22 citations · 46 across the 15 of their papers we have counts for
17 papers
Let the Bullets Fly: Multimodal Fake News Detection with Temporal-Aligned Generative Danmaku
Xiansheng Luo, Chaowei Zhang, Zewei Zhang +2
The social interactions among crowds via \textit{Danmaku} (a.k.a., bullet comments) on modern multimedia platforms can facilitate both viewpoint conflicts and consensus, providing…
Acting Flatterers via LLMs Sycophancy: Combating Clickbait with LLMs Opposing-Stance Reasoning
Chaowei Zhang, Xiansheng Luo, Zewei Zhang +3
The widespread proliferation of online content has intensified concerns about clickbait, deceptive or exaggerated headlines designed to attract attention. While Large Language Mode…
AI4Reading: Chinese Audiobook Interpretation System Based on Multi-Agent Collaboration
Minjiang Huang, Jipeng Qiang, Yi Zhu +3
Audiobook interpretations are attracting increasing attention, as they provide accessible and in-depth analyses of books that offer readers practical insights and intellectual insp…
Chinese Cyberbullying Detection: Dataset, Method, and Validation
Yi Zhu, Xin Zou, Xindong Wu
Existing cyberbullying detection benchmarks were organized by the polarity of speech, such as "offensive" and "non-offensive", which were essentially hate speech detection. However…
Redefining Simplicity: Benchmarking Large Language Models from Lexical to Document Simplification
Jipeng Qiang, Minjiang Huang, Yi Zhu +3
Text simplification (TS) refers to the process of reducing the complexity of a text while retaining its original meaning and key information. Existing work only shows that large la…
New Evaluation Paradigm for Lexical Simplification
Jipeng Qiang, Minjiang Huang, Yi Zhu +3
Lexical Simplification (LS) methods use a three-step pipeline: complex word identification, substitute generation, and substitute ranking, each with separate evaluation datasets. W…
Progressive Document-level Text Simplification via Large Language Models
Dengzhao Fang, Jipeng Qiang, Yi Zhu +3
Research on text simplification has primarily focused on lexical and sentence-level changes. Long document-level simplification (DS) is still relatively unexplored. Large Language…
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…
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…
Clickbait Detection via Large Language Models
Han Wang, Yi Zhu, Ye Wang +3
Clickbait, which aims to induce users with some surprising and even thrilling headlines for increasing click-through rates, permeates almost all online content publishers, such as…
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…
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…
Chinese Idiom Paraphrasing
Jipeng Qiang, Yang Li, Chaowei Zhang +4
Idioms, are a kind of idiomatic expression in Chinese, most of which consist of four Chinese characters. Due to the properties of non-compositionality and metaphorical meaning, Chi…
Prompt-Learning for Short Text Classification
Yi Zhu, Xinke Zhou, Jipeng Qiang +3
In the short text, the extremely short length, feature sparsity, and high ambiguity pose huge challenges to classification tasks. Recently, as an effective method for tuning Pre-tr…
An Unsupervised Method for Building Sentence Simplification Corpora in Multiple Languages
Xinyu Lu, Jipeng Qiang, Yun Li +2
The availability of parallel sentence simplification (SS) is scarce for neural SS modelings. We propose an unsupervised method to build SS corpora from large-scale bilingual transl…
LSBert: A Simple Framework for Lexical Simplification
Jipeng Qiang, Yun Li, Yi Zhu +2
Lexical simplification (LS) aims to replace complex words in a given sentence with their simpler alternatives of equivalent meaning, to simplify the sentence. Recently unsupervised…
Lexical Simplification with Pretrained Encoders
Jipeng Qiang, Yun Li, Yi Zhu +2
Lexical simplification (LS) aims to replace complex words in a given sentence with their simpler alternatives of equivalent meaning. Recently unsupervised lexical simplification ap…