BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks | Paper Citation Record

Observation 9c88cdfa-1dd8-41ea-9aab-4adff7d14c77 · outbound

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

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks End to End Learning for Self-Driving Cars

Reference 1

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Observation 4e7b95a2-5efb-4adc-9b9b-738fea526535 · outbound

This paper cites Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases,

Reference 2

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Observation 44d51f42-f273-4725-a7d4-d3732c77d1f6 · outbound

This paper cites Deep learning for healthcare: review, opportunities and challenges,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Deep learning for healthcare: review, opportunities and challenges,

Reference 3

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Observation 9269cd90-4151-472d-9950-fc65b37330f0 · outbound

This paper cites Pre-trained models: Past, present and future,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Pre-trained models: Past, present and future,

Reference 4

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Observation 6b9bb4ce-4de8-4537-92f7-3fbdbd7e484d · outbound

This paper cites Spt-code: Sequence- to-sequence pre-training for learning source code representations,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Spt-code: Sequence- to-sequence pre-training for learning source code representations,

Reference 5

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Observation 0d9ccfe8-012e-4447-a1e7-69a00abe8be6 · outbound

This paper cites Fine-tuning of pre-trained deep learning models with extreme learning machine,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Fine-tuning of pre-trained deep learning models with extreme learning machine,

Reference 6

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Observation 567f8d74-077c-4da1-8169-cfc13dc72743 · outbound

This paper cites Sentiment analysis for software engineering: How far can pre-trained transformer models go?.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Sentiment analysis for software engineering: How far can pre-trained transformer models go?

Reference 7

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Observation f0fb8e1d-c16e-42dc-9cf3-44a9774a1bb9 · outbound

This paper cites Leveraging small software engineering data sets with pre-trained neural networks,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Leveraging small software engineering data sets with pre-trained neural networks,

Reference 8

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Observation 3148b1b0-a4d1-4a03-a5d3-86b74fdfe0cb · outbound

This paper cites Parameter-efficient fine-tuning of large- scale pre-trained language models,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Parameter-efficient fine-tuning of large- scale pre-trained language models,

Reference 9

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Observation 3d37fe91-05a7-4a7e-9ccd-c4c5471a2760 · outbound

This paper cites Backdoor learning: A survey,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Backdoor learning: A survey,

Reference 10

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Observation b58095d0-4093-4f0a-8cb6-93d1c4bf8993 · outbound

This paper cites Physical backdoor attacks to lane detection systems in autonomous driving,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Physical backdoor attacks to lane detection systems in autonomous driving,

Reference 11

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Observation f7311d8f-40af-4417-9e11-aa4e14c7ba38 · outbound

This paper cites Deeplocalize: Fault localization for deep neural networks,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Deeplocalize: Fault localization for deep neural networks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.585442Z

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Observation ce6561eb-2d18-4f38-abff-7a1ebbff8110 · outbound

This paper cites Deepdiagnosis: auto- matically diagnosing faults and recommending actionable fixes in deep learning programs,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Deepdiagnosis: auto- matically diagnosing faults and recommending actionable fixes in deep learning programs,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.575360Z

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Observation 9e0c3240-949f-4979-8fa3-3d613671c82b · outbound

This paper cites Mutation-based Fault Localization of Deep Neural Networks.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Mutation-based Fault Localization of Deep Neural Networks

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:07:40.813539Z

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Observation d2b5849f-2476-4ec9-8efe-4ab5ca08e3b7 · outbound

This paper cites Keep your eyes on the lane: Real-time attention- guided lane detection,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Keep your eyes on the lane: Real-time attention- guided lane detection,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.565324Z

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Observation b550807e-be76-44c2-8116-dd59257364d8 · outbound

This paper cites Glm: General language model pretraining with autoregressive blank infilling,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Glm: General language model pretraining with autoregressive blank infilling,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.555020Z

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Observation 3955e6f6-5ed8-4562-a07d-15fffc36a96d · outbound

