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Large Language Models as Fiduciaries: A Case Study Toward Robustly
  Communicating With Artificial Intelligence Through Legal Standards

Large Language Models as Fiduciaries: A Case Study Toward Robustly Communicating With Artificial Intelligence Through Legal Standards

24 January 2023
John J. Nay
    ELM
    AILaw
ArXivPDFHTML

Papers citing "Large Language Models as Fiduciaries: A Case Study Toward Robustly Communicating With Artificial Intelligence Through Legal Standards"

4 / 4 papers shown
Title
Pile of Law: Learning Responsible Data Filtering from the Law and a
  256GB Open-Source Legal Dataset
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset
Peter Henderson
M. Krass
Lucia Zheng
Neel Guha
Christopher D. Manning
Dan Jurafsky
Daniel E. Ho
AILaw
ELM
129
94
0
01 Jul 2022
Autoformalization with Large Language Models
Autoformalization with Large Language Models
Yuhuai Wu
Albert Q. Jiang
Wenda Li
M. Rabe
Charles Staats
M. Jamnik
Christian Szegedy
AI4CE
108
156
0
25 May 2022
LexGLUE: A Benchmark Dataset for Legal Language Understanding in English
LexGLUE: A Benchmark Dataset for Legal Language Understanding in English
Ilias Chalkidis
Abhik Jana
D. Hartung
M. Bommarito
Ion Androutsopoulos
Daniel Martin Katz
Nikolaos Aletras
AILaw
ELM
123
244
0
03 Oct 2021
Grounding Language to Entities and Dynamics for Generalization in
  Reinforcement Learning
Grounding Language to Entities and Dynamics for Generalization in Reinforcement Learning
H. Wang
Victor Zhong
Karthik Narasimhan
76
53
0
19 Jan 2021
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