972 citations · 2.3k across the 31 of their papers we have counts for
10 papers · 1 filter
Neural Generative Question Answering
Jun Yin, Xin Jiang, Zhengdong Lu +3
This paper presents an end-to-end neural network model, named Neural Generative Question Answering (GENQA), that can generate answers to simple factoid questions, based on the fact…
Towards Neural Network-based Reasoning
Baolin Peng, Zhengdong Lu, Hang Li +1
We propose Neural Reasoner, a framework for neural network-based reasoning over natural language sentences. Given a question, Neural Reasoner can infer over multiple supporting fac…
A Deep Memory-based Architecture for Sequence-to-Sequence Learning
Fandong Meng, Zhengdong Lu, Zhaopeng Tu +2
We propose DEEPMEMORY, a novel deep architecture for sequence-to-sequence learning, which performs the task through a series of nonlinear transformations from the representation of…
Learning to Answer Questions From Image Using Convolutional Neural Network
Lin Ma, Zhengdong Lu, Hang Li
In this paper, we propose to employ the convolutional neural network (CNN) for the image question answering (QA). Our proposed CNN provides an end-to-end framework with convolution…
Neural Responding Machine for Short-Text Conversation
Lifeng Shang, Zhengdong Lu, Hang Li
We propose Neural Responding Machine (NRM), a neural network-based response generator for Short-Text Conversation. NRM takes the general encoder-decoder framework: it formalizes th…
CNN: A Convolutional Architecture for Word Sequence Prediction
Mingxuan Wang, Zhengdong Lu, Hang Li +2
We propose a novel convolutional architecture, named CNN, for word sequence prediction. Different from previous work on neural network-based language modeling and generation (…