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LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models
Autor:
Guha, Neel, Nyarko, Julian, Ho, Daniel E., Ré, Christopher, Chilton, Adam, Narayana, Aditya, Chohlas-Wood, Alex, Peters, Austin, Waldon, Brandon, Rockmore, Daniel N., Zambrano, Diego, Talisman, Dmitry, Hoque, Enam, Surani, Faiz, Fagan, Frank, Sarfaty, Galit, Dickinson, Gregory M., Porat, Haggai, Hegland, Jason, Wu, Jessica, Nudell, Joe, Niklaus, Joel, Nay, John, Choi, Jonathan H., Tobia, Kevin, Hagan, Margaret, Ma, Megan, Livermore, Michael, Rasumov-Rahe, Nikon, Holzenberger, Nils, Kolt, Noam, Henderson, Peter, Rehaag, Sean, Goel, Sharad, Gao, Shang, Williams, Spencer, Gandhi, Sunny, Zur, Tom, Iyer, Varun, Li, Zehua
The advent of large language models (LLMs) and their adoption by the legal community has given rise to the question: what types of legal reasoning can LLMs perform? To enable greater study of this question, we present LegalBench: a collaboratively co
Externí odkaz:
http://arxiv.org/abs/2308.11462
