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Forecasting future world events is a challenging but valuable task.
Okapi at trec-3
Stephen E. Robertson, Steve Walker, Susan Jones, Micheline Hancock-Beaulieu, and Mike Gatford · 1994
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Judgemental and statistical time series forecasting: a review of the literature
Richard Webby and Marcus O’Connor · 1996
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Risky business: safety regulations, risk compensation, and individual behavior
James Hedlund · 2000
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Principles of forecasting: a handbook for researchers and practitioners , volume 30
Jon Scott Armstrong · 2001
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Fallacies of risk
Sven Ove Hansson · 2004
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Forecasting methods and applications
Spyros Makridakis, Steven C Wheelwright, and Rob J Hyndman · 2008
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URL https://80000hours.org/calibration-training/
80k hours calibration, 2013 · 2013
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On the difference between binary prediction and true exposure with implications for forecasting tournaments and decision making research
Nassim Nicholas Taleb and Philip E. Tetlock · 2013
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The psychology of intelligence analysis: drivers of prediction accuracy in world politics
Barbara Mellers, Eric Stone, Pavel Atanasov, Nick Rohrbaugh, S Emlen Metz, Lyle Ungar, Michael M Bishop, Michael Horowitz, Ed Merkle, and Philip Tetlock · 2015
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Posterior calibration and exploratory analysis for natural language processing models
Khanh Nguyen and Brendan O’Connor · 2015
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Cooperative inverse reinforcement learning
Dylan Hadfield-Menell, S. Russell, P. Abbeel, and A. Dragan · 2016
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Common crawl news dataset, 2016
Sebastian Nagel · 2016
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Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang · 2016
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Superforecasting: The art and science of prediction
Philip E Tetlock and Dan Gardner · 2016
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On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger · 2017
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news-please: A generic news crawler and extractor
Felix Hamborg, Norman Meuschke, Corinna Breitinger, and Bela Gipp · 2017
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Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel S. Weld, and Luke Zettlemoyer · 2017
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J. Leike, Miljan Martic, Victoria Krakovna, Pedro A. Ortega, Tom Everitt, Andrew Lefrancq, Laurent Orseau, and S. Legg · 2017
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Uncertainty in forecasts of long-run economic growth
Peter Christensen, Kenneth Gillingham, and William Nordhaus · 2018
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Modeling uncertainty in integrated assessment of climate change: A multimodel comparison
Kenneth Gillingham, William Nordhaus, David Anthoff, Geoffrey Blanford, Valentina Bosetti, Peter Christensen, Haewon McJeon, and John Reilly · 2018
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Geoffrey Irving, Paul Christiano, and Dario Amodei · 2018
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Deep anomaly detection with outlier exposure
Dan Hendrycks, Mantas Mazeika, and Thomas Dietterich · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
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Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman · 2021
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Truthful ai: Developing and governing ai that does not lie
Owain Evans, Owen Cotton-Barratt, Lukas Finnveden, Adam Bales, Avital Balwit, Peter Wills, Luca Righetti, and William Saunders · 2021
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Leveraging passage retrieval with generative models for open domain question answering
Gautier Izacard and Edouard Grave · 2021
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ForecastQA: A question answering challenge for event forecasting with temporal text data
Woojeong Jin, Rahul Khanna, Suji Kim, Dong-Ho Lee, Fred Morstatter, Aram Galstyan, and Xiang Ren · 2021
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Carroll L Wainwright and Peter Eckersley · 2019
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Modelling the pandemic the simulations driving the world’s response to covid-19
David Adam · 2020
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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
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Deberta: Decoding-enhanced BERT with disentangled attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen · 2020
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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
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Forecasting in social settings: The state of the art
Spyros Makridakis, Rob J Hyndman, and Fotios Petropoulos · 2020
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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
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Stephanie Lin, Jacob Hilton, and Owain Evans · 2021
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Revisiting the calibration of modern neural networks
Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, and Mario Lucic · 2021
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Training value-aligned reinforcement learning agents using a normative prior
Md Sultan Al Nahian, Spencer Frazier, Brent Harrison, and Mark Riedl · 2021
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Webgpt: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, et al · 2021
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Retrieval augmentation reduces hallucination in conversation
Kurt Shuster, Spencer Poff, Moya Chen, Douwe Kiela, and Jason Weston · 2021
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BEIR: A heterogeneous benchmark for zero-shot evaluation of information retrieval models
Nandan Thakur, Nils Reimers, Andreas Rücklé, Abhishek Srivastava, and Iryna Gurevych · 2021
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Neuralprophet: Explainable forecasting at scale
Oskar Triebe, Hansika Hewamalage, Polina Pilyugina, Nikolay Laptev, Christoph Bergmeir, and Ram Rajagopal · 2021
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Training a helpful and harmless assistant with reinforcement learning from human feedback
Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, et al · 2022
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X-risk analysis for ai research
Dan Hendrycks and Mantas Mazeika · 2022
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Unifiedqa-v2: Stronger generalization via broader cross-format training
Daniel Khashabi, Yeganeh Kordi, and Hannaneh Hajishirzi · 2022
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Getting gpt-3 to predict metaculus questions, 2022
Mathias Kirk Bonde · 2022
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Teaching models to express their uncertainty in words
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False dichotomy alert: Improving subjective-probability estimates vs. raising awareness of systemic risk
Philip E. Tetlock, Yunzi Lu, and Barbara A. Mellers · 2022
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Uncalibrated models can improve human-ai collaboration
Kailas Vodrahalli, Tobias Gerstenberg, and James Zou · 2022
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