Characterizing Similarities and Divergences in Conversational Tones in Humans and LLMs by Sampling with People (2024.acl-long)
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| Challenge: | Existing taxonomies or text corpora suffer from experimenter bias and are not representative of real-world distributions. |
| Approach: | They propose an iterative method for simultaneously eliciting conversational tones and sentences . they run 50 iterations with human participants and GPT-4 and obtain a dataset of sentences and frequent conversational tone. |
| Outcome: | The proposed method can be used to characterize the differences between humans and LLMs. |
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| Challenge: | In this paper, we examine how large language models adapt their language use to the linguistic patterns of their user. |
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