activity
20182022
most citedLearning to Generate Questions by Learning What not to Generate

105 citations · 146 across the 3 of their papers we have counts for

collaborators

7 papers

cs.AI20222 cited

R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning

Shengyao Lu, Bang Liu, Keith G. Mills +2

Systematicity, i.e., the ability to recombine known parts and rules to form new sequences while reasoning over relational data, is critical to machine intelligence. A model with st…

cs.CL201939 cited

Multiresolution Graph Attention Networks for Relevance Matching

Ting Zhang, Bang Liu, Di Niu +2

A large number of deep learning models have been proposed for the text matching problem, which is at the core of various typical natural language processing (NLP) tasks. However, e…

cs.CL2019105 cited

Learning to Generate Questions by Learning What not to Generate

Bang Liu, Mingjun Zhao, Di Niu +4

Automatic question generation is an important technique that can improve the training of question answering, help chatbots to start or continue a conversation with humans, and prov…

cs.CE2018

House Price Modeling over Heterogeneous Regions with Hierarchical Spatial Functional Analysis

Bang Liu, Borislav Mavrin, Di Niu +1

Online real-estate information systems such as Zillow and Trulia have gained increasing popularity in recent years. One important feature offered by these systems is the online hom…

cs.IR2018

Growing Story Forest Online from Massive Breaking News

Bang Liu, Di Niu, Kunfeng Lai +2

We describe our experience of implementing a news content organization system at Tencent that discovers events from vast streams of breaking news and evolves news story structures…

cs.CL2018

Matching Natural Language Sentences with Hierarchical Sentence Factorization

Bang Liu, Ting Zhang, Fred X. Han +3

Semantic matching of natural language sentences or identifying the relationship between two sentences is a core research problem underlying many natural language tasks. Depending o…