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Recent work shows that causal facts can be effectively extracted from LLMs through prompting, facilitating the creation of causal graphs for causal inference tasks.
Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, and Jamie Brew. 2019 · 1910
Earlier work this paper cites.
The direction of time , volume 65
Hans Reichenbach. 1956 · 1956
Earlier work this paper cites.
A causal calculus (i)
Irving J Good. 1961 · 1961
Earlier work this paper cites.
Post hoc, ergo propter hoc
John Woods and Douglas Walton. 1977 · 1977
Earlier work this paper cites.
Human Inference: Strategies and Shortcomings of Social Judgment
R.E. Nisbett and L. Ross. 1980 · 1980
Earlier work this paper cites.
Reasoning about change: time and causation from the standpoint of artificial intelligence
Yoav Shoham. 1987 · 1987
Earlier work this paper cites.
How we know what isn’t so: The fallibility of human reason in everyday life
Thomas Gilovich. 1991 · 1991
Earlier work this paper cites.
Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, T. J. Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeff Wu, and Dario Amodei. 2020 · 2001
Earlier work this paper cites.
John s. bell’s concept of local causality
Travis Norsen. 2007 · 2007
Earlier work this paper cites.
Causality
Judea Pearl. 2009 · 2009
Earlier work this paper cites.
The order of things: Inferring causal structure from temporal patterns
Neil Bramley, Tobias Gerstenberg, and David Lagnado. 2014 · 2014
Earlier work this paper cites.
Distinguishing cause from effect using observational data: Methods and benchmarks
Joris M. Mooij, J. Peters, Dominik Janzing, Jakob Zscheischler, and Bernhard Scholkopf. 2014 · 2014
Earlier work this paper cites.
A modification of the halpern-pearl definition of causality
Joseph Y. Halpern. 2015 · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
Earlier work this paper cites.
Towards ai-complete question answering: A set of prerequisite toy tasks
Jason Weston, Antoine Bordes, Sumit Chopra, and Tomas Mikolov. 2015 · 2015
Earlier work this paper cites.
Actual causality
Joseph Y Halpern. 2016 · 2016
Earlier work this paper cites.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2017 · 2017
Cited alongside, same era.
Textworld: A learning environment for text-based games
Marc-Alexandre Côté, Ákos Kádár, Xingdi Yuan, Ben A. Kybartas, Tavian Barnes, Emery Fine, James Moore, Matthew J. Hausknecht, Layla El Asri, Mahmoud Adada, Wendy Tay, and Adam Trischler. 2018 · 2018
Cited alongside, same era.
Annotation artifacts in natural language inference data
Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel Bowman, and Noah A. Smith. 2018 · 2018
Cited alongside, same era.
Review of causal discovery methods based on graphical models
Clark Glymour, Kun Zhang, and Peter Spirtes. 2019 · 2019
Cited alongside, same era.
Right for the wrong reasons: Diagnosing syntactic heuristics in natural language inference
R. Thomas McCoy, Ellie Pavlick, and Tal Linzen. 2019 · 2019
Cited alongside, same era.
The pile: An 800gb dataset of diverse text for language modeling
Studying large language model generalization with influence functions
Roger Baker Grosse, Juhan Bae, Cem Anil, Nelson Elhage, Alex Tamkin, Amirhossein Tajdini, Benoit Steiner, Dustin Li, Esin Durmus, Ethan Perez, Evan Hubinger, Kamil.e Lukovsiut.e, Karina Nguyen, Nicholas Joseph, Sam McCandlish, Jared Kaplan, and Sam Bowman. 2023 · 2023
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CLadder: A benchmark to assess causal reasoning capabilities of language models
Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, Zhiheng LYU, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, and Bernhard Schölkopf. 2023 · 2023
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Causal reasoning and large language models: Opening a new frontier for causality
Emre Kıcıman, Robert Osazuwa Ness, Amit Sharma, and Chenhao Tan. 2023 · 2023
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Passive learning of active causal strategies in agents and language models
Andrew Kyle Lampinen, Stephanie C. Y. Chan, Ishita Dasgupta, Andrew Joo Hun Nam, and Jane X. Wang. 2023 · 2023
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, Shawn Presser, and Connor Leahy. 2020 · 2020
Cited alongside, same era.
