All-in-One: A composable attack on LLM transformations
Read the original at arxiv.org→arXiv:2610.33298v1 Announce Type: new Abstract: Quantization, pruning, and model merging are popular transformations applied to deployment-ready LLMs to improve efficiency and downstream performance. Recent work has...
Original headline: "All-in-One: A Composable Attack on LLM Transformations"
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- Oct 27, 04:00 UTC arXiv cs.LG lead source All-in-One: A Composable Attack on LLM Transformations