A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models explores A defense framework to prevent backdoor attacks in multimodal large language models by regularizing feature representations and output distributions.. Commercial viability score: 4/10 in Multimodal LLM Security.
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Canonical route: /paper/a-patch-based-cross-view-regularized-framework-for-backdoor-defense-in-multimodal-large-language-models
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Canonical ID a-patch-based-cross-view-regularized-framework-for-backdoor-defense-in-multimodal-large-language-models | Route /paper/a-patch-based-cross-view-regularized-framework-for-backdoor-defense-in-multimodal-large-language-models
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curl https://sciencetostartup.com/api/v1/agent-handoff/paper/a-patch-based-cross-view-regularized-framework-for-backdoor-defense-in-multimodal-large-language-modelsMCP example
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/buildability/a-patch-based-cross-view-regularized-framework-for-backdoor-defense-in-multimodal-large-language-models
Subject: A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models
Verdict
Ignore
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Dimensions overall score 4.0
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Receipt path
/buildability/a-patch-based-cross-view-regularized-framework-for-backdoor-defense-in-multimodal-large-language-models
Paper ref
a-patch-based-cross-view-regularized-framework-for-backdoor-defense-in-multimodal-large-language-models
arXiv id
2604.04488
Generated at
2026-04-07T20:13:34.907Z
Evidence freshness
fresh
Last verification
2026-04-07T20:13:34.907Z
Sources
0
References
0
Coverage
0%
Lineage hash
4c7320beca79ddf7d8a1629fb34684c2ef8ce0302754d21e678fb964f4bc0325
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unsigned_external
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