Identifying relevant persona or knowledge for conversational systems is critical to grounded dialogue response generation. However, each grounding has been mostly researched in isolation with more practical multi-context dialogue tasks introduced in recent works. We define Persona and Knowledge Dual Context Identification as the task to identify persona and knowledge jointly for a given dialogue, which could be of elevated importance in complex multi-context dialogue settings. We develop a novel grounding retrieval method that utilizes all contexts of dialogue simultaneously. Our method requires less computational power via utilizing neural QA retrieval models. We further introduce our novel null-positive rank test which measures ranking performance on semantically dissimilar samples (i.e. hard negatives) in relation to data augmentation.
@article{arxiv.2302.06674,
title = {PK-ICR: Persona-Knowledge Interactive Context Retrieval for Grounded Dialogue},
author = {Minsik Oh and Joosung Lee and Jiwei Li and Guoyin Wang},
journal= {arXiv preprint arXiv:2302.06674},
year = {2024}
}
Comments
Accepted to EMNLP 2023 main conference (Oral). Code available at https://github.com/minsik-ai/PK-ICR