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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=sha256:4f29290472c5abe7f22c09d4d6c58beae8e0e508d6c7fffa1801d53df2bcc864

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=sha256:28b4528fd3bdd3390d42af423c7eb1e9c35a4c671504c14f8f8a5f513e68c024

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=pdf_text observed=2026-08-12T10:39:22.333747Z digest=sha256:995aa4f281937a2ed5aaa175c271e1338cb2d32646ce6aec785c236af50e9b01

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:fed8c690b3e0052d8a0b1c1d176c9f62adecb3106d9c11d1700b2099b6838b53

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=sha256:412e74d14606f9b14d1f993876c464c2d64bae0b3ed94b6d8f57668de4d18555

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=sha256:3de970705a6600a8e2981579bc12107c7f7f0681564ef4d5a3bcba6f5764a378

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=sha256:722f8ba5971427ffd3a1331acfce60cf051cbfad8ec297c000ed969c06be75a6

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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raw_fallback, observed 2026-08-12T10:39:24.040648Z

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:c541f6d299d173ecfd18e69f36510f593656cb2a607031b8d2ab631392eaec5d

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=sha256:0c67d2bb967cae69ee6d5efb153500133d538b5ad1329793d04128c12d96eeb2

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=sha256:0b2993d5b3b14b3df617fc79acc56a59fa6831269699e4b586da96368fbe0b30

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:e5df8a35c6c185572732cfaa54488895fca77c55eb489f7c32320efadd7955a2

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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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:cc0256972e543239f30438f26f7d8fd7a6325827d1372fe28ce4e431b8f2ea76

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:bfba8c2285962a52a1421d87819014448632b21f8eb4cb735d9a3e7bdac76fe3

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=sha256:06a900346604df52e79292d42b16185706420b21c34ebf3e771ed8b3343fcf6c

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=sha256:6a3fdb6f10033a5f4f300d8b207fc1a6f5d6ff211d26482bde2be31ab4fde0f1

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=sha256:719b8257078b1cda0bdf8fc73cce74cb8f6f408ea809ab08b7e085a4d7b27fb9

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=sha256:2014b3204a00f372f8e485cff4bf5303964a284d8b4e1629cb3ce1ed89a2fd98

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:f643434aedf7e41a1ea7c4bfed06f2bf8a08bbe29e2b413a9195c5d22bb64910

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:bf1912d69fe669ff0242a6272508bba68020bdce0d394ad67f6011f00c41d1a0

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=sha256:645a2dbc49adae10959164b480b627cc5ad7d060f4250cc66c14e79275332634

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:f6fa799cbc23044825dc670261ed8753b02a0e228974fda647b9aa6d99a68c70

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=sha256:8311fca2a1487d955d1473430848cd2e9697f1a8bf926d385460a93feb31484e

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=sha256:0faa20604c4124cee81b444a015623228eb9d2da205a39565b0278a2b4408630

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=sha256:5bd5cb3444175a0c1edfce48d9af994c71280e793e32af5802cd4ecab83d7d62

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:bb7bb089b46ea76002351c95265abaa2fb855ba6dfe903a2fa229613d762e556

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:a16bbb2ddcde86ec28a94b5cb33cc09c5771731c1da13553404f00b4023a1ff2

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=sha256:5d5ff85df0bbde701bd7978dbc7dd603f0d966203ee43d950bceb1265249b908

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

Resolution
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:eaddbbf8201e5ff86662cf15bd7fda5af6582a5b33289a15e70c55072e8d8fca

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=sha256:4b60098a394acb5dcc0c76e228b73bd84e39870c67576b037b232e6110b16d3b

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

Resolution
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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=sha256:862d768f7584048d7b83a567cc96b023a54549fe6c623c4414716c3f61a7b110

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:e635f5868b1eae2d23f3b3af8910529360385b99f8f81c9d641f8292fcfcdc79

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=sha256:048e3c69f59760c436e63881f5e7258bd16fd91f3e2e7ca6e7e61d5003321ea2

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:a5a07ecc81e0ebf784447e422fa7a93362da2d2870742a5909bd4cbd030fd1c8

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=sha256:5e2cf34a0216f5e9fe72aec015d4d2b949a79113e99ce2d47cd0b98fae96cabb

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=sha256:13b1bae1987349a93679b60b0d517fa0f9db55447503308b2b2513eac2d589d2

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

Resolution
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:d033bc0301ab2193009d8f27c3e6fe33a63d86b7545951d75d8084fd443a9d7d

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:b7d74303b8baa10ce74f00c97ce96ef4664e644d457e2bf2cbf990704d627555

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:f9763435b42fced7b208745fa72d4e2909dad4fd09d6140bdb02f61bf0bf1465

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=sha256:2b6166354a17330f9a1767815b38fee0bb90aaa4e89285e5b7b72bd22ef514cd

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:ff5c433dec5715a49c30c2a46bc5e32e7d2f7f69c53700814ea3dcbd54d9bece

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:f1a89587bf6a1fd137cf664633b700e249f1dada2959d51086d07f5b217f17f8

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:a4f010c95a5820eb23016bc1bc24b9f4a7b3862217a9716e6ee4551d519e919b