This paper cites Bdefects4nn,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Bdefects4nn,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.543292Z

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Observation 67e5caec-d8fd-426f-9357-f8b9aaef81c4 · outbound

This paper cites Towards practical deployment-stage backdoor attack on deep neural networks,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Towards practical deployment-stage backdoor attack on deep neural networks,

Reference 18

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Observation 2062b895-3997-45e8-9371-88eee151e51e · outbound

This paper cites Subnet Replacement: Deployment-stage backdoor attack against deep neural networks in gray-box setting.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Subnet Replacement: Deployment-stage backdoor attack against deep neural networks in gray-box setting

Reference 19

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Observation 36cbf8a9-4f5f-441d-b8fd-500b13333ead · outbound

This paper cites An embarrassingly simple approach for trojan attack in deep neural networks,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks An embarrassingly simple approach for trojan attack in deep neural networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.519245Z

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Observation 760ac872-ff7c-483e-8816-a08b22c4459f · outbound

This paper cites Deeppayload: Black-box backdoor attack on deep learning models through neural payload injec- tion,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Deeppayload: Black-box backdoor attack on deep learning models through neural payload injec- tion,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.508790Z

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Observation 4105f32a-e480-4de6-a045-ac00bc41737a · outbound

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

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain

Reference 22

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Observation 672bc458-59c2-4933-b707-603614c88b69 · outbound

This paper cites Trojaning attack on neural networks,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Trojaning attack on neural networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.498610Z

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Observation 8484f523-5c4c-4f47-966a-0ef2679d6e1e · outbound

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

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Fine-pruning: Defending against backdooring attacks on deep neural networks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.488941Z

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Observation 52b1a7fe-ed97-415f-a4e0-38aee81e5676 · outbound

This paper cites Neural cleanse: Identifying and mitigating backdoor attacks in neural networks,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Neural cleanse: Identifying and mitigating backdoor attacks in neural networks,

Reference 25

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Observation 8348f8cb-40b6-4ef7-a9c0-667bd613c572 · outbound

This paper cites Adversarial neuron pruning purifies backdoored deep models,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Adversarial neuron pruning purifies backdoored deep models,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.471777Z

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Observation 750cb26d-fd2d-4ff8-9325-5d16208ef65f · outbound

This paper cites Data-free backdoor removal based on channel lipschitzness,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Data-free backdoor removal based on channel lipschitzness,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.461354Z

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Observation 7fbea683-3bc6-49bc-8eb5-bc7d74fa55be · outbound

This paper cites Backdoor defense via test-time detecting and repairing,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Backdoor defense via test-time detecting and repairing,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.450772Z

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Observation d4821229-0461-4d05-b954-5cf84fabfb19 · outbound

This paper cites Neural network semantic backdoor detection and mitigation: A causality-based approach,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Neural network semantic backdoor detection and mitigation: A causality-based approach,

Reference 29

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Observation a1ed3c41-9b5a-46d9-8102-b3a42728d30b · outbound

This paper cites Reconstructive neuron pruning for backdoor defense,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Reconstructive neuron pruning for backdoor defense,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.433684Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9228deb3-70af-4f54-a1b1-70eceb7f770f · outbound

This paper cites Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.356882Z

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Observation fe95fc88-9bb8-4f71-a30c-42c34ed94702 · outbound

This paper cites Neural response interpretation through the lens of critical pathways,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Neural response interpretation through the lens of critical pathways,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.422513Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f2cad3b9-59d6-4710-a52e-7ccd26b812c8 · outbound

This paper cites Importance estimation for neural network pruning,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Importance estimation for neural network pruning,

Reference 33

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Observation 6572726c-51e5-47e9-b9ad-a0a55be8d3fc · outbound

This paper cites Patching weak convolutional neural network models through modularization and composition,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Patching weak convolutional neural network models through modularization and composition,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.403469Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 57d15d5b-a0e9-4b4f-9732-612eb0391f7b · outbound

