October 31, 2018
The use of connectionist approaches in conversational agents has been progressing rapidly due to the availability of large corpora. However current generative dialogue models often lack coherence and are content poor. This work proposes an architecture to incorporate unstructured knowledge sources to enhance the next utterance prediction in chit-chat type of generative dialogue models. We focus on Sequence-to-Sequence (Seq2Seq) conversational agents trained with the Reddit News dataset, and consider incorporating external knowledge from Wikipedia summaries as well as from the NELL knowledge base. Our experiments show faster training time and improved perplexity when leveraging external knowledge.
Publisher
EMNLP
July 23, 2024
Llama team
July 23, 2024
May 06, 2024
Gregoire Mialon, Yann LeCun, Thomas Scialom, Clémentine Fourrier, Thomas Wolf
May 06, 2024
April 23, 2024
Sachit Menon, Ishan Misra, Rohit Girdhar
April 23, 2024
April 05, 2024
Suyu Ge, Chunting Zhou, Rui Hou, Madian Khabsa, Yi-Chia Wang, Qifan Wang, Jiawei Han, Yuning Mao
April 05, 2024
Product experiences
Foundational models
Product experiences
Latest news
Foundational models