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Found 3 papers, 1 papers with code
Unveiling Safety Vulnerabilities of Large Language Models
As large language models become more prevalent, their possible harmful or inappropriate responses are a cause for concern.
The Fast Johnson-Lindenstrauss Transform is Even Faster
In this work, we give a surprising new analysis of the Fast JL transform, showing that the $k \ln^2 n$ term in the embedding time can be improved to $(k \ln^2 n)/\alpha$ for an $\alpha = \Omega(\min\{\varepsilon^{-1}\ln(1/\varepsilon), \ln n\})$.
Optimality of the Johnson-Lindenstrauss Dimensionality Reduction for Practical Measures
They provided upper bounds on its quality for a wide range of practical measures and showed that indeed these are best possible in many cases.
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