SlowGuess/NAACL_2022_OCR huggingface dataset:
Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew E. Peters, Ashish Sabharwal, and Yejin Choi. 2020. Adversarial filters of dataset biases. In Proc. of ICML.
Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, and Nicholas Carlini. 2022. Deduplicating training data makes language models better. In Proc. of ACL.
Hector Levesque, Ernest Davis, and Leora Morgenstern. 2012. The winograd schema challenge. In Proc. of KR.
Xiang Lorraine Li, Adhiguna Kuncoro, Cyprien de Masson d'Autume, Phil Blunsom, and Aida Nematzadeh. 2021. Do language models learn commonsense knowledge? arXiv:2111.00607.
Hugo Liu and Push Singh. 2004. Conceptnet: A practical commonsense reasoning toolkit. BT Technology Journal, 22(4).
Nelson F. Liu, Tony Lee, Robin Jia, and Percy Liang. 2021a. Can small and synthetic benchmarks drive modeling innovation? a retrospective study of question answering modeling approaches. arXiv:2102.01065.
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2021b. Pretrain, prompt, and predict: A systematic survey of prompting methods in natural language processing. arXiv:2107.13586.
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. RoBERTa: A robustly optimized bert pretraining approach. arXiv:1907.11692.
Will Merrill, Yoav Goldberg, Roy Schwartz, and Noah A. Smith. 2021. Provable limitations of acquiring meaning from ungrounded form: what will future language models understand? TACL.
Saif Mohammad, Ekaterina Shutova, and Peter Turney. 2016. Metaphor as a medium for emotion: An empirical study. In *Proc. of *SEM.
Roser Morante and Eduardo Blanco. 2012. *SEM 2012 shared task: Resolving the scope and focus of negation. In Proc. of *SEM.*
Silviu Oprea and Walid Magdy. 2020. iSarcasm: A dataset of intended sarcasm. In Proc. of ACL.
Judea Pearl. 2009. Causality. Cambridge university press.
Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018. Deep contextualized word representations. In Proc. of NAACL-HLT.
Matthew E. Peters, Mark Neumann, Robert Logan, Roy Schwartz, Vidur Joshi, Sameer Singh, and Noah A. Smith. 2019. Knowledge enhanced contextual word representations. In Proc. of EMNLP.
Adam Poliak, Jason Naradowsky, Aparajita Haldar, Rachel Rudinger, and Benjamin Van Durme. 2018. Hypothesis only baselines in natural language inference. In *Proc. of *SEM.
Lianhui Qin, Vered Shwartz, Peter West, Chandra Bhagavatula, Jena D. Hwang, Ronan Le Bras, Antoine Bosselut, and Yejin Choi. 2020. Back to the future: Unsupervised backprop-based decoding for counterfactual and abductive commonsense reasoning. In Proc. of EMNLP.
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019. Language models are unsupervised multitask learners. OpenAI blog, 1(8).
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020. Exploring the limits of transfer learning with a unified text-to-text transformer. JMLR, 21(140):1-67.
Inioluwa Deborah Raji, Emily M. Bender, Amandalynne Paullada, Emily Denton, and Alex Hanna. 2021. AI and the everything in the whole wide world benchmark. In Proc. Of NeurIPS Benchmarks and Datasets track.
Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018. Know what you don't know: Unanswerable questions for SQuAD. In Proc. of ACL.
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016. SQuAD: 100,000+ questions for machine comprehension of text. In Proc. of EMNLP.
Arijit Ray, Gordon Christie, Mohit Bansal, Dhruv Batra, and Devi Parikh. 2016. Question relevance in VQA: Identifying non-visual and false-premise questions. In Proc. of EMNLP.
Adam Roberts, Colin Raffel, and Noam Shazeer. 2020. How much knowledge can you pack into the parameters of a language model? In Proc. of EMNLP.
Anna Rogers. 2021. Changing the world by changing the data. In Proc. of ACL.
Dana Rubinstein, Effi Levi, Roy Schwartz, and Ari Rappoport. 2015. How well do distributional models capture different types of semantic knowledge? In Proc. of ACL.
Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2020. WinoGrande: An adversarial winograd schema challenge at scale. In Proc. of AAAI.
Timo Schick and Hinrich Schütze. 2021. It's not just size that matters: Small language models are also few-shot learners. In Proc. of NAACL.
