2 datasets found

The paper presents a study on the impact of synthetic data on large language models (LLMs) and proposes a method to steer LLMs towards desirable non-differentiable attributes.

This paper uses SummEval and Topical-Chat datasets for evaluating the quality of summaries and responses.