43 citations · 78 across the 2 of their papers we have counts for
4 papers
Federated Learning Meets Natural Language Processing: A Survey
Ming Liu, Stella Ho, Mengqi Wang +3
Federated Learning aims to learn machine learning models from multiple decentralized edge devices (e.g. mobiles) or servers without sacrificing local data privacy. Recent Natural L…
SciSummPip: An Unsupervised Scientific Paper Summarization Pipeline
Jiaxin Ju, Ming Liu, Longxiang Gao +1
The Scholarly Document Processing (SDP) workshop is to encourage more efforts on natural language understanding of scientific task. It contains three shared tasks and we participat…
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…
Variational Auto-encoder Based Bayesian Poisson Tensor Factorization for Sparse and Imbalanced Count Data
Yuan Jin, Ming Liu, Yunfeng Li +4
Non-negative tensor factorization models enable predictive analysis on count data. Among them, Bayesian Poisson-Gamma models can derive full posterior distributions of latent facto…