A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models | Paper Citation Record

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This paper cites In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recogni- tion, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recogni- tion, pp

Reference 1

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This paper cites Interna- tional Journal of Computer Vision, 1–20 (2025).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Interna- tional Journal of Computer Vision, 1–20 (2025)

Reference 2

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This paper cites Inter- national Journal of Computer Vision 133(6), 3568–3585 (2025).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Inter- national Journal of Computer Vision 133(6), 3568–3585 (2025)

Reference 3

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This paper cites Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection

Reference 4

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This paper cites Compromising Embodied Agents with Contextual Backdoor Attacks.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Compromising Embodied Agents with Contextual Backdoor Attacks

Reference 5

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This paper cites In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp

Reference 6

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This paper cites Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt

Reference 7

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This paper cites arXiv preprint arXiv:2503.04833 , year=.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models arXiv preprint arXiv:2503.04833 , year=

Reference 8

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This paper cites Reasoning-Augmented Conversation for Multi-Turn Jailbreak Attacks on Large Language Models.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Reasoning-Augmented Conversation for Multi-Turn Jailbreak Attacks on Large Language Models

Reference 9

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This paper cites arXiv preprint arXiv:2509.21400 (2025).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models arXiv preprint arXiv:2509.21400 (2025)

Reference 10

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This paper cites International Jour- nal of Computer Vision134(1), 18 (2026).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models International Jour- nal of Computer Vision134(1), 18 (2026)

Reference 11

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This paper cites Advances in neural information processing sys- tems36, 34892–34916 (2023).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Advances in neural information processing sys- tems36, 34892–34916 (2023)

Reference 12

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This paper cites GPT-4 Technical Report.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models GPT-4 Technical Report

Reference 13

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This paper cites In: International Conference on Machine Learning, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: International Conference on Machine Learning, pp

Reference 14

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A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Unresolved cited work

Reference 15

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This paper cites Advances in neural information pro- cessing systems36, 49250–49267 (2023).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Advances in neural information pro- cessing systems36, 49250–49267 (2023)

Reference 16

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This paper cites In: Machine Learning for Health (ML4H), pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Machine Learning for Health (ML4H), pp

Reference 17

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This paper cites In: European Conference on Computer Vision, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: European Conference on Computer Vision, pp

Reference 18

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

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain

Reference 19

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This paper cites In: Findings of the Association for Computational Lin- guistics: NAACL 2024, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Findings of the Association for Computational Lin- guistics: NAACL 2024, pp

Reference 20

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This paper cites Advances in Neural Information Processing Systems37, 57733–57764 (2024).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Advances in Neural Information Processing Systems37, 57733–57764 (2024)

Reference 21

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This paper cites Hidden Killer: Invisible Textual Backdoor Attacks with Syntactic Trigger.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Hidden Killer: Invisible Textual Backdoor Attacks with Syntactic Trigger

Reference 22

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This paper cites In: Proceedings of the 26th ACM SIGKDD Interna- tional Conference on Knowledge Dis- covery & Data Mining, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Proceedings of the 26th ACM SIGKDD Interna- tional Conference on Knowledge Dis- covery & Data Mining, pp

Reference 23

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This paper cites In: 25th Annual Network And Distributed System Security Sympo- sium (NDSS 2018) (2018).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: 25th Annual Network And Distributed System Security Sympo- sium (NDSS 2018) (2018)

Reference 24

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This paper cites In: Findings of the Association for Computational Lin- guistics: ACL 2025, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Findings of the Association for Computational Lin- guistics: ACL 2025, pp

Reference 25

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This paper cites Backdooring Vision-Language Models with Out-Of-Distribution Data.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Backdooring Vision-Language Models with Out-Of-Distribution Data

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This paper cites In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recogni- tion, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recogni- tion, pp

Reference 27

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This paper cites arXiv preprint arXiv:2412.20392 (2024).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models arXiv preprint arXiv:2412.20392 (2024)

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This paper cites Advances in neural information processing systems35, 23716–23736 (2022).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Advances in neural information processing systems35, 23716–23736 (2022)

Reference 29

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This paper cites OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

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This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

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This paper cites In: International Conference on Machine Learning, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: International Conference on Machine Learning, pp

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This paper cites In: International Conference on Machine Learning, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: International Conference on Machine Learning, pp

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This paper cites Kosmos-2: Grounding Multimodal Large Language Models to the World.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Kosmos-2: Grounding Multimodal Large Language Models to the World