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=sha256:236bd125029624dc94f9937253626ba7667524d0cb843d6857b0afe342fe2796

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=sha256:965b10e111e010ce9b01a8a10c2d840f07dbedfd5e51f51b132c8f5a6d20ae6c

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=sha256:0543fa6fb0d90b7ad7618a83dbfa7894c28bdf3b4472f08f0ee844a558df4492

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=sha256:881be281f46ffc4daa48c69167942104ad8f59a769a016dd32fd0dd671830dae

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=sha256:1c171b3c18ee3479af6befc2ba1a4debf04fc004dd147d9ae234f0f37da5124a

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:d5f5a05372904028ca4cbb206322750e95c112f286bd051a33c785482195cc0a

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:f5c6c08cf151347bde8e87534140f4931419f1a9bf83b3efeaf45c94a423a511

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=sha256:55e5fcdf30073818382f87e18515e2cb5d6a64b7ce3c82ae3e98eabcdf51549c

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:f7b32c125a6ed67dc00ac397f349d284c0bccdf2a01104a44e454488b7fba1f3

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=sha256:8c74ed235524c626c20ea4c5d77c92bde33b6f5babeab9e4dbe259c48f67a033

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:c5b15a9a5f9572cdb2aa07c3a3e53e6f305997c396021d2af07022b76817bfe5

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=sha256:8a0eb2f497ba7471b036b993c922bcabaff0b4ff24218964767e2a2f5b275377

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=sha256:4335b787e8f6d27893443bedecf40fab075f8cbcabdb23f13abc40d22bd8ca8f

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=sha256:85766f4a43d492809fb7ad52ee83a25f13d1321ccebaaf896c0bf6af42473943

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=sha256:14bae14ed48ce50e4b7d3812f2b148f897f65f2ab974488c42b052234bf9e67b

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=sha256:53f0471038a009bc86093bd8252315fa23c28b7f3660664cbe9e11f9d215cc87

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=sha256:2832e7d209685119f89a06f4a1c66ca2d7f19c0fd0c8c66547fb24c28ac09a36

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=sha256:6d2561a0feeeb56520a1adfaf572ddfb7436eaa5155588dd262ea6dfddd64e65

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:f1b5f3d1e187c6063ee470c734bea41e654bec9623359f73e81257f00d912296

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=sha256:84c1b2c9529ceb6c2ec61ff6743e4e623ff3bd67f30f1e0a9240db84fb54d41f

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=sha256:8573e25800859f1a3bb3eb696cc491adb8c45ab54f8507bbbaa8be07581a5a7e

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=sha256:83e8d856aeb49e98ad7ccc0d483823bffb3cfc3b2afc49e348769a227e1a5ea6

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:e2e41b9cda4482bcbca8755fb99ee553092320e97cc9f278f80cae4a66992b01

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:f1fc812ea70d85e4105b0f0bd8395b2462dbb5577583690c52effdcae0223b51

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:ef6ed9e1d4733a161bbfcbab1d0410d9694d165c6cb3d4ac997554d5e5dec648

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:c5887a7a740d91a77caafae9600be38cec2d80bea55d001c306a382eaab38061

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=sha256:437e5eaa32595be82b62517ced75960d4106bb46f43117a55fc33bf427a511fc

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=sha256:1f039e826b1fa40a089cc611c63fa6027c5a14ce77b1488323725bbe0350642d

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=sha256:1aa01564998a0a4df3d59a6d3dd940a97ff7bc1029aa54d89db22ca94f48cdca

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=sha256:3951eae5e4982c5d9b8658a73e020aead3132a8906fa4febc95c2f30e0a2b4a4

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=sha256:80a478bfb6dbc5b9a228305a9aeaedcb3a3c114fd9cb926865259500edd99595

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=sha256:6aae7c397c25694a4bdc6d06f25f7f53e9ca23e459bd096b83f8ab67f9cfbb5d

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=sha256:5211a2532e6ff4192986ccca478165a87d45aacde9efd8890f3513fa03459c1b

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:c956ffc1b605eec8a2c2c1b4da955578606aa9c47c633276f4fa992331b847b8

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:fcc1005b8c16fad582be6d600e7f2887a41b0d0fbee96cf2f7fed40b3c206c40

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=sha256:97bfd232f52c65c145635c478c2063be7b0bb8b8a187a318f107abcf4dda1805

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=sha256:293cc1bae44bb0816bba8501fabd7c4dbacf9cb1dc2513f288030456136cbb9c

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=sha256:16ff35cafdea6dfde61c88c229710b8861fc359a3fe34fcaf8ce0c38baa3eff9

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=sha256:5484571f656e9c54471ba17b0a482ddf38f9e8b7f86c55de528c9b9032cc860c

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=sha256:9abf9190c74e52fe46f3c7fcb50c6329c21c43100e1093c910b975c4aad2530c

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:de3980785e509f8375ae48e9cc082f55f8ae07933bb4c2a037ce8172cd053fb2

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:b518a2be49899baeb18d81ffe8dade34c67d4c534a05618183235a203024b009

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:ad4f0b144fce712e41bcc34c7b3cf30f28080757e8fd30f39c0d5b5b4a17e72c

Pith citing papers

No inbound Pith citation observations are available.