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20182025
most citedA Hierarchical Structured Self-Attentive Model for Extractive Document Summarization (HSSAS)

131 citations · 194 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CL2024★ 9 cited

Multi-head Sequence Tagging Model for Grammatical Error Correction

Kamal Al-Sabahi, Kang Yang, Wangwang Liu +3

To solve the Grammatical Error Correction (GEC) problem , a mapping between a source sequence and a target one is needed, where the two differ only on few spans. For this reason, t…

cs.CL2018★ 18 cited

Bidirectional Attentional Encoder-Decoder Model and Bidirectional Beam Search for Abstractive Summarization

Kamal Al-Sabahi, Zhang Zuping, Yang Kang

Sequence generative models with RNN variants, such as LSTM, GRU, show promising performance on abstractive document summarization. However, they still have some issues that limit t…

cs.CL2018★ 33 cited

An Enhanced Latent Semantic Analysis Approach for Arabic Document Summarization

Kamal Al-Sabahi, Zuping Zhang, Jun Long +1

The fast-growing amount of information on the Internet makes the research in automatic document summarization very urgent. It is an effective solution for information overload. Man…

cs.CL2018★ 3 cited

Latent Semantic Analysis Approach for Document Summarization Based on Word Embeddings

Kamal Al-Sabahi, Zhang Zuping, Yang Kang

Since the amount of information on the internet is growing rapidly, it is not easy for a user to find relevant information for his/her query. To tackle this issue, much attention h…

cs.CL2018★ 131 cited

A Hierarchical Structured Self-Attentive Model for Extractive Document Summarization (HSSAS)

Kamal Al-Sabahi, Zhang Zuping, Mohammed Nadher

The recent advance in neural network architecture and training algorithms have shown the effectiveness of representation learning. The neural network-based models generate better r…