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This paper cites IEEE Transactions on Pat- tern Analysis and Machine Intelli- gence (2025).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models IEEE Transactions on Pat- tern Analysis and Machine Intelli- gence (2025)

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This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

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This paper cites Bench2ADVLM: A Closed-Loop Benchmark for Vision-language Models in Autonomous Driving.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Bench2ADVLM: A Closed-Loop Benchmark for Vision-language Models in Autonomous Driving

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This paper cites Agentsafe: Benchmarking the safety of embodied agents on hazardous instructions.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Agentsafe: Benchmarking the safety of embodied agents on hazardous instructions

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This paper cites Visual Adversarial Attack on Vision-Language Models for Autonomous Driving.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Visual Adversarial Attack on Vision-Language Models for Autonomous Driving

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This paper cites Black-Box Adversarial Attack on Vision Language Models for Autonomous Driving.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Black-Box Adversarial Attack on Vision Language Models for Autonomous Driving

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This paper cites Visual Intelligence2(1), 1–10 (2024).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Visual Intelligence2(1), 1–10 (2024)

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This paper cites Universal camouflage attack on vision-language models for autonomous driving.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Universal camouflage attack on vision-language models for autonomous driving

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

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

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Observation b1b3c418-51e2-494f-b110-802edbdee95f · outbound

This paper cites Stealthy Low-frequency Backdoor Attack against Deep Neural Networks.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Stealthy Low-frequency Backdoor Attack against Deep Neural Networks

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This paper cites Universal Backdoor Attacks Detection via Adaptive Adversarial Probe.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Universal Backdoor Attacks Detection via Adaptive Adversarial Probe

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This paper cites Unlearning Backdoor Threats: Enhancing Backdoor Defense in Multimodal Contrastive Learning via Local Token Unlearning.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Unlearning Backdoor Threats: Enhancing Backdoor Defense in Multimodal Contrastive Learning via Local Token Unlearning

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Observation 5af172ae-e6ce-4b25-9ba0-18316f5a510b · outbound

This paper cites Advances in Neural Informa- tion Processing Systems37, 114928– 114964 (2024).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Advances in Neural Informa- tion Processing Systems37, 114928– 114964 (2024)

Reference 47

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Observation a280cbb2-1dd2-49f3-b3fa-5ca6889eba34 · outbound

This paper cites Adversarial Backdoor Defense in CLIP.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Adversarial Backdoor Defense in CLIP

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Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:05:49.283566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e2e9d226-d3c3-4433-a8a1-fde450d50091 · outbound

This paper cites Robust Anti-Backdoor Instruction Tuning in LVLMs.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Robust Anti-Backdoor Instruction Tuning in LVLMs

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:05:49.185883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5da1835a-9c72-4b2b-bd5f-533cff141100 · outbound

This paper cites Lie Detector: Unified Backdoor Detection via Cross-Examination Framework.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Lie Detector: Unified Backdoor Detection via Cross-Examination Framework

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:05:49.273916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 42a59bec-4e81-4d54-83a6-bdfcc13ff736 · outbound

This paper cites ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:05:49.264619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8e8d1372-d087-4400-b2fc-16e240eee93c · outbound

This paper cites ELBA-Bench: An Efficient Learning Backdoor Attacks Benchmark for Large Language Models.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models ELBA-Bench: An Efficient Learning Backdoor Attacks Benchmark for Large Language Models

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:05:49.242956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ffc9a407-85d9-4f67-b2d2-e3186d8954cb · outbound

This paper cites In: 2025 IEEE/ACM 47th Interna- tional Conference on Software Engi- neering (ICSE), pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: 2025 IEEE/ACM 47th Interna- tional Conference on Software Engi- neering (ICSE), pp

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.231632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1fa43b85-5292-4a21-97f8-c5f65657ea4d · outbound

This paper cites IEEE Transactions on Information Foren- sics and Security (2026).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models IEEE Transactions on Information Foren- sics and Security (2026)

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.236395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4019e872-c869-42ef-b1a4-a3d670d0f029 · outbound

This paper cites Natural Reflection Backdoor Attack on Vision Language Model for Autonomous Driving.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Natural Reflection Backdoor Attack on Vision Language Model for Autonomous Driving

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:05:49.195873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 05f2fa40-bcde-439f-8a10-4920cd164397 · outbound

This paper cites WaNet -- Imperceptible Warping-based Backdoor Attack.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models WaNet -- Imperceptible Warping-based Backdoor Attack

