Fetching the paper…
Reading the bibliography…
Detecting fake news requires both a delicate sense of diverse clues and a profound understanding of the real-world background, which remains challenging for detectors based on small language models (SLMs) due to their knowledge and capability limitations.
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, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
Earlier work this paper cites.
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 · 1907
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015 · 2015
Earlier work this paper cites.
Pizzagate: From rumor, to hashtag, to gunfire in dc
Marc Fisher, John Woodrow Cox, and Peter Hermann. 2016 · 2016
Earlier work this paper cites.
Fake news detection on social media: A data mining perspective
Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang, and Huan Liu. 2017 · 2017
Earlier work this paper cites.
DeClarE: Debunking fake news and false claims using evidence-aware deep learning
Kashyap Popat, Subhabrata Mukherjee, Andrew Yates, and Gerhard Weikum. 2018 · 2018
Earlier work this paper cites.
EANN: Event adversarial neural networks for multi-modal fake news detection
Yaqing Wang, Fenglong Ma, Zhiwei Jin, Ye Yuan, Guangxu Xun, Kishlay Jha, Lu Su, and Jing Gao. 2018 · 2018
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. 2019 · 2019
Earlier work this paper cites.
dEFEND: Explainable fake news detection
Kai Shu, Limeng Cui, Suhang Wang, Dongwon Lee, and Huan Liu. 2019 · 2019
Earlier work this paper cites.
Network-based fake news detection: A pattern-driven approach
Xinyi Zhou and Reza Zafarani. 2019 · 2019
Earlier work this paper cites.
The COVID-19 ‘infodemic’: a new front for information professionals
Salman Bin Naeem and Rubina Bhatti. 2020 · 2020
Earlier work this paper cites.
FANG: Leveraging social context for fake news detection using graph representation
Van-Hoang Nguyen, Kazunari Sugiyama, Preslav Nakov, and Min-Yen Kan. 2020 · 2020
Earlier work this paper cites.
Capturing the style of fake news
Piotr Przybyla. 2020 · 2020
Earlier work this paper cites.
FakeNewsNet: A data repository with news content, social context and spatiotemporal information for studying fake news on social media
Kai Shu, Deepak Mahudeswaran, Suhang Wang, Dongwon Lee, and Huan Liu. 2020 · 2020
Earlier work this paper cites.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
Cited alongside, same era.
FakeBERT: Fake news detection in social media with a BERT-based deep learning approach
Rohit Kumar Kaliyar, Anurag Goswami, and Pratik Narang. 2021 · 2021
Cited alongside, same era.
MDFEND: Multi-domain fake news detection
Qiong Nan, Juan Cao, Yongchun Zhu, Yanyan Wang, and Jintao Li. 2021 · 2021
Cited alongside, same era.
Improving fake news detection by using an entity-enhanced framework to fuse diverse multimodal clues
Peng Qi, Juan Cao, Xirong Li, Huan Liu, Qiang Sheng, Xiaoyue Mi, Qin He, Yongbiao Lv, Chenyang Guo, and Yingchao Yu. 2021 · 2021
Cited alongside, same era.
Integrating pattern-and fact-based fake news detection via model preference learning
Qiang Sheng, Xueyao Zhang, Juan Cao, and Lei Zhong. 2021 · 2021
The economic cost of bad actors on the internet
CHEQ. 2019 · 2023
Closest in time.
Learn over past, evolve for future: Forecasting temporal trends for fake news detection
Beizhe Hu, Qiang Sheng, Juan Cao, Yongchun Zhu, Danding Wang, Zhengjia Wang, and Zhiwei Jin. 2023 · 2023
Closest in time.
Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung. 2023 · 2023
Closest in time.
