AiSocrates: Towards Answering Ethical Quandary Questions. (arXiv:2205.05989v1 [cs.CL])

Web: http://arxiv.org/abs/2205.05989

Considerable advancements have been made in various NLP tasks based on the
impressive power of large pre-trained language models (LLMs). These results
have inspired efforts to understand the limits of LLMs so as to evaluate how
far we are from achieving human level general natural language understanding.
In this work, we challenge the capability of LLMs with the new task of Ethical
Quandary Generative Question Answering. Ethical quandary questions are more
challenging to address because multiple conflicting answers may exist …

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