This paper cites Npc: N euron p ath c overage via characterizing decision logic of deep neural networks,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Npc: N euron p ath c overage via characterizing decision logic of deep neural networks,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.388974Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7cdff99a-d587-4b3f-b9fa-a4f2e3fceb7c · outbound

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

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Reference 36

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Observation f76a6905-46fa-4368-8b6a-b6420e79db13 · outbound

This paper cites Backdoorbench: A comprehensive benchmark of backdoor learning,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Backdoorbench: A comprehensive benchmark of backdoor learning,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.300827Z

Source-reported events for the cited work

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Observation 51a2d931-8c5f-4280-8395-4572979af9a8 · outbound

This paper cites Causality-based neural network repair,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Causality-based neural network repair,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.381349Z

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Observation f68a97ba-13d3-44f2-8788-1fe54efab292 · outbound

This paper cites Trojanzoo: Towards unified, holistic, and practical evaluation of neural backdoors,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Trojanzoo: Towards unified, holistic, and practical evaluation of neural backdoors,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.283974Z

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Observation e1730dcf-05b8-46b5-9c74-40e9bdd1cd0a · outbound

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

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Learning multiple layers of features from tiny images,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.387572Z

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Observation 93312a1a-c48d-4480-80e3-ae97507f50fc · outbound

This paper cites Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.390909Z

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Observation 1b1418b3-5766-4860-a494-6f8931a7b896 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.394345Z

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Observation 68e3153f-27cf-4b40-bd57-95e5b9351565 · outbound

This paper cites Deep residual learning for image recognition,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Deep residual learning for image recognition,

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.494994Z

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Observation bec8b9a3-6a8c-4898-a153-445cede6d208 · outbound

This paper cites Fairneuron: improving deep neural network fairness with adversary games on selective neurons,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Fairneuron: improving deep neural network fairness with adversary games on selective neurons,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.253563Z

Source-reported events for the cited work

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Observation 653a8874-a243-457e-9937-4e0756b67198 · outbound

This paper cites Mode: automated neural network model debugging via state differential analysis and input selection,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Mode: automated neural network model debugging via state differential analysis and input selection,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.239123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3a5683eb-73c6-47cf-a5e9-0e3842e22879 · outbound

This paper cites Ai-lancet: Locating error- inducing neurons to optimize neural networks,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Ai-lancet: Locating error- inducing neurons to optimize neural networks,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.227534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c16218c1-6972-4a95-856a-0a531e80a54c · outbound

This paper cites On decomposing a deep neural network into modules,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks On decomposing a deep neural network into modules,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.507269Z

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Unavailable: canonical work link unavailable.

Observation 27a49673-453d-460b-a0cd-9100f5be5f40 · outbound

This paper cites Reusing deep neural network models through model re-engineering,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Reusing deep neural network models through model re-engineering,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.208592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 593400b4-4088-479d-af9d-dda144309b74 · outbound

This paper cites Decomposing a recurrent neural network into modules for enabling reusability and replacement,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Decomposing a recurrent neural network into modules for enabling reusability and replacement,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.196682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ead5e26a-057b-4a78-9b86-0b2116afab47 · outbound

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

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Invisible backdoor attack with sample-specific triggers,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.185749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c5a578c2-4dd3-4e40-b998-edcdd2f16960 · outbound

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

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Deep feature space trojan attack of neural networks by controlled detoxification,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.175244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c338d308-371c-4df9-bf1c-8c5d4aca3380 · outbound

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

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks A new backdoor attack in cnns by training set corruption without label poisoning,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.164224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ffdb9656-3eaa-4fd6-890a-18be494c29f9 · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Mobilenetv2: Inverted residuals and linear bottlenecks,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.153737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fc4fb979-9bf4-4427-a173-dfd615b464b6 · outbound

This paper cites Wide Residual Networks.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Wide Residual Networks

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.529522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d2ced78-cce8-4e02-9199-f91afe8a6ff8 · outbound

This paper cites Imagenette: A smaller subset of 10 easily classified classes from imagenet,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Imagenette: A smaller subset of 10 easily classified classes from imagenet,

