Buckets:
| license: cc-by-4.0 | |
| task_categories: | |
| - text2text-generation | |
| language: | |
| - en | |
| size_categories: | |
| - 10K<n<100K | |
| # Dataset Card for SPC: Synthetic-Persona-Chat Dataset | |
| Abstract from the paper introducing this dataset: | |
| > High-quality conversational datasets are essential for developing AI models that can communicate with users. One way to foster deeper interactions between a chatbot and its user is through personas, aspects of the user's character that provide insights into their personality, motivations, and behaviors. Training Natural Language Processing (NLP) models on a diverse and comprehensive persona-based dataset can lead to conversational models that create a deeper connection with the user, and maintain their engagement. In this paper, we leverage the power of Large Language Models (LLMs) to create a large, high-quality conversational dataset from a seed dataset. We propose a Generator-Critic architecture framework to expand the initial dataset, while improving the quality of its conversations. The Generator is an LLM prompted to output conversations. The Critic consists of a mixture of expert LLMs that control the quality of the generated conversations. These experts select the best generated conversations, which we then use to improve the Generator. We release Synthetic-Persona-Chat, consisting of 20k conversations seeded from Persona-Chat. We evaluate the quality of Synthetic-Persona-Chat and our generation framework on different dimensions through extensive experiments, and observe that the losing rate of Synthetic-Persona-Chat against Persona-Chat during Turing test decreases from 17.2% to 8.8% over three iterations. | |
| ## Dataset Details | |
| ### Dataset Description | |
| > We introduce the Synthetic-Persona-Chat dataset, a persona-based conversational dataset, consisting of two parts. The first part, consisting of 4,723 personas and 10,906 conversations, is an extension to Persona-Chat, which has the same user profile pairs as Persona-Chat but new synthetic conversations, with the same train/validation/test split as Persona-Chat. The second part is new synthetic personas and synthetic conversations based on that, consisting of 5,648 synthetic personas and 11,001 conversations. Synthetic-Persona-Chat is created using the Generator-Critic framework introduced in Faithful Persona-based Conversational Dataset Generation with Large Language Models. | |
| Each conversation in the dataset has the following format: | |
| ``` | |
| { | |
| "User 1 Persona":[], | |
| "User 2 Persona":[], | |
| "Conversation":[] | |
| } | |
| ``` | |
| ### Dataset Sources | |
| <!-- Provide the basic links for the dataset. --> | |
| - **Repository:** https://github.com/google-research-datasets/Synthetic-Persona-Chat/tree/main | |
| - **Paper:** https://arxiv.org/abs/2312.10007 | |
| ## Citation | |
| **BibTeX:** | |
| ```@misc{jandaghi2023faithful, | |
| title={Faithful Persona-based Conversational Dataset Generation with Large Language Models}, | |
| author={Pegah Jandaghi and XiangHai Sheng and Xinyi Bai and Jay Pujara and Hakim Sidahmed}, | |
| year={2023}, | |
| eprint={2312.10007}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL} | |
| } | |
| ``` |
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