35 citations · 101 across the 14 of their papers we have counts for
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cs.CL2021
Neural Attention-Aware Hierarchical Topic Model
Yuan Jin, He Zhao, Ming Liu +2
Neural topic models (NTMs) apply deep neural networks to topic modelling. Despite their success, NTMs generally ignore two important aspects: (1) only document-level word count inf…
cs.CL2020★ 35 cited
SummPip: Unsupervised Multi-Document Summarization with Sentence Graph Compression
Jinming Zhao, Ming Liu, Longxiang Gao +5
Obtaining training data for multi-document summarization (MDS) is time consuming and resource-intensive, so recent neural models can only be trained for limited domains. In this pa…
cs.CL2017★ 3 cited
MetaLDA: a Topic Model that Efficiently Incorporates Meta information
He Zhao, Lan Du, Wray Buntine +1
Besides the text content, documents and their associated words usually come with rich sets of meta informa- tion, such as categories of documents and semantic/syntactic features of…