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.532742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b09b9d68-028f-433c-9c3a-ae41debd536d · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Imagenet: A large-scale hierarchical image database,

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.535781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6db8fea9-c23f-4128-bd5a-27be6218322d · outbound

This paper cites Tusimple benchmark,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Tusimple benchmark,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.130068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e91b2d41-1ae5-4f59-8db7-1a952704305b · outbound

This paper cites BadGPT: Exploring Security Vulnerabilities of ChatGPT via Backdoor Attacks to InstructGPT.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks BadGPT: Exploring Security Vulnerabilities of ChatGPT via Backdoor Attacks to InstructGPT

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.541758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b79b331-6d0e-425f-95ea-3e661d498637 · outbound

This paper cites Learning word vectors for sentiment analysis,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Learning word vectors for sentiment analysis,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.545622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6be9741-6551-4534-bada-e7ee8b3ae280 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks LoRA: Low-Rank Adaptation of Large Language Models

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.549227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fe6ab13-69f5-401c-bfa3-0555ec3c9c6d · outbound

This paper cites Blind backdoors in deep learning models,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Blind backdoors in deep learning models,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.553176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ee600c4-2af9-4640-a177-9a60c5eb811c · outbound

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

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.557822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edbb7fcb-1abf-44a3-ad1e-52133c6756ce · outbound

This paper cites Spectral signatures in backdoor attacks,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Spectral signatures in backdoor attacks,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.105752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ae74d645-7fd8-4c9c-ab16-5a5d975d1430 · outbound

This paper cites Rule-based runtime mitigation against poison attacks on neural networks,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Rule-based runtime mitigation against poison attacks on neural networks,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.095852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9f30fb04-98b2-42f8-b4ac-4e3251a38e8f · outbound

This paper cites Vpn: V erification of p oisoning in n eural networks,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Vpn: V erification of p oisoning in n eural networks,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.086499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b05f6cdb-8747-4fc7-bdbb-f963d5953540 · outbound

This paper cites Dual attention suppression attack: Generate adversarial camouflage in physical world,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Dual attention suppression attack: Generate adversarial camouflage in physical world,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.076035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 693c5da1-1c5e-4911-8379-51431a883d6c · outbound

This paper cites Perceptual- sensitive gan for generating adversarial patches,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Perceptual- sensitive gan for generating adversarial patches,

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.575934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e0309d1-7abd-4d37-aaf1-8a123de5d5b1 · outbound

This paper cites Bias-based universal adversarial patch attack for automatic check-out,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Bias-based universal adversarial patch attack for automatic check-out,

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.578871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f539bf5-c766-4a7b-8afc-b269be89a836 · outbound

This paper cites Robustart: Benchmarking robustness on architecture design and training techniques,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Robustart: Benchmarking robustness on architecture design and training techniques,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.051485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8077871f-1009-4051-9e6f-0a74a025f0be · outbound

This paper cites Training robust deep neural networks via adversarial noise propagation,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Training robust deep neural networks via adversarial noise propagation,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.039322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 57c82d2b-4461-4ab9-8744-56d011face67 · outbound

This paper cites Spatiotemporal attacks for embodied agents,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Spatiotemporal attacks for embodied agents,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.028282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 404d021f-abb0-45ef-90b3-89925058bbb6 · outbound

This paper cites X-adv: Physical adversarial object attacks against x-ray prohibited item detection,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks X-adv: Physical adversarial object attacks against x-ray prohibited item detection,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.017332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1dd8772b-3671-41ae-9d10-2395f862a5d5 · outbound

This paper cites Harnessing perceptual adversarial patches for crowd counting,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Harnessing perceptual adversarial patches for crowd counting,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:41.007093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4dc02076-cbda-4a58-a5ac-b142c4980ed7 · outbound

This paper cites Exploring the relationship between architecture and adversarially robust generalization,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Exploring the relationship between architecture and adversarially robust generalization,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:40.995964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 08bdb74c-250e-493f-8baf-efed5671b3b6 · outbound

