RESEARCH

NLP

Personalizing Dialogue Agents: I have a dog, do you have pets too?

July 15, 2018

Abstract

Chit-chat models are known to have several problems: they lack specificity, do not display a consistent personality and are often not very captivating. In this work we present the task of making chit-chat more engaging by conditioning on profile information. We collect data and train models to (i) condition on their given profile information; and (ii) information about the person they are talking to, resulting in improved dialogues, as measured by next utterance prediction. Since (ii) is initially unknown, our model is trained to engage its partner with personal topics, and we show the resulting dialogue can be used to predict profile information about the interlocutors.

Download the Paper

Related Publications

August 01, 2019

NLP

Simple and Effective Curriculum Pointer-Generator Networks for Reading Comprehension over Long Narratives | Facebook AI Research

Yi Tay, Shuohang Wang, Luu Anh Tuan, Jie Fu, Minh C. Phan, Xingdi Yuan, Jinfeng Rao, Siu Cheung Hui, Aston Zhang

August 01, 2019

July 27, 2019

NLP

Unsupervised Question Answering by Cloze Translation | Facebook AI Research

Patrick Lewis, Ludovic Denoyer, Sebastian Riedel

July 27, 2019

September 10, 2019

NLP

Bridging the Gap Between Relevance Matching and Semantic Matching for Short Text Similarity Modeling | Facebook AI Research

Jinfeng Rao, Linqing Liu, Yi Tay, Wei Yang, Peng Shi, Jimmy Lin

September 10, 2019

May 17, 2019

NLP

Unsupervised Hyper-alignment for Multilingual Word Embeddings | Facebook AI Research

Jean Alaux, Edouard Grave, Marco Cuturi, Armand Joulin

May 17, 2019

Help Us Pioneer The Future of AI

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.