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cs.CR2024
Countering Autonomous Cyber Threats
Kade M. Heckel, Adrian Weller
With the capability to write convincing and fluent natural language and generate code, Foundation Models present dual-use concerns broadly and within the cyber domain specifically.…
cs.LG2024
On Evaluating LLMs' Capabilities as Functional Approximators: A Bayesian Perspective
Shoaib Ahmed Siddiqui, Yanzhi Chen, Juyeon Heo +2
Recent works have successfully applied Large Language Models (LLMs) to function modeling tasks. However, the reasons behind this success remain unclear. In this work, we propose a…
cs.LG2024
Mutual Information Multinomial Estimation
Yanzhi Chen, Zijing Ou, Adrian Weller +1
Estimating mutual information (MI) is a fundamental yet challenging task in data science and machine learning. This work proposes a new estimator for mutual information. Our main d…