Timo Schick and Hinrich Schütze. 2021. True few-shot learning with prompts - a real-world perspective. arXiv:2111.13440.
Roy Schwartz, Jesse Dodge, Noah A. Smith, and Oren Etzioni. 2020. Green AI. CACM, 63(12).
Roy Schwartz, Maarten Sap, Ioannis Konstas, Leila Zilles, Yejin Choi, and Noah A. Smith. 2017. The effect of different writing tasks on linguistic style: A case study of the ROC story cloze task. In Proc. of CoNLL.
Rishi Sharma, James Allen, Omid Bakhshandeh, and Nasrin Mostafazadeh. 2018. Tackling the story ending biases in the story cloze test. In Proc. of ACL.
Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, Eric Wallace, and Sameer Singh. 2020. *AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts*. In *Proc. of EMNLP*.
Avanti Shrikumar, Amr Alexandari, and Anshul Kundaje. 2019. A flexible and adaptive framework for abstention under class imbalance. arXiv:1802.07024.
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman. 2014. Deep inside convolutional networks: Visualising image classification models and saliency maps. arXiv:1312.6034.
Daniel Smilkov, Nikhil Thorat, Been Kim, Fernanda Viégas, and Martin Wattenberg. 2017. SmoothGrad: removing noise by adding noise. arXiv:1706.03825.
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Ng, and Christopher Potts. 2013. Recursive deep models for semantic compositionality over a sentiment treebank. In Proc. of EMNLP.
Gabriel Stanovsky, Noah A. Smith, and Luke Zettlemoyer. 2019. Evaluating gender bias in machine translation. In Proc. of ACL.
M. Steedman and J. Baldridge. 2006. Combinatory categorical grammar. In Keith Brown, editor, Encyclopedia of Language & Linguistics (Second Edition), second edition edition, pages 610-621. Elsevier, Oxford.
Emma Strubell, Ananya Ganesh, and Andrew McCallum. 2019. Energy and policy considerations for deep learning in NLP. In Proc. of ACL.
Elior Sulem, Jamaal Hay, and Dan Roth. 2021. Do we know what we don't know? studying unanswerable questions beyond SQuAD 2.0. In Findings of EMNLP.
Mukund Sundararajan, Ankur Taly, and Qiqi Yan. 2017. Axiomatic attribution for deep networks. In Proc. of ICML.
Swabha Swayamdipta, Roy Schwartz, Nicholas Lourie, Yizhong Wang, Hannaneh Hajishirzi, Noah A. Smith, and Yejin Choi. 2020. Dataset cartography: Mapping and diagnosing datasets with training dynamics. In Proc. of EMNLP.
Niket Tandon, Keisuke Sakaguchi, Bhavana Dalvi, Dheeraj Rajagopal, Peter Clark, Michal Guerquin, Kyle Richardson, and Eduard Hovy. 2020. A dataset for tracking entities in open domain procedural text. In Proc. of EMNLP.
Yulia Tsvetkov, Leonid Boytsov, Anatole Gershman, Eric Nyberg, and Chris Dyer. 2014. Metaphor detection with cross-lingual model transfer. In Proc. of ACL.
Luyu Wang, Yujia Li, Ozlem Aslan, and Oriol Vinyals. 2021. WikiGraphs: A Wikipedia text - knowledge graph paired dataset. In Proc. of TextGraphs.
Zhao Wang and Aron Culotta. 2020. Identifying spurious correlations for robust text classification. In Findings of EMNLP.
Orion Weller and Kevin Seppi. 2019. Humor detection: A transformer gets the last laugh. In Proc. of EMNLP.
Yadollah Yaghoobzadeh, Soroush Mehri, Remi Tachet des Combes, T. J. Hazen, and Alessandro Sordoni. 2021. Increasing robustness to spurious correlations using forgettable examples. In Proc. of EACL.
Rowan Zellers, Yonatan Bisk, Roy Schwartz, and Yejin Choi. 2018. SWAG: A large-scale adversarial dataset for grounded commonsense inference. In Proc. of EMNLP.
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019. HellaSwag: Can a machine really finish your sentence? In Proc. of ACL.
Sheng Zhang, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Kevin Duh, and Benjamin Van Durme. 2018. ReCoRD: Bridging the gap between