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Following the hype around OpenAI's ChatGPT conversational agent, the laststraw in the recent development of Large Language Models (LLMs) thatdemonstrate emergent unprecedented zero-shot capabilities, we audit the latestOpenAI's GPT-3.5 model, `gpt-3.5-turbo', the first available ChatGPT model, inthe LexGLUE benchmark in a zero-shot fashion providing examples in a templatedinstruction-following format. The results indicate that ChatGPT achieves anaverage micro-F1 score of 47.6% across LexGLUE tasks, surpassing the baselineguessing rates. Notably, the model performs exceptionally well in somedatasets, achieving micro-F1 scores of 62.8% and 70.2% in the ECtHR B andLEDGAR datasets, respectively. The code base and model predictions areavailable for review on https://github.com/coastalcph/zeroshot_lexglue.

ChatGPT may Pass the Bar Exam soon, but has a Long Way to Go for the LexGLUE benchmark