Reference 56

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:05:49.217777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation cbf1a1c8-b5aa-4e1d-a02a-a9aca14053d9 · outbound

This paper cites Advances in Neural Information Processing Systems33, 3454–3464 (2020).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Advances in Neural Information Processing Systems33, 3454–3464 (2020)

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.260018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8d88b0b7-1395-4551-9bbd-7e6a0e467ee4 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recogni- tion, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recogni- tion, pp

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.285644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 08a8dfb5-359c-4925-bde1-e6cf8ba5d51e · outbound

This paper cites an unresolved cited work.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-05-16T02:02:07.269451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 919cdc51-52a2-4448-ab43-42a19f33d206 · outbound

This paper cites IEEE Transactions on Depend- able and Secure Computing18(5), 2088–2105 (2020).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models IEEE Transactions on Depend- able and Secure Computing18(5), 2088–2105 (2020)

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.229381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f7fe804e-b0b0-4672-b22b-23ccb233e1ee · outbound

This paper cites Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Reference 61

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:16:31.113595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d0364fd3-3ba5-42cd-a190-7564f42733ad · outbound

This paper cites In: 2019 IEEE Sympo- sium on Security and Privacy (SP), pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: 2019 IEEE Sympo- sium on Security and Privacy (SP), pp

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.224587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1c5d457a-21c4-40bc-9511-77b78835b056 · outbound

This paper cites In: International Sympo- sium on Research in Attacks, Intru- sions, and Defenses, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: International Sympo- sium on Research in Attacks, Intru- sions, and Defenses, pp

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.281286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b1152bc0-930a-4e39-97f4-cf529efbe86f · outbound

This paper cites In: Pro- ceedings of the 35th Annual Com- puter Security Applications Confer- ence, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Pro- ceedings of the 35th Annual Com- puter Security Applications Confer- ence, pp

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.201059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8484a0bd-a627-48b5-8e59-5d55689aaeb7 · outbound

This paper cites Advances in Neural 23 Information Processing Systems34, 16913–16925 (2021).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Advances in Neural 23 Information Processing Systems34, 16913–16925 (2021)

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.233970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e1bc2cd4-9fdd-45d5-a9d3-88a2a773f5f4 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recogni- tion, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recogni- tion, pp

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.271762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 40875cd0-511a-49db-b332-4c79544b6251 · outbound

This paper cites International Journal of Com- puter Vision134(4), 144 (2026).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models International Journal of Com- puter Vision134(4), 144 (2026)

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.288593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0afb5f8c-cece-4a2c-89f3-4a21ef5e8654 · outbound

This paper cites No Query, No Access.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models No Query, No Access

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:05:49.131666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b3ab311e-9aff-4b77-873c-ea444aa4f29d · outbound

This paper cites Pushing the Limits of Safety: A Technical Report on the ATLAS Challenge 2025.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Pushing the Limits of Safety: A Technical Report on the ATLAS Challenge 2025

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:05:49.310638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0bedbd4c-7431-4b58-b3d7-e86d0216f8e5 · outbound

This paper cites AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty

Reference 70

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:05:49.261392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5065dd01-59de-48c8-bad3-fc524c88fd17 · outbound

This paper cites Transferable Adversarial Attacks for Image and Video Object Detection.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Transferable Adversarial Attacks for Image and Video Object Detection

Reference 71

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:05:49.182636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c755ab02-f62e-473f-81de-3193ebead5e4 · outbound

This paper cites Parallel Rectangle Flip Attack: A Query-based Black-box Attack against Object Detection.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Parallel Rectangle Flip Attack: A Query-based Black-box Attack against Object Detection

Reference 72

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:05:49.199039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1a7d822d-1a2b-4022-badf-673ae352ddd3 · outbound

This paper cites In: European Conference on Com- puter Vision (2022).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: European Conference on Com- puter Vision (2022)

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.296187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 407dc2fc-bceb-4a61-8a6e-1e20e04c78bd · outbound

This paper cites Improving Adversarial Transferability by Stable Diffusion.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Improving Adversarial Transferability by Stable Diffusion

Reference 74

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:05:49.314143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0c653238-d2e6-4c3c-a6fa-c13fe9b1265a · outbound

This paper cites Advances in neural information processing systems33, 596–608 (2020).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Advances in neural information processing systems33, 596–608 (2020)

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.198554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8184e24d-35d9-449b-91fc-7a95f9b1168d · outbound

This paper cites In: Proceed- ings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2023).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Proceed- ings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2023)

