Saved You A Click: Automatically Answering Clickbait Titles
원문 초록
Often clickbait articles have a title that is phrased as a question or vague teaser that entices the user to click on the link and read the article to find the explanation. We developed a system that will automatically find the answer or explanation of the clickbait hook from the website text so that the user does not need to read through the text themselves. We fine-tune an extractive question and answering model (RoBERTa) and an abstractive one (T5), using data scraped from the 'StopClickbait' Facebook pages and Reddit's 'SavedYouAClick' subforum. We find that both extractive and abstractive models improve significantly after finetuning. We find that the extractive model performs slightly better according to ROUGE scores, while the abstractive one has a slight edge in terms of BERTscores.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
AI Wizards at CheckThat! 2025: Enhancing Transformer-Based Embeddings with Sentiment for Subjectivity Detection in News Articles
Remember Past, Anticipate Future: Learning Continual Multimodal Misinformation Detectors
Narrative Shift Detection: A Hybrid Approach of Dynamic Topic Models and Large Language Models
Characterizing Linguistic Shifts in Croatian News via Diachronic Word Embeddings
How Grounded is Wikipedia? A Study on Structured Evidential Support
Intent Factored Generation: Unleashing the Diversity in Your Language Model
토론
이 논문과 연결된 포럼 글이 아직 없습니다.