8 papers
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…
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…
Is LLMs Hallucination Usable? LLM-based Negative Reasoning for Fake News Detection
Chaowei Zhang, Zongling Feng, Zewei Zhang +3
The questionable responses caused by knowledge hallucination may lead to LLMs' unstable ability in decision-making. However, it has never been investigated whether the LLMs' halluc…
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…