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.298614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f61f7246-6a40-4a42-9210-eefae7b8b50d · outbound

This paper cites IEEE transactions on pat- tern analysis and machine intelli- gence41(8), 1979–1993 (2018).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models IEEE transactions on pat- tern analysis and machine intelli- gence41(8), 1979–1993 (2018)

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.215196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5135d18b-d3b8-4681-9fbf-d89173971a9d · outbound

This paper cites Diversifying the High-level Features for better Adversarial Transferability.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Diversifying the High-level Features for better Adversarial Transferability

Reference 78

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:05:49.270863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9174e75b-e68a-4379-b4a7-d8ddd05251d0 · outbound

This paper cites Regularizing Neural Networks by Penalizing Confident Output Distributions.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Regularizing Neural Networks by Penalizing Confident Output Distributions

Reference 79

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:05:49.307471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fe74c021-c9dc-4c44-ba00-586f18f5a629 · outbound

This paper cites In: Interna- tional Conference on Machine Learn- ing, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Interna- tional Conference on Machine Learn- ing, pp

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.240769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c51acf26-8d7d-4376-ba2a-d14c88de6568 · outbound

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

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering

Reference 81

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:05:49.228092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e0a668ee-260e-4e60-8d73-375d1c058ece · outbound

This paper cites In: Proceedings of the 33rd ACM International Con- ference on Multimedia, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Proceedings of the 33rd ACM International Con- ference on Multimedia, pp

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.264879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b858af93-de5d-4674-ab00-06e5fe0d2b3f · outbound

This paper cites T2V-OptJail: Discrete Prompt Optimization for Text-to-Video Jailbreak Attacks.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models T2V-OptJail: Discrete Prompt Optimization for Text-to-Video Jailbreak Attacks

Reference 83

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:05:49.302329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e92c1387-2c6d-4023-8392-e33277bccbbd · outbound

This paper cites In: Com- puter Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXVI 16 (2020).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Com- puter Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXVI 16 (2020)

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.205763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 734c1e8c-30e2-446c-9d36-ac99c90dfe43 · outbound

This paper cites In: Proceedings of the 32nd ACM International Confer- ence on Multimedia, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Proceedings of the 32nd ACM International Confer- ence on Multimedia, pp

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.276480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 06ac682a-0c87-462c-8301-20e8b5367cee · outbound

This paper cites Environmental Matching Attack Against Unmanned Aerial Vehicles Object Detection.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Environmental Matching Attack Against Unmanned Aerial Vehicles Object Detection

Reference 86

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:05:49.124863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 392b2e1e-2336-4afb-b5c4-b09c0ee4b324 · outbound

This paper cites In: 32nd USENIX Security Symposium (USENIX Security 23), pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: 32nd USENIX Security Symposium (USENIX Security 23), pp

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.184472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5f4430a7-bfb5-421f-9657-01479aa20bd6 · outbound

This paper cites In: Pro- ceedings of the 31st ACM SIGSOFT International Symposium on Soft- ware Testing and Analysis, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Pro- ceedings of the 31st ACM SIGSOFT International Symposium on Soft- ware Testing and Analysis, pp

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.219635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 845a0add-6b58-4266-99ab-0b0fb8eea9a2 · outbound

This paper cites In: 33rd USENIX Security Symposium (USENIX Security 24), pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: 33rd USENIX Security Symposium (USENIX Security 24), pp

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.227015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c425c277-0063-416f-a252-008e53d9e72a · outbound

This paper cites In: Proceedings of the Com- puter Vision and Pattern Recog- nition Conference, pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: Proceedings of the Com- puter Vision and Pattern Recog- nition Conference, pp

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.257472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2198c4fa-6540-40d6-a123-920bf9455bae · outbound

This paper cites In: 2025 40th IEEE/ACM International Confer- ence on Automated Software Engi- neering (ASE), pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: 2025 40th IEEE/ACM International Confer- ence on Automated Software Engi- neering (ASE), pp

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.208289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 324fb9ee-fd33-4912-aa26-8e34b186a35a · outbound

This paper cites IEEE Transactions on Dependable and Secure Comput- ing (2025).

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models IEEE Transactions on Dependable and Secure Comput- ing (2025)

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.193959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation faca641a-106d-43fd-a132-91c619cfd472 · outbound

This paper cites In: 2023 60th ACM/IEEE Design Automa- tion Conference (DAC), pp.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models In: 2023 60th ACM/IEEE Design Automa- tion Conference (DAC), pp

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T02:02:07.283482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers