{"version":"1.0","type":"rich","provider_name":"Acast","provider_url":"https://acast.com","height":250,"width":700,"html":"<iframe src=\"https://embed.acast.com/$/665063a7c82f830012fb4863/66506feef749480012bb6a34?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":"Teaching Language Models to Think Like Lawyers","thumbnail_width":200,"thumbnail_height":200,"thumbnail_url":"https://open-images.acast.com/shows/665063a7c82f830012fb4863/1716547536810-5e2359350ec453c8ff16d086b4f581ee.jpeg?height=200","description":"<p>This episode explores prompt engineering, a new research area that attempts to teach large language models (LLMs) to perform complex legal reasoning tasks. We discuss a paper that investigates how to make LLMs “think like a lawyer” using the Japanese Bar exam as a benchmark.</p>","author_name":"Simon Landry"}