PRIME

Published:

GitHub Repo

Introduction:

We release Intention-in-Interaction (IN3) benchmark and develop Mistral-Interact, capable of discerning vague instructions and recovering missing details. Mistral-Interact has the following features:

  • Better understanding of user judgments: Among all the open-source models, Mistral-Interact is the best at predicting task vagueness and missing details that users regard as necessary.

  • Comprehensive summarization of user intentions: Mistral-Interact is effective in making an explicit and comprehensive summary based on detailed user intentions.

  • Enhanced model-user interaction experience: Mistral-Interact inquires about missing details in vague tasks more reasonably and friendly than other open-source models, thus promoting a clearer understanding of the user’s implicit intentions.

  • Comparable performance with closed-source GPT-4: We prove that smaller-scale model experts can approach or even exceed general-purpose large-scale models across various aspects including vagueness judgment, comprehensiveness of summaries, and friendliness of interaction.