This paper cites A comprehensive evaluation framework for deep model robustness,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks A comprehensive evaluation framework for deep model robustness,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:40.984956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d9666cc0-28b1-4672-b518-e4e03a8ae548 · outbound

This paper cites Towards defending multiple lp-norm bounded adversarial perturbations via gated batch normalization,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Towards defending multiple lp-norm bounded adversarial perturbations via gated batch normalization,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:40.973294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8c9b6109-7285-4a01-8fa4-172a71c04e99 · outbound

This paper cites Latent imitator: Generating natural individual discriminatory instances for black-box fairness testing,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Latent imitator: Generating natural individual discriminatory instances for black-box fairness testing,

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.607489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd294f2d-7690-4303-b85e-a54188574b30 · outbound

This paper cites Robustmq: benchmarking robustness of quantized models,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Robustmq: benchmarking robustness of quantized models,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:40.954846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 388cf808-ec45-4ac4-94d0-78185e20b4e9 · outbound

This paper cites GenderBias-\emph{VL}: Benchmarking Gender Bias in Vision Language Models via Counterfactual Probing.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks GenderBias-\emph{VL}: Benchmarking Gender Bias in Vision Language Models via Counterfactual Probing

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.613465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a0ad7da-4a81-488e-bec5-82085125e69e · outbound

This paper cites NeuSemSlice: Towards Effective DNN Model Maintenance via Neuron-level Semantic Slicing.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks NeuSemSlice: Towards Effective DNN Model Maintenance via Neuron-level Semantic Slicing

Reference 80

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:07:40.688080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 54ea500e-ad56-4ea7-b789-4a81e9ca9f00 · outbound

This paper cites Deepfault: Fault localization for deep neural networks,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Deepfault: Fault localization for deep neural networks,

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:40.944042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1a250648-94eb-4d85-a7d4-d4357c4eeae2 · outbound

This paper cites Automatic fault detection for deep learning programs using graph transformations,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Automatic fault detection for deep learning programs using graph transformations,

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-12T05:07:40.623050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a3bc492-f530-4120-9c80-60d815c665d7 · outbound

This paper cites Deepcrime: mutation testing of deep learning systems based on real faults,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Deepcrime: mutation testing of deep learning systems based on real faults,

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:40.924654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 28d817c7-7bd1-42a0-b8f9-c80f3b65cabb · outbound

This paper cites Nn repair: Constraint-based repair of neural network classifiers,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Nn repair: Constraint-based repair of neural network classifiers,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:40.913272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 04515c47-df07-4718-8733-b38ab9631124 · outbound

This paper cites Interpreting and improving adversarial robustness of deep neural networks with neuron sensitivity,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Interpreting and improving adversarial robustness of deep neural networks with neuron sensitivity,

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:40.900848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 694e58f5-8ebd-494a-bed0-4be339d35b8f · outbound

This paper cites Understanding adversarial robustness via critical attacking route,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Understanding adversarial robustness via critical attacking route,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:40.888087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f5cd09a7-1a18-49f2-9f26-28d6a7a76aef · outbound

This paper cites Fairer: fairness as decision rationale alignment,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Fairer: fairness as decision rationale alignment,

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:40.872789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 97a3ceb6-61fa-4722-93bd-b634695b1866 · outbound

This paper cites Faire: Repairing fairness of neural networks via neuron condition synthesis,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Faire: Repairing fairness of neural networks via neuron condition synthesis,

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:40.861031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 78719626-8593-4b7f-8b43-a4369114aee8 · outbound

This paper cites Runner: Responsible unfair neuron repair for enhancing deep neural network fairness,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Runner: Responsible unfair neuron repair for enhancing deep neural network fairness,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:40.848014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5df91437-8538-4f20-b6d9-79758278d0ec · outbound

This paper cites Trojan ai,.

BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Trojan ai,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:07:40.835737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers