sha256:bc4e270872785a8a91ddad3823221c7c372e1df1d340a91c1b306fe9ffbf771c

Observation e3bb7813-0372-406d-b777-ff41f833d0a5 · outbound

This paper cites Black-box backdoor defense via zero-shot image purifi- 15 cation,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Black-box backdoor defense via zero-shot image purifi- 15 cation,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.282317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.619242Z digest=sha256:19a989e6ca51b558d748970d80d8ff9881365accdeebb07b19bf6c7465b4ca98

Observation 0d885779-0a19-44e3-a277-9e931a5717d1 · outbound

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

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Very deep convolutional networks for large-scale image recognition,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.265552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.623927Z digest=sha256:2b5e1b8fc53c46158bbb25fb7f64aa26a6bfd6b03715985044de193676e10a30

Observation c0c062ba-09a8-49f9-8546-4091f961b7bf · outbound

This paper cites Going deeper with convolutions,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Going deeper with convolutions,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.248999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.628032Z digest=sha256:4c61154e9c5ce8df5eb85cfd291cc257fa6886d761d3377eba32aa6e34ec97b0

Observation abdcc7d4-9324-4d87-9324-775a09174c79 · outbound

This paper cites Bypassing backdoor de- tection algorithms in deep learning,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Bypassing backdoor de- tection algorithms in deep learning,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.231946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.632034Z digest=sha256:5256cbe4a40a9c0d3697a58caa6d391f7dc04f7b048f69f12d32c94ce202a48d

Observation dec83c56-bf94-4c31-a6ea-8d3289dcb867 · outbound

This paper cites Model orthogonalization: Class distance hardening in neural networks for better security,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Model orthogonalization: Class distance hardening in neural networks for better security,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.216063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.636126Z digest=sha256:4f188aa0f9bf3de37242341a14a608ce9fd0d263b92acb0a94df0a9c8ff4da1a

Observation 099b0192-6858-4465-a5a4-670f4aa6c701 · outbound

This paper cites Amplitude spectra of natural images,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Amplitude spectra of natural images,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.200236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.640380Z digest=sha256:9c6d169072f73cd4c4d0b2a20cfcbf80dc5f92c16b53d83e1b6616f397c21ce2

Observation 33af07f7-6616-4332-8b0b-350ff5b9e948 · outbound

This paper cites Spectral signatures in backdoor attacks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Spectral signatures in backdoor attacks,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.185320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.645197Z digest=sha256:39091536c327629274c35a8225aa12bbedd0e44bd0444fa90cb59fcdb75dca57

Observation a30149db-2509-4839-a111-e31e88dc2b53 · outbound

This paper cites Neural cleanse: Identifying and mit- igating backdoor attacks in neural networks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Neural cleanse: Identifying and mit- igating backdoor attacks in neural networks,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.169283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.650538Z digest=sha256:c646ca541232cf33dab6dc244a81690224afd1cb125d38accbb9064cb3e4b34b

Observation 3e3e540e-a4d6-497b-985f-87836b211d7c · outbound

This paper cites MM- BD: Post-Training Detection of Backdoor Attacks with Arbitrary Backdoor Pattern Types Using a Maximum Margin Statistic,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm MM- BD: Post-Training Detection of Backdoor Attacks with Arbitrary Backdoor Pattern Types Using a Maximum Margin Statistic,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.151252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.656192Z digest=sha256:9a3b196b3d94f18e9758c6b3b55ebbe738c1d63188093c88e9229f3c0fdc7dbc

Observation f238d8e2-3661-4402-b6a2-1ad57b0e2bad · outbound

This paper cites Versatile Backdoor Attack with Visible, Semantic, Sample-Specific, and Compatible Triggers.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Versatile Backdoor Attack with Visible, Semantic, Sample-Specific, and Compatible Triggers

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-12T10:39:22.661197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.661197Z digest=sha256:0c8c3e5872a41403610c9392bc50494394bd09458723bb446ea56378c8d8fcff

Observation 8b73a7c0-5ccb-41b7-957e-bda918a1291a · outbound

This paper cites An invisible black-box backdoor attack through frequency domain,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm An invisible black-box backdoor attack through frequency domain,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.134174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.666086Z digest=sha256:621e36885049ba8ccdb8e8f3344e33b39f112a056351515e70fe566f3f4ac481

Observation 15bcba9f-c257-4cec-a1f9-57a3fdbb018a · outbound

This paper cites D3: Deep dual-domain based fast restora- tion of jpeg-compressed images,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm D3: Deep dual-domain based fast restora- tion of jpeg-compressed images,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.117691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.670921Z digest=sha256:d6899608716f86618dd3d9ecb469986df17b86e652fd8bcc11ef0c40841e7864

Observation 3981d7a3-22c4-4f39-8311-304477f1991e · outbound

This paper cites Latent backdoor attacks on deep neural networks,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Latent backdoor attacks on deep neural networks,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.101338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.675843Z digest=sha256:d811a3a6983bfd9f40b12dbdc98b1edbdee7f9ec2fa3a166764a1259904ff64e

Observation 492fdd91-9f0d-4f56-a979-3ff5046bd901 · outbound

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

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Narcissus: A practical clean-label backdoor attack with limited information,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.085023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.680652Z digest=sha256:f4589a6349fd1fed74ddf130104cf878da051790c7b142f26303dd40c28950a2

Observation cd167b17-8eca-430b-8283-3b1a2167ce86 · outbound

This paper cites Rethinking the backdoor attacks’ triggers: A frequency perspective,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Rethinking the backdoor attacks’ triggers: A frequency perspective,

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-12T10:39:22.685303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.685303Z digest=sha256:443db83b8a4850c922a13569cae4c7cc465d86d0d42b0ba514b0f3a0e7d3917a

Observation 08826ee9-99cf-46c8-a77b-ff8c5375da18 · outbound

This paper cites BadMerging: Backdoor Attacks Against Model Merging.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm BadMerging: Backdoor Attacks Against Model Merging

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-12T10:39:22.690265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.690265Z digest=sha256:cbefae3ef7fe8c8a7587c1432209d6f59f2798a4a4d07018cc1e6e1b2fbf34ac

Observation f62c7a7f-401b-4be3-9f2b-511120b56691 · outbound

This paper cites The unreasonable effectiveness of deep fea- tures as a perceptual metric,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm The unreasonable effectiveness of deep fea- tures as a perceptual metric,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.056267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.695197Z digest=sha256:6e3911076c69fc8003fcfd2d64595d27e8d6e8edfbfc4c104d478ffb3e323e06

Observation 26cd11dc-2b8f-41e8-b231-35aa549c754e · outbound

This paper cites Shufflenet: An extremely efficient convolutional neural network for mobile devices,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Shufflenet: An extremely efficient convolutional neural network for mobile devices,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.039628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.699898Z digest=sha256:bd4614f88e790690706d693955efc855774772dabe6cc17cc912a478f33d7360

Observation b09c203e-e5e8-483c-94bb-b7782b705a1b · outbound

This paper cites Backdoor defense via deconfounded representation learning,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Backdoor defense via deconfounded representation learning,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:23.023610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.704433Z digest=sha256:ff3edce3c0ac5cffabe63321c59f8ae0e16f3db6616787b1f6d3f5cabdc12ab9

Observation 297f7fcd-a59c-494f-b065-652ae58cc235 · outbound

This paper cites Defeat: Deep hidden feature backdoor attacks by imperceptible perturbation and latent representation constraints,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Defeat: Deep hidden feature backdoor attacks by imperceptible perturbation and latent representation constraints,

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-12T10:39:22.709015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:39:22.709015Z digest=sha256:e858cebb1c893bf169ae220a4e386fd3881365954b4db0f03c6ea2c2ff0742d5

Observation 3507472b-9652-4477-8df1-7c770416f81c · outbound

This paper cites Imperceptible back- door attack: From input space to feature representation,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Imperceptible back- door attack: From input space to feature representation,

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:22.993974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.713900Z digest=sha256:71fea2a44d51b1c20f1d140a970b01c0d0ea8dcef1025404c251073c44a1ad3c

Observation b24ba50e-c45a-4023-b93a-eb498b35d3a1 · outbound

This paper cites Neural polarizer: A lightweight and effective backdoor defense via purifying poisoned features,.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Neural polarizer: A lightweight and effective backdoor defense via purifying poisoned features,

Reference 82

Resolution
malformed identifier
raw_fallback, observed 2026-08-12T10:39:22.976267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.719353Z digest=sha256:7475144e9a5f065a8a5b13686c691ea878bec0c20926c6e0b8c8e1c52ce610aa

Observation 505d9e6a-d8de-4b30-8244-df97051ba2a5 · outbound

This paper cites ASD adaptively splits clean from the poisoned dataset during training so as to defend backdoors.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm ASD adaptively splits clean from the poisoned dataset during training so as to defend backdoors

Reference 83

Resolution
malformed identifier
raw_fallback, observed 2026-08-12T10:39:22.958720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.723820Z digest=sha256:ae26377cf9a45a7dca422f52c1075b0786100f243a0089ff2e7c69f997aa6747

Observation 24aa86b0-8bca-46c8-b438-6f8b779168be · outbound

This paper cites an unresolved cited work.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm Unresolved cited work

Reference 84

Resolution
unresolved
raw_fallback, observed 2026-08-12T10:39:22.942241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.729034Z digest=sha256:7fff65242c9d34a0ff3817baf7fa7e4073a6b6249eabb5f141037e633b85cb8a

Observation 8694ca4f-c451-447c-9646-ffc2dd175dcc · outbound

This paper cites They cannot be trivially extended to produce dual-domain stealthy triggers.

LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm They cannot be trivially extended to produce dual-domain stealthy triggers

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:39:22.925954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:39:22.734016Z digest=sha256:7485414c32d516bf7e65bd6684ef66701c16828f2ccdf8e86bf4c99abd711e80

Pith citing papers

No inbound Pith citation observations are available.