A new arXiv paper details a method for mapping and controlling personality traits in large language models using low-rank adapters. This technique allows for the adjustment of characteristics like neuroticism and agreeableness, with measurable impacts on AI safety. Separately, a preprint introduces layer-parallel cuts to encrypted AI inference, which can speed up computations by 2.65 times with a minimal perplexity cost, potentially making private AI more practical. AI
IMPACT These advancements could lead to more controllable and safer AI models, as well as more private AI inference capabilities.
RANK_REASON The cluster contains two preprints discussing novel research in LLM control and encrypted AI inference.
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