Prompts generated from ChatGPT3.5, ChatGPT4, LLama3-8B, and Mistral-7B with NYT and HC3 topics in different roles and parameters configurations

The dataset is useful to study lexical aspects of LLMs with different parameters/roles configurations. - The 0_Base_Topics.xlsx file lists the topics used for the dataset generation - The rest of the files collect the answers of ChatGPT to these topics with different configurations of parameters/context: -- Temperature (parameter): Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. --Frequency penalty (parameter): Number between -2.0 and 2.0.

Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. -- Top probability (parameter): An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. -- Presence penalty (parameter): Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. -- Roles (context) --- Default: No role is assigned to the LLM, the default role is used. --- Child: The LLM is requested to answer as a five-year-old child. --- Young adult male: The LLM is requested to answer as a young male adult. --- Young adult female: The LLM is requested to answer as a young female adult. --- Elderly adult male: The LLM is requested to answer as an elderly male adult. --- Elderly adult female: The LLM is requested to answer as an elderly female adult. --- Affluent adult male: The LLM is requested to answer as an affluent male adult. --- Affluent adult female: The LLM is requested to answer as an affluent female adult. --- Lower-class adult male: The LLM is requested to answer as a lower-class male adult. --- Lower-class adult female: The LLM is requested to answer as a lower-class female adult. --- Erudite: The LLM is requested to answer as an erudite who uses a rich vocabulary.