Grading Conversational Responses Of Chatbots
This work provides a benchmark for evaluating chatbot conversational quality, though it is incremental as it applies existing metrics to a new model.
The paper analyzed ChatGPT's responses to 60 Quora questions using BLEU, METEOR, and ROUGE metrics, finding that while its performance is remarkable, it still falls short of typical human replies.
Chatbots have long been capable of answering basic questions and even responding to obscure prompts, but recently their improvements have been far more significant. Modern chatbots like Open AIs ChatGPT3 not only have the ability to answer basic questions but can write code and movie scripts and imitate well-known people. In this paper, we analyze ChatGPTs' responses to various questions from a dataset of queries from the popular Quora forum. We submitted sixty questions to ChatGPT and scored the answers based on three industry-standard metrics for grading machine translation: BLEU, METEOR, and ROUGE. These metrics allow us to compare the machine responses with the most upvoted human answer to the same question to assess ChatGPT's ability to submit a humanistic reply. The results showed that while the responses and translation abilities of ChatGPT are remarkable, they still fall short of what a typical human reaction would be.