4 papers
Extracting Variable-Depth Logical Document Hierarchy from Long Documents: Method, Evaluation, and Application
Rongyu Cao, Yixuan Cao, Ganbin Zhou +1
In this paper, we study the problem of extracting variable-depth "logical document hierarchy" from long documents, namely organizing the recognized "physical document objects" into…
Atom Responding Machine for Dialog Generation
Ganbin Zhou, Ping Luo, Jingwu Chen +3
Recently, improving the relevance and diversity of dialogue system has attracted wide attention. For a post x, the corresponding response y is usually diverse in the real-world cor…
Hierarchical Neural Network for Extracting Knowledgeable Snippets and Documents
Ganbin Zhou, Rongyu Cao, Xiang Ao +4
In this study, we focus on extracting knowledgeable snippets and annotating knowledgeable documents from Web corpus, consisting of the documents from social media and We-media. Inf…
Tree-Structured Neural Machine for Linguistics-Aware Sentence Generation
Ganbin Zhou, Ping Luo, Rongyu Cao +4
Different from other sequential data, sentences in natural language are structured by linguistic grammars. Previous generative conversational models with chain-structured decoder i…