Search Results for author: David Karamardian

Found 2 papers, 1 papers with code

Can LLMs Follow Simple Rules?

1 code implementation6 Nov 2023 Norman Mu, Sarah Chen, Zifan Wang, Sizhe Chen, David Karamardian, Lulwa Aljeraisy, Basel Alomair, Dan Hendrycks, David Wagner

As Large Language Models (LLMs) are deployed with increasing real-world responsibilities, it is important to be able to specify and constrain the behavior of these systems in a reliable manner.

Large Language Models as Tax Attorneys: A Case Study in Legal Capabilities Emergence

no code implementations12 Jun 2023 John J. Nay, David Karamardian, Sarah B. Lawsky, WenTing Tao, Meghana Bhat, Raghav Jain, Aaron Travis Lee, Jonathan H. Choi, Jungo Kasai

Better understanding of Large Language Models' (LLMs) legal analysis abilities can contribute to improving the efficiency of legal services, governing artificial intelligence, and leveraging LLMs to identify inconsistencies in law.

Logical Reasoning

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