64 citations · 108 across the 7 of their papers we have counts for
8 papers
Generating Sentences from Disentangled Syntactic and Semantic Spaces
Yu Bao, Hao Zhou, Shujian Huang +5
Variational auto-encoders (VAEs) are widely used in natural language generation due to the regularization of the latent space. However, generating sentences from the continuous lat…
An Imitation Learning Approach to Unsupervised Parsing
Bowen Li, Lili Mou, Frank Keller
Recently, there has been an increasing interest in unsupervised parsers that optimize semantically oriented objectives, typically using reinforcement learning. Unfortunately, the l…
Modeling Past and Future for Neural Machine Translation
Zaixiang Zheng, Hao Zhou, Shujian Huang +4
Existing neural machine translation systems do not explicitly model what has been translated and what has not during the decoding phase. To address this problem, we propose a novel…
Why Do Neural Dialog Systems Generate Short and Meaningless Replies? A Comparison between Dialog and Translation
Bolin Wei, Shuai Lu, Lili Mou +4
This paper addresses the question: Why do neural dialog systems generate short and meaningless replies? We conjecture that, in a dialog system, an utterance may have multiple equal…
Affective Neural Response Generation
Nabiha Asghar, Pascal Poupart, Jesse Hoey +2
Existing neural conversational models process natural language primarily on a lexico-syntactic level, thereby ignoring one of the most crucial components of human-to-human dialogue…
Order-Planning Neural Text Generation From Structured Data
Lei Sha, Lili Mou, Tianyu Liu +4
Generating texts from structured data (e.g., a table) is important for various natural language processing tasks such as question answering and dialog systems. In recent studies, r…