RASLIK uses randomized antipodal search on linearized influence kernels to achieve data Pareto improvement in LLM unlearning, outperforming baselines with sublinear complexity and double gains in quality and efficiency.
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Randomized Antipodal Search Done Right for Data Pareto Improvement of LLM Unlearning
RASLIK uses randomized antipodal search on linearized influence kernels to achieve data Pareto improvement in LLM unlearning, outperforming baselines with sublinear complexity and double gains in quality and efficiency.