CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection | Paper Citation Record

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection GPT-4 Technical Report

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Qwen Technical Report

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Qwen2.5-VL Technical Report

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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This paper cites The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Euro- pean Conference on Computer Vision

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This paper cites AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

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This paper cites Advances in Neural Information Processing Systems37, 57817–57840 (2024).

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Advances in Neural Information Processing Systems37, 57817–57840 (2024)

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the IEEE/CVF conference on computer vision and pat- tern recognition

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This paper cites In: ECAI 2025, pp.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: ECAI 2025, pp

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Mixture-of-LoRAs: An Efficient Multitask Tuning for Large Language Models

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This paper cites VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Unresolved cited work

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model

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This paper cites Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

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This paper cites Sensors22(9), 3166 (2022).

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Sensors22(9), 3166 (2022)

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection HiDe-LLaVA: Hierarchical Decoupling for Continual Instruction Tuning of Multimodal Large Language Model

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This paper cites Advances in Neural Information Processing Systems37, 71162– 71187 (2024).

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Advances in Neural Information Processing Systems37, 71162– 71187 (2024)

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: International conference on machine learning

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection ICLR1(2), 3 (2022)

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the Computer Vision and Pattern Recognition Conference

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Pro- ceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogni- tion

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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This paper cites Proceedings of the national academy of sciences114(13), 3521–3526 (2017).

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Proceedings of the national academy of sciences114(13), 3521–3526 (2017)

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection The Power of Scale for Parameter-Efficient Prompt Tuning

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection LLaVA-OneVision: Easy Visual Task Transfer

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the IEEE/CVF conference on com- puter vision and pattern recognition

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Prefix-Tuning: Optimizing Continuous Prompts for Generation

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection IAD-R1: Reinforcing Consistent Reasoning in Industrial Anomaly Detection

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the AAAI Conference on Artificial Intelligence

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This paper cites IEEE transactions on pattern anal- ysis and machine intelligence40(12), 2935–2947 (2017).

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection IEEE transactions on pattern anal- ysis and machine intelligence40(12), 2935–2947 (2017)

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

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This paper cites Applied Intelligence53(20), 23628–23640 (2023).

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Applied Intelligence53(20), 23628–23640 (2023)

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Advances in Neural Information Processing Systems35, 16165–16177 (2022)

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Sensors23(21), 8750 (2023)

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Advances in neural information processing systems36, 34892–34916 (2023)

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the AAAI conference on artificial intelligence

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Advances in Neural Information Processing Systems36, 30402–30415 (2023)

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Advances in neural information processing systems30(2017)

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Decoupled Weight Decay Regularization

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Unresolved cited work

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Advances in Neural Information Processing Systems37, 97476–97498 (2024)

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Advances in neural information processing systems32(2019)

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This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: European conference on computer vision

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This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the AAAI Conference on Artificial Intelligence

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CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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This paper cites LLaMA: Open and Efficient Foundation Language Models.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection LLaMA: Open and Efficient Foundation Language Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc49fedb-b2d9-4883-8a73-236fdc419dd2 · outbound

This paper cites Student-Teacher Feature Pyramid Matching for Anomaly Detection.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Student-Teacher Feature Pyramid Matching for Anomaly Detection

Reference 55

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6206aef9-0cf5-438b-a5fa-0deca63350b1 · outbound

This paper cites Visual Intelligence4(1), 7 (2026).

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Visual Intelligence4(1), 7 (2026)

Reference 56

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e22b864-2f25-48af-a632-6784bdd58994 · outbound

This paper cites In: Findings of the Association for Computational Linguistics: EMNLP 2023.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Findings of the Association for Computational Linguistics: EMNLP 2023

Reference 57

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67ddad43-d6f0-4bce-9527-ba2638f54902 · outbound

This paper cites In: Pro- ceedings of the IEEE/CVF International Conference on Computer Vision.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Pro- ceedings of the IEEE/CVF International Conference on Computer Vision

Reference 58

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91a7748b-183b-47ca-92c6-9a5b0cd4aaee · outbound

This paper cites In: Medical Imaging 2018: Computer- Aided Diagnosis.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Medical Imaging 2018: Computer- Aided Diagnosis

Reference 59

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4eadc84-4d69-412e-8bd2-d57468eb73d1 · outbound

This paper cites Advances in Neural Information Pro- cessing Systems37, 69925–69975 (2024).

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Advances in Neural Information Pro- cessing Systems37, 69925–69975 (2024)

Reference 60

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 679b5bf7-010b-4698-b66e-5fbcbf052ef6 · outbound

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

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the Computer Vision and Pattern Recognition Conference

Reference 61

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9472100e-ffb3-4cf3-b4e1-0501ec889141 · outbound

This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: International Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 62

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 537eb16f-b77e-4be9-ab79-d6db620ea36d · outbound

This paper cites IEEE Transactions on Medical Imaging40(12), 3641–3651 (2021).

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection IEEE Transactions on Medical Imaging40(12), 3641–3651 (2021)

Reference 63

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc46e728-7c2c-42b9-aafb-c527423f8cbd · outbound

This paper cites arXiv preprint arXiv:2506.05453 (2025).

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection arXiv preprint arXiv:2506.05453 (2025)

Reference 64

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a612626b-f8e3-49ce-ba22-58413842c0b3 · outbound

This paper cites Thinking Before Looking: Improving Multimodal LLM Reasoning via Mitigating Visual Hallucination.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Thinking Before Looking: Improving Multimodal LLM Reasoning via Mitigating Visual Hallucination

Reference 65

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46e1c825-7d69-4116-8f19-7cbd7ce5c66b · outbound

This paper cites arXiv preprint arXiv:2310.18961 (2023).

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection arXiv preprint arXiv:2310.18961 (2023)

Reference 66

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a8e7858-bbcf-42a9-b162-65691892fd19 · outbound

This paper cites In: Proceedings of the IEEE/CVF con- ference on computer vision and pattern recognition.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection In: Proceedings of the IEEE/CVF con- ference on computer vision and pattern recognition

Reference 67

Resolution: unresolved; no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers