activity
20162024
most citedAn Experimental Study of LSTM Encoder-Decoder Model for Text Simplification

35 citations · 78 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2024

Prompt-tuning for Clickbait Detection via Text Summarization

Haoxiang Deng, Yi Zhu, Ye Wang +4

Clickbaits are surprising social posts or deceptive news headlines that attempt to lure users for more clicks, which have posted at unprecedented rates for more profit or commercia…

cs.CL2023

Multilingual Lexical Simplification via Paraphrase Generation

Kang Liu, Jipeng Qiang, Yun Li +3

Lexical simplification (LS) methods based on pretrained language models have made remarkable progress, generating potential substitutes for a complex word through analysis of its c…

cs.CL2023

Sentence Simplification Using Paraphrase Corpus for Initialization

Kang Liu, Jipeng Qiang

Neural sentence simplification method based on sequence-to-sequence framework has become the mainstream method for sentence simplification (SS) task. Unfortunately, these methods a…

cs.CL20231 cited

ParaLS: Lexical Substitution via Pretrained Paraphraser

Jipeng Qiang, Kang Liu, Yun Li +2

Lexical substitution (LS) aims at finding appropriate substitutes for a target word in a sentence. Recently, LS methods based on pretrained language models have made remarkable pro…

cs.CL202322 cited

Sentence Simplification via Large Language Models

Yutao Feng, Jipeng Qiang, Yun Li +2

Sentence Simplification aims to rephrase complex sentences into simpler sentences while retaining original meaning. Large Language models (LLMs) have demonstrated the ability to pe…

cs.CL201620 cited

Topic Modeling over Short Texts by Incorporating Word Embeddings

Jipeng Qiang, Ping Chen, Tong Wang +1

Inferring topics from the overwhelming amount of short texts becomes a critical but challenging task for many content analysis tasks, such as content charactering, user interest pr…