From 69088d5527319bac3cc9893f2449db854227be70 Mon Sep 17 00:00:00 2001 From: artillect Date: Mon, 9 Jan 2023 13:43:41 -0800 Subject: [PATCH 1/3] Change abstract from code block to normal text --- README.md | 21 +-------------------- 1 file changed, 1 insertion(+), 20 deletions(-) diff --git a/README.md b/README.md index b4bfee2..be173b0 100644 --- a/README.md +++ b/README.md @@ -7,26 +7,7 @@ GPT Takes the Bar - Supplementary Information * __Publication Date__: 2022-12-29 ## Abstract -``` -Nearly all jurisdictions in the United States require a professional license exam, commonly referred to as -“the Bar Exam,” as a precondition for law practice. To even sit for the exam, most jurisdictions require -that an applicant completes at least seven years of post-secondary education, including three years at an -accredited law school. In addition, most test-takers also undergo weeks to months of further, exam-specific -preparation. Despite this significant investment of time and capital, approximately one in five test-takers -still score under the rate required to pass the exam on their first try. In the face of a complex task that -requires such depth of knowledge, what, then, should we expect of the state of the art in “AI?” In this -research, we document our experimental evaluation of the performance of OpenAI’s text-davinci-003 model, -often-referred to as GPT-3.5, on the multistate multiple choice (MBE) section of the exam. While we find no -benefit in fine-tuning over GPT-3.5’s zero-shot performance at the scale of our training data, we do find that -hyperparameter optimization and prompt engineering positively impacted GPT-3.5’s zero-shot performance. For -best prompt and parameters, GPT-3.5 achieves a headline correct rate of 50.3% on a complete NCBE MBE -practice exam, significantly in excess of the 25% baseline guessing rate, and performs at a passing rate -for both Evidence and Torts. GPT-3.5’s ranking of responses is also highly correlated with correctness; -its top two and top three choices are correct 71% and 88% of the time, respectively, indicating very strong -non-entailment performance. While our ability to interpret these results is limited by nascent scientific -understanding of LLMs and the proprietary nature of GPT, we believe that these results strongly suggest that -an LLM will pass the MBE component of the Bar Exam in the near future. -``` +Nearly all jurisdictions in the United States require a professional license exam, commonly referred to as “the Bar Exam,” as a precondition for law practice. To even sit for the exam, most jurisdictions require that an applicant completes at least seven years of post-secondary education, including three years at an accredited law school. In addition, most test-takers also undergo weeks to months of further, exam-specific preparation. Despite this significant investment of time and capital, approximately one in five test-takers still score under the rate required to pass the exam on their first try. In the face of a complex task that requires such depth of knowledge, what, then, should we expect of the state of the art in “AI?” In this research, we document our experimental evaluation of the performance of OpenAI’s text-davinci-003 model, often-referred to as GPT-3.5, on the multistate multiple choice (MBE) section of the exam. While we find no benefit in fine-tuning over GPT-3.5’s zero-shot performance at the scale of our training data, we do find that hyperparameter optimization and prompt engineering positively impacted GPT-3.5’s zero-shot performance. For best prompt and parameters, GPT-3.5 achieves a headline correct rate of 50.3% on a complete NCBE MBE practice exam, significantly in excess of the 25% baseline guessing rate, and performs at a passing rate for both Evidence and Torts. GPT-3.5’s ranking of responses is also highly correlated with correctness; its top two and top three choices are correct 71% and 88% of the time, respectively, indicating very strong non-entailment performance. While our ability to interpret these results is limited by nascent scientific understanding of LLMs and the proprietary nature of GPT, we believe that these results strongly suggest that an LLM will pass the MBE component of the Bar Exam in the near future. ### Table of Contents From c7116b29615e442277c3db22d8a13562f23c3fcb Mon Sep 17 00:00:00 2001 From: artillect Date: Mon, 9 Jan 2023 13:44:06 -0800 Subject: [PATCH 2/3] Added white background to bar chart --- accuracy_bar_chart.png | Bin 341246 -> 382474 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/accuracy_bar_chart.png b/accuracy_bar_chart.png index 783e26a781b15d931baadef2ce3baa3a71fdafd5..34d008d0edb80973367df6e633d0e66e5c9cc2e4 100644 GIT binary patch literal 382474 zcmeFYWl&wqwl<8rySwYc9fAdScXxMp3GN=8K!6Y=xVr=o5`qM`;4Z=5N%lVHo>TX| zKW^3c{`jiSs!Hv}oZX|lM-O?%GuDn)R+K_UAV2^E14EXPmQV%$vknFZ&jbepJfT4B z_zea|{Lxok+g;Vfi_F>8$NxqJ+KVS{{$Cz-tR^05&tczX6@ z(srUg!R%P;g&r$GJg-g;kuU}I`JPQMBCq%msqc8pf1;-XeLgJ 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