all AI news
TOAD: Task-Oriented Automatic Dialogs with Diverse Response Styles
Feb. 16, 2024, 5:47 a.m. | Yinhong Liu, Yimai Fang, David Vandyke, Nigel Collier
cs.CL updates on arXiv.org arxiv.org
Abstract: In light of recent advances in large language models~(LLMs), the expectations for the next generation of virtual assistants include enhanced naturalness and adaptability across diverse usage scenarios. However, the creation of high-quality annotated data for Task-Oriented Dialog~(TOD) is recognized to be slow and costly. To address these challenges, we introduce Task-Oriented Automatic Dialogs~(TOAD), a novel and scalable TOD dataset along with its automatic generation pipeline. The TOAD dataset simulates realistic app context interaction and provide …
abstract adaptability advances annotated data arxiv assistants cs.cl data dialog diverse language language models large language large language models light llms next quality type usage virtual virtual assistants
More from arxiv.org / cs.CL updates on arXiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
#13721 - Data Engineer - AI Model Testing
@ Qualitest | Miami, Florida, United States
Elasticsearch Administrator
@ ManTech | 201BF - Customer Site, Chantilly, VA