Causenet: Towards a causality graph extracted from the web
Stefan Heindorf, Yan Scholten, Henning Wachsmuth, Axel-Cyrille Ngonga Ngomo, and Martin Potthast. 2020 · 2020
Cited alongside, same era.
A counterfactual simulation model of causal judgments for physical events
Tobias Gerstenberg, Noah D Goodman, David A Lagnado, and Joshua B Tenenbaum. 2021 · 2021
Cited alongside, same era.
Lora: Low-rank adaptation of large language models
J. Edward Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, and Weizhu Chen. 2021 · 2021
Cited alongside, same era.
Are all spurious features in natural language alike? an analysis through a causal lens
Nitish Joshi, Xiang Pan, and Hengxing He. 2022 · 2022
Cited alongside, same era.
Probabilities of causation: three counterfactual interpretations and their identification
Judea Pearl. 2022 · 2022
Cited alongside, same era.
Prompting gpt-3 to be reliable
Chenglei Si, Zhe Gan, Zhengyuan Yang, Shuohang Wang, Jianfeng Wang, Jordan L. Boyd-Graber, and Lijuan Wang. 2022 · 2022
Cited alongside, same era.
Teaching arithmetic to small transformers
Nayoung Lee, Kartik K. Sreenivasan, Jason D. Lee, Kangwook Lee, and Dimitris Papailiopoulos. 2023 · 2023
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Inverse scaling: When bigger isn’t better
Ian R. McKenzie, Alexander Lyzhov, Michael Martin Pieler, Alicia Parrish, Aaron Mueller, Ameya Prabhu, Euan McLean, Aaron Kirtland, Alexis Ross, Alisa Liu, Andrew Gritsevskiy, Daniel Wurgaft, Derik Kauffman, Gabriel Recchia, Jiacheng Liu, Joe Cavanagh, Max Weiss, Sicong Huang, The Floating Droid, Tom Tseng, Tomasz Korbak, Xudong Shen, Yuhui Zhang, Zhengping Zhou, Najoung Kim, Sam Bowman, and Ethan Perez. 2023 · 2023
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Language models are greedy reasoners: A systematic formal analysis of chain-of-thought
Abulhair Saparov and He He. 2023 · 2023
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Evaluating the moral beliefs encoded in llms
Nino Scherrer, Claudia Shi, Amir Feder, and David M. Blei. 2023 · 2023
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Positional description matters for transformers arithmetic
Ruoqi Shen, Sébastien Bubeck, Ronen Eldan, Yin Tat Lee, Yuanzhi Li, and Yi Zhang. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin R. Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Daniel M. Bikel, Lukas Blecher, Cristian Cantón Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony S. Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel M. Kloumann, A. V. Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, R. Subramanian, Xia Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zhengxu Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurelien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom. 2023 · 2023
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Ifqa: A dataset for open-domain question answering under counterfactual presuppositions
W. Yu, Meng Jiang, Peter Clark, and Ashish Sabharwal. 2023 · 2023
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Causal parrots: Large language models may talk causality but are not causal
M. Zecevic, Moritz Willig, Devendra Singh Dhami, and Kristian Kersting. 2023 · 2023
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Can large language models infer causation from correlation?
Zhijing Jin, Jiarui Liu, Zhiheng LYU, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona T. Diab, and Bernhard Schölkopf. 2024 · 2024
Closest in time.
Counterfactual Theories of Causation
Peter Menzies and Helen Beebee. 2024 · 2024
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A critical review of causal inference benchmarks for large language models
Linying Yang, Oscar Clivio, Vik Shirvaikar, and Fabian Falck. 2023 · 2024
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