Fetching the paper…
Reading the bibliography…
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 news portals and social media.
Click bait: Forward-reference as lure in online news headlines
Jonas Nygaard Blom and Kenneth Reinecke Hansen · 2015
Earlier work this paper cites.
Misleading online content: recognizing clickbait as ”false news”
Yimin Chen, Niall J Conroy, and Victoria L Rubin · 2015
Earlier work this paper cites.
Clickbait detection using deep learning
Amol Agrawal · 2016
Earlier work this paper cites.
”8 amazing secrets for getting more clicks”: detecting clickbaits in news streams using article informality
Prakhar Biyani, Kostas Tsioutsiouliklis, and John Blackmer · 2016
Earlier work this paper cites.
Stop clickbait: Detecting and preventing clickbaits in online news media
Abhijnan Chakraborty, Bhargavi Paranjape, Sourya Kakarla, and Niloy Ganguly · 2016
Earlier work this paper cites.
Bag of tricks for efficient text classification
Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov · 2016
Earlier work this paper cites.
We used neural networks to detect clickbaits: You won’t believe what happened next!
Ankesh Anand, Tanmoy Chakraborty, and Noseong Park · 2017
Earlier work this paper cites.
Diving deep into clickbaits: Who use them to what extents in which topics with what effects?
Md Main Uddin Rony, Naeemul Hassan, and Mohammad Yousuf · 2017
Earlier work this paper cites.
Learning to identify ambiguous and misleading news headlines
Wei Wei and Xiaojun Wan · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
Identifying clickbait: A multi-strategy approach using neural networks
Vaibhav Kumar, Dhruv Khattar, Siddhartha Gairola, Yash Kumar Lal, and Vasudeva Varma · 2018
Cited alongside, same era.
Hybridizing metric learning and case-based reasoning for adaptable clickbait detection
Daniel López-Sánchez, Jorge Revuelta Herrero, Angélica González Arrieta, and Juan M Corchado · 2018
Cited alongside, same era.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
Later among the works it cites.
A deep model based on lure and similarity for adaptive clickbait detection
Jiaming Zheng, Ke Yu, and Xiaofei Wu · 2021
Later among the works it cites.
Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al · 2022
Later among the works it cites.
Clickbait detection on wechat: A deep model integrating semantic and syntactic information
Tong Liu, Ke Yu, Lu Wang, Xuanyu Zhang, Hao Zhou, and Xiaofei Wu · 2022
Later among the works it cites.
Lamda: Language models for dialog applications
Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, et al · 2022
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Kai-Chou Yang, Timothy Niven, and Hung-Yu Kao · 2019
Cited alongside, same era.
Detecting incongruity between news headline and body text via a deep hierarchical encoder
Seunghyun Yoon, Kunwoo Park, Joongbo Shin, Hongjun Lim, Seungpil Won, Meeyoung Cha, and Kyomin Jung · 2019
Cited alongside, same era.
Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Cited alongside, same era.
Predicting clickbait strength in online social media
Vijayasaradhi Indurthi, Bakhtiyar Syed, Manish Gupta, and Vasudeva Varma · 2020
Cited alongside, same era.
Musem: Detecting incongruent news headlines using mutual attentive semantic matching
Rahul Mishra, Piyush Yadav, Remi Calizzano, and Markus Leippold · 2020
Cited alongside, same era.
Later among the works it cites.
Clickbait detection via contrastive variational modelling of text and label
Xiaoyuan Yi, Jiarui Zhang, Wenhao Li, Xiting Wang, and Xing Xie · 2022
Later among the works it cites.
Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig · 2023
Closest in time.
Detecting clickbait in chinese social media by prompt learning
Yin Wu, Mingpei Cao, Yueze Zhang, and Yong Jiang · 2023
Closest in time.