ChatGPT: Jack of all trades, master of none
Jan Kocoń, Igor Cichecki, Oliwier Kaszyca, Mateusz Kochanek, Dominika Szydło, Joanna Baran, Julita Bielaniewicz, Marcin Gruza, Arkadiusz Janz, Kamil Kanclerz, Anna Kocoń, Bartłomiej Koptyra, Wiktoria Mieleszczenko-Kowszewicz, Piotr Miłkowski, Marcin Oleksy, Maciej Piasecki, Łukasz Radliński, Konrad Wojtasik, Stanisław Woźniak, and Przemysław Kazienko. 2023 · 2023
Closest in time.
Yubo Ma, Yixin Cao, YongChing Hong, and Aixin Sun. 2023 · 2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Mining dual emotion for fake news detection
Xueyao Zhang, Juan Cao, Xirong Li, Qiang Sheng, Lei Zhong, and Kai Shu. 2021 · 2021
Cited alongside, same era.
Meta-path-based fake news detection leveraging multi-level social context information
Jian Cui, Kwanwoo Kim, Seung Ho Na, and Seungwon Shin. 2022 · 2022
Cited alongside, same era.
CHEF: A pilot Chinese dataset for evidence-based fact-checking
Xuming Hu, Zhijiang Guo, GuanYu Wu, Aiwei Liu, Lijie Wen, and Philip Yu. 2022b · 2022
Cited alongside, same era.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Cited alongside, same era.
Divide-and-conquer: Post-user interaction network for fake news detection on social media
Erxue Min, Yu Rong, Yatao Bian, Tingyang Xu, Peilin Zhao, Junzhou Huang, and Sophia Ananiadou. 2022 · 2022
Cited alongside, same era.
Domain adaptive fake news detection via reinforcement learning
Ahmadreza Mosallanezhad, Mansooreh Karami, Kai Shu, Michelle V. Mancenido, and Huan Liu. 2022 · 2022
Cited alongside, same era.
Zoom out and observe: News environment perception for fake news detection
Qiang Sheng, Juan Cao, Xueyao Zhang, Rundong Li, Danding Wang, and Yongchun Zhu. 2022 · 2022
Cited alongside, same era.
Closest in time.
It’s about time: Rethinking evaluation on rumor detection benchmarks using chronological splits
Yida Mu, Kalina Bontcheva, and Nikolaos Aletras. 2023 · 2023
Closest in time.
ChatGPT: Optimizing language models for dialogue
OpenAI. 2022 · 2023
Closest in time.
Towards reliable misinformation mitigation: Generalization, uncertainty, and GPT-4
Kellin Pelrine, Meilina Reksoprodjo, Caleb Gupta, Joel Christoph, and Reihaneh Rabbany. 2023 · 2023
Closest in time.
Role-playing in large language models like ChatGPT
Sunil Ramlochan. 2023 · 2023
Closest in time.
The vast majority of content we take action on for misinformation is identified proactively
Yoel Roth. 2022 · 2023
Closest in time.
LLaMA: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023 · 2023
Closest in time.
Small models are valuable plug-ins for large language models
Canwen Xu, Yichong Xu, Shuohang Wang, Yang Liu, Chenguang Zhu, and Julian McAuley. 2023 · 2023
Closest in time.
Siren’s song in the AI ocean: A survey on hallucination in large language models
Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, Lemao Liu, Tingchen Fu, Xinting Huang, Enbo Zhao, Yu Zhang, Yulong Chen, Longyue Wang, Anh Tuan Luu, Wei Bi, Freda Shi, and Shuming Shi. 2023 · 2023
Closest in time.
A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, Yifan Du, Chen Yang, Yushuo Chen, Zhipeng Chen, Jinhao Jiang, Ruiyang Ren, Yifan Li, Xinyu Tang, Zikang Liu, Peiyu Liu, Jian-Yun Nie, and Ji-Rong Wen. 2023 · 2023
Closest in time.
Can ChatGPT understand too? a comparative study on ChatGPT and fine-tuned BERT
Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, and Dacheng Tao. 2023 · 2023
Closest in time.