43 citations · 78 across the 5 of their papers we have counts for
7 papers · 1 filter
How Far are We from Robust Long Abstractive Summarization?
Huan Yee Koh, Jiaxin Ju, He Zhang +2
Abstractive summarization has made tremendous progress in recent years. In this work, we perform fine-grained human annotations to evaluate long document abstractive summarization…
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…
Transformer over Pre-trained Transformer for Neural Text Segmentation with Enhanced Topic Coherence
Kelvin Lo, Yuan Jin, Weicong Tan +3
This paper proposes a transformer over transformer framework, called Transformer, to perform neural text segmentation. It consists of two components: bottom-level sentence enco…
Leveraging Information Bottleneck for Scientific Document Summarization
Jiaxin Ju, Ming Liu, Huan Yee Koh +3
This paper presents an unsupervised extractive approach to summarize scientific long documents based on the Information Bottleneck principle. Inspired by previous work which uses t…
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…