77 citations · 732 across the 55 of their papers we have counts for
7 papers · 1 filter
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…
Variational Attention for Sequence-to-Sequence Models
Hareesh Bahuleyan, Lili Mou, Olga Vechtomova +1
The variational encoder-decoder (VED) encodes source information as a set of random variables using a neural network, which in turn is decoded into target data using another neural…
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…
On Improving Deep Reinforcement Learning for POMDPs
Pengfei Zhu, Xin Li, Pascal Poupart +1
Deep Reinforcement Learning (RL) recently emerged as one of the most competitive approaches for learning in sequential decision making problems with fully observable environments,…
Generative Mixture of Networks
Ershad Banijamali, Ali Ghodsi, Pascal Poupart
A generative model based on training deep architectures is proposed. The model consists of K networks that are trained together to learn the underlying distribution of a given data…