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Prior work has demonstrated large language models' (LLMs) potential to discern statistical tendencies within their pre-training corpora.
Towards an atlas of cultural commonsense for machine reasoning
Anurag Acharya, Kartik Talamadupula, and Mark A Finlayson. 2020 · 2009
Earlier work this paper cites.
The wvs cultural map of the world
Ronald Inglehart and Chris Welzel. 2010 · 2010
Earlier work this paper cites.
Quantitative analysis of culture using millions of digitized books
Jean-Baptiste Michel, Yuan Kui Shen, Aviva Presser Aiden, Adrian Veres, Matthew K Gray, Google Books Team, Joseph P Pickett, Dale Hoiberg, Dan Clancy, Peter Norvig, et al. 2011 · 2011
Earlier work this paper cites.
Syntactic annotations for the Google Books NGram corpus
Yuri Lin, Jean-Baptiste Michel, Erez Aiden Lieberman, Jon Orwant, Will Brockman, and Slav Petrov. 2012 · 2012
Earlier work this paper cites.
Identifying cross-cultural differences in word usage
Aparna Garimella, Rada Mihalcea, and James Pennebaker. 2016 · 2016
Earlier work this paper cites.
Incorporating dialectal variability for socially equitable language identification
David Jurgens, Yulia Tsvetkov, and Dan Jurafsky. 2017 · 2017
Earlier work this paper cites.
SemEval-2017 task 3: Community question answering
Preslav Nakov, Doris Hoogeveen, Lluís Màrquez, Alessandro Moschitti, Hamdy Mubarak, Timothy Baldwin, and Karin Verspoor. 2017 · 2017
Earlier work this paper cites.
Do neural nets learn statistical laws behind natural language?
Shuntaro Takahashi and Kumiko Tanaka-Ishii. 2017 · 2017
Earlier work this paper cites.
What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties
Alexis Conneau, German Kruszewski, Guillaume Lample, Loïc Barrault, and Marco Baroni. 2018 · 2018
Earlier work this paper cites.
COMET: Commonsense transformers for automatic knowledge graph construction
Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz, and Yejin Choi. 2019 · 2019
Earlier work this paper cites.
A structural probe for finding syntax in word representations
John Hewitt and Christopher D. Manning. 2019 · 2019
Earlier work this paper cites.
RankQA: Neural question answering with answer re-ranking
Bernhard Kratzwald, Anna Eigenmann, and Stefan Feuerriegel. 2019 · 2019
Earlier work this paper cites.
Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, and Alexander Miller. 2019 · 2019
Earlier work this paper cites.
Cross-cultural transfer learning for text classification
Dor Ringel, Gal Lavee, Ido Guy, and Kira Radinsky. 2019 · 2019
Earlier work this paper cites.
Evaluating computational language models with scaling properties of natural language
Shuntaro Takahashi and Kumiko Tanaka-Ishii. 2019 · 2019
Cited alongside, same era.
Text analysis for the social sciences: methods for drawing statistical inferences from texts and transcripts
Carl W Roberts. 2020 · 2020
Cited alongside, same era.
The importance of modeling social factors of language: Theory and practice
Dirk Hovy and Diyi Yang. 2021 · 2021
Cited alongside, same era.
Visually grounded reasoning across languages and cultures
Fangyu Liu, Emanuele Bugliarello, Edoardo Maria Ponti, Siva Reddy, Nigel Collier, and Desmond Elliott. 2021 · 2021
Cited alongside, same era.
Language model evaluation beyond perplexity
Clara Meister and Ryan Cotterell. 2021 · 2021
Cited alongside, same era.
Cross-cultural similarity features for cross-lingual transfer learning of pragmatically motivated tasks
Frmt: A benchmark for few-shot region-aware machine translation
Parker Riley, Timothy Dozat, Jan A Botha, Xavier Garcia, Dan Garrette, Jason Riesa, Orhan Firat, and Noah Constant. 2022 · 2022
Later among the works it cites.
Iteratively prompt pre-trained language models for chain of thought
Boshi Wang, Xiang Deng, and Huan Sun. 2022 · 2022
Later among the works it cites.
Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, and Denny Zhou. 2022 · 2022
Later among the works it cites.
Sociolectal analysis of pretrained language models
Sheng Zhang, Xin Zhang, Weiming Zhang, and Anders Søgaard. 2021 · 2022
Later among the works it cites.
Mathprompter: Mathematical reasoning using large language models
Shima Imani, Liang Du, and Harsh Shrivastava. 2023 · 2023
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Jimin Sun, Hwijeen Ahn, Chan Young Park, Yulia Tsvetkov, and David R. Mortensen. 2021 · 2021
Cited alongside, same era.
Can we map culture?
Ted Underwood and Richard Jean So. 2021 · 2021
Cited alongside, same era.
Analyzing linguistic features for answer re-ranking of why-questions
Manvi Breja and Sanjay Kumar Jain. 2022 · 2022
Cited alongside, same era.
Computational analysis of 140 years of us political speeches reveals more positive but increasingly polarized framing of immigration
Dallas Card, Serina Chang, Chris Becker, Julia Mendelsohn, Rob Voigt, Leah Boustan, Ran Abramitzky, and Dan Jurafsky. 2022 · 2022
Cited alongside, same era.
Challenges and strategies in cross-cultural NLP
Daniel Hershcovich, Stella Frank, Heather Lent, Miryam de Lhoneux, Mostafa Abdou, Stephanie Brandl, Emanuele Bugliarello, Laura Cabello Piqueras, Ilias Chalkidis, Ruixiang Cui, Constanza Fierro, Katerina Margatina, Phillip Rust, and Anders Søgaard. 2022 · 2022
Cited alongside, same era.
Foundation models of scientific knowledge for chemistry: Opportunities, challenges and lessons learned
Sameera Horawalavithana, Ellyn Ayton, Shivam Sharma, Scott Howland, Megha Subramanian, Scott Vasquez, Robin Cosbey, Maria Glenski, and Svitlana Volkova. 2022 · 2022
Cited alongside, same era.
Large language models struggle to learn long-tail knowledge
Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, and Colin Raffel. 2022 · 2022
Cited alongside, same era.
Closest in time.
Multi-lingual and multi-cultural figurative language understanding
Anubha Kabra, Emmy Liu, Simran Khanuja, Alham Fikri Aji, Genta Indra Winata, Samuel Cahyawijaya, Anuoluwapo Aremu, Perez Ogayo, and Graham Neubig. 2023 · 2023
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Qa dataset explosion: A taxonomy of nlp resources for question answering and reading comprehension
Anna Rogers, Matt Gardner, and Isabelle Augenstein. 2023 · 2023
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Bloom: A 176b-parameter open-access multilingual language model
Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, Jonathan Tow, Alexander M. Rush, and et al. 2023 · 2023
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Reflexion: Language agents with verbal reinforcement learning
Noah Shinn, Federico Cassano, Beck Labash, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. 2023 · 2023
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Grounding characters and places in narrative texts
Sandeep Soni, Amanpreet Sihra, Elizabeth F. Evans, Matthew Wilkens, and David Bamman. 2023 · 2023
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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, et al. 2023 · 2023
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Zero-shot information extraction via chatting with chatgpt
Xiang Wei, Xingyu Cui, Ning Cheng, Xiaobin Wang, Xin Zhang, Shen Huang, Pengjun Xie, Jinan Xu, Yufeng Chen, Meishan Zhang, et al. 2023 · 2023
Closest in time.
GeoMLAMA: Geo-diverse commonsense probing on multilingual pre-trained language models
Da Yin, Hritik Bansal, Masoud Monajatipoor, Liunian Harold Li, and Kai-Wei Chang. 2022 · 2055
Closest in time.