DLR-Lock locks open-weight LLMs against unauthorized fine-tuning by swapping MLPs for deep low-rank residual networks that inflate backprop memory and complicate optimization, yet preserve original capabilities via module-wise distillation.
arXiv.org
5 Pith papers cite this work, alongside 11 external citations. Polarity classification is still indexing.
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representative citing papers
Thematic analysis of r/LocalLLaMA discussions finds users define openness via reliability, local control, privacy, and adaptation under compute, licensing, and usability constraints.
RepSelect isolates forget-set-specific representations via gradient PCA collapse to achieve 4-50x better post-relearning robustness than baselines across multiple models and forget categories.
The web's anti-bot regime should be replaced by a framework that presumptively lets user-authorized AI agents act for their principals, requires platforms to disclose access policies, and permits agent blocking only when proportionate to concrete harms.
AI model evaluations for biological capabilities should prioritize high-consequence risks like pandemics, informed by life sciences dual-use experience, and occur prior to deployment to enable biosafety measures.
citing papers explorer
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Locking Pretrained Weights via Deep Low-Rank Residual Distillation
DLR-Lock locks open-weight LLMs against unauthorized fine-tuning by swapping MLPs for deep low-rank residual networks that inflate backprop memory and complicate optimization, yet preserve original capabilities via module-wise distillation.
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Open AI in the Wild: Adoption and Adaptation of Open Models on r/LocalLLaMA
Thematic analysis of r/LocalLLaMA discussions finds users define openness via reliability, local control, privacy, and adaptation under compute, licensing, and usability constraints.
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RepSelect: Robust LLM Unlearning via Representation Selectivity
RepSelect isolates forget-set-specific representations via gradient PCA collapse to achieve 4-50x better post-relearning robustness than baselines across multiple models and forget categories.
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The Agentic Web Requires New Normative Infrastructure
The web's anti-bot regime should be replaced by a framework that presumptively lets user-authorized AI agents act for their principals, requires platforms to disclose access policies, and permits agent blocking only when proportionate to concrete harms.
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Prioritizing High-Consequence Biological Capabilities in Evaluations of Artificial Intelligence Models
AI model evaluations for biological capabilities should prioritize high-consequence risks like pandemics, informed by life sciences dual-use experience, and occur prior to deployment to enable biosafety measures.