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Evidence retrieval is a core part of automatic fact-checking.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
Earlier work this paper cites.
Fact checking: Task definition and dataset construction
Andreas Vlachos and Sebastian Riedel. 2014 · 2014
Earlier work this paper cites.
Emergent: a novel data-set for stance classification
William Ferreira and Andreas Vlachos. 2016 · 2016
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Reading Wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
Earlier work this paper cites.
Where the truth lies: Explaining the credibility of emerging claims on the web and social media
Kashyap Popat, Subhabrata Mukherjee, Jannik Strötgen, and Gerhard Weikum. 2017 · 2017
Earlier work this paper cites.
Truth of varying shades: Analyzing language in fake news and political fact-checking
Hannah Rashkin, Eunsol Choi, Jin Yea Jang, Svitlana Volkova, and Yejin Choi. 2017 · 2017
Earlier work this paper cites.
Separating facts from fiction: Linguistic models to classify suspicious and trusted news posts on Twitter
Svitlana Volkova, Kyle Shaffer, Jin Yea Jang, and Nathan Hodas. 2017 · 2017
Earlier work this paper cites.
“liar, liar pants on fire”: A new benchmark dataset for fake news detection
William Yang Wang. 2017 · 2017
Earlier work this paper cites.
Where is your evidence: Improving fact-checking by justification modeling
Tariq Alhindi, Savvas Petridis, and Smaranda Muresan. 2018 · 2018
Earlier work this paper cites.
Can rumour stance alone predict veracity?
Sebastian Dungs, Ahmet Aker, Norbert Fuhr, and Kalina Bontcheva. 2018 · 2018
Earlier work this paper cites.
Understanding the Promise and Limits of Automated Fact-Checking
Lucas Graves. 2018 · 2018
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Checking how fact-checkers check
Chloe Lim. 2018 · 2018
Earlier work this paper cites.
Towards exploiting background knowledge for building conversation systems
Nikita Moghe, Siddhartha Arora, Suman Banerjee, and Mitesh M. Khapra. 2018 · 2018
Earlier work this paper cites.
Automatic detection of fake news
Verónica Pérez-Rosas, Bennett Kleinberg, Alexandra Lefevre, and Rada Mihalcea. 2018 · 2018
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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.
The web as a knowledge-base for answering complex questions
Alon Talmor and Jonathan Berant. 2018 · 2018
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MultiFC: A real-world multi-domain dataset for evidence-based fact checking of claims
Isabelle Augenstein, Christina Lioma, Dongsheng Wang, Lucas Chaves Lima, Casper Hansen, Christian Hansen, and Jakob Grue Simonsen. 2019 · 2019
Earlier work this paper cites.
A richly annotated corpus for different tasks in automated fact-checking
Andreas Hanselowski, Christian Stab, Claudia Schulz, Zile Li, and Iryna Gurevych. 2019 · 2019
Earlier work this paper cites.
Natural questions: A benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M. Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 2019 · 2019
Earlier work this paper cites.
Multi-hop reading comprehension through question decomposition and rescoring
Sewon Min, Victor Zhong, Luke Zettlemoyer, and Hannaneh Hajishirzi. 2019 · 2019
Earlier work this paper cites.
Answering complex open-domain questions through iterative query generation
Peng Qi, Xiaowen Lin, Leo Mehr, Zijian Wang, and Christopher D. Manning. 2019 · 2019
Cited alongside, same era.
Generating fact checking explanations
Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, and Isabelle Augenstein. 2020 · 2020
Cited alongside, same era.
Generating fact checking briefs
Angela Fan, Aleksandra Piktus, Fabio Petroni, Guillaume Wenzek, Marzieh Saeidi, Andreas Vlachos, Antoine Bordes, and Sebastian Riedel. 2020 · 2020
Cited alongside, same era.
Retrieval augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Mingwei Chang. 2020 · 2020
Cited alongside, same era.
DeBERTa: Decoding-enhanced BERT with Disentangled Attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen. 2020 · 2020
Cited alongside, same era.
Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
A neural model to jointly predict and explain truthfulness of statements
Erik Brand, Kevin Roitero, Michael Soprano, Afshin Rahimi, and Gianluca Demartini. 2022 · 2022
Later among the works it cites.
Generating literal and implied subquestions to fact-check complex claims
Jifan Chen, Aniruddh Sriram, Eunsol Choi, and Greg Durrett. 2022a · 2022
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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 · 2022
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Rarr: Researching and revising what language models say, using language models
Luyu Gao, Zhuyun Dai, Panupong Pasupat, Anthony Chen, Arun Tejasvi Chaganty, Yicheng Fan, Vincent Zhao, N. Lao, Hongrae Lee, Da-Cheng Juan, and Kelvin Guu. 2022 · 2022
Later among the works it cites.
Missing counter-evidence renders NLP fact-checking unrealistic for misinformation
Max Glockner, Yufang Hou, and Iryna Gurevych. 2022 · 2022
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Cited alongside, same era.
Generalization through memorization: Nearest neighbor language models
Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis. 2020 · 2020
Cited alongside, same era.
Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al. 2020 · 2020
Cited alongside, same era.
Unsupervised question decomposition for question answering
Ethan Perez, Patrick Lewis, Wen-tau Yih, Kyunghyun Cho, and Douwe Kiela. 2020 · 2020
Cited alongside, same era.
e-fever: Explanations and summaries for automated fact checking
Dominik Stammbach and Elliott Ash. 2020 · 2020
Cited alongside, same era.
Break it down: A question understanding benchmark
Tomer Wolfson, Mor Geva, Ankit Gupta, Matt Gardner, Yoav Goldberg, Daniel Deutch, and Jonathan Berant. 2020 · 2020
Cited alongside, same era.
Does the Whole Exceed Its Parts? The Effect of AI Explanations on Complementary Team Performance
Gagan Bansal, Tongshuang Wu, Joyce Zhou, Raymond Fok, Besmira Nushi, Ece Kamar, Marco Tulio Ribeiro, and Daniel Weld. 2021 · 2021
Cited alongside, same era.
Later among the works it cites.
News Summarization and Evaluation in the Era of GPT-3
Tanya Goyal, Junyi Jessy Li, and Greg Durrett. 2022 · 2022
Later among the works it cites.
Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation
Yixin Liu, Alexander R. Fabbri, Pengfei Liu, Yilun Zhao, Linyong Nan, Ruilin Han, Simeng Han, Shafiq Joty, Chien-Sheng Wu, Caiming Xiong, and Dragomir Radev. 2022 · 2022
Later among the works it cites.
Varifocal question generation for fact-checking
Nedjma Ousidhoum, Zhangdie Yuan, and Andreas Vlachos. 2022 · 2022
Later among the works it cites.
Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
Later among the works it cites.
Improving passage retrieval with zero-shot question generation
Devendra Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, and Luke Zettlemoyer. 2022 · 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 · 2022
Later among the works it cites.
Training language models with memory augmentation
Zexuan Zhong, Tao Lei, and Danqi Chen. 2022 · 2022
Later among the works it cites.
WiCE: Real-World Entailment for Claims in Wikipedia
Ryo Kamoi, Tanya Goyal, Juan Diego Rodriguez, and Greg Durrett. 2023 · 2023
Closest in time.
In-context retrieval-augmented language models
Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, and Yoav Shoham. 2023 · 2023
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Averitec: A dataset for real-world claim verification with evidence from the web
Michael Schlichtkrull, Zhijiang Guo, and Andreas Vlachos. 2023 · 2023
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REPLUG: Retrieval-Augmented Black-Box Language Models
Weijia Shi, Sewon Min, Michihiro Yasunaga, Minjoon Seo, Rich James, Mike Lewis, Luke Zettlemoyer, and Wen-tau Yih. 2023 · 2023
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Benchmarking Large Language Models for News Summarization
Tianyi Zhang, Faisal Ladhak, Esin Durmus, Percy Liang, Kathleen McKeown, and Tatsunori B. Hashimoto. 2023 · 2023
Closest in time.
Mosh Levy, Alon Jacoby, and Yoav Goldberg. 2024 · 2024
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Lost in the middle: How language models use long contexts
Nelson F Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang. 2024 · 2024
Closest in time.