178 citations · 486 across the 4 of their papers we have counts for
4 papers
RLTM: An Efficient Neural IR Framework for Long Documents
Chen Zheng, Yu Sun, Shengxian Wan +1
Deep neural networks have achieved significant improvements in information retrieval (IR). However, most existing models are computational costly and can not efficiently scale to l…
Match-SRNN: Modeling the Recursive Matching Structure with Spatial RNN
Shengxian Wan, Yanyan Lan, Jun Xu +3
Semantic matching, which aims to determine the matching degree between two texts, is a fundamental problem for many NLP applications. Recently, deep learning approach has been appl…
Text Matching as Image Recognition
Liang Pang, Yanyan Lan, Jiafeng Guo +3
Matching two texts is a fundamental problem in many natural language processing tasks. An effective way is to extract meaningful matching patterns from words, phrases, and sentence…
A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations
Shengxian Wan, Yanyan Lan, Jiafeng Guo +3
Matching natural language sentences is central for many applications such as information retrieval and question answering. Existing deep models rely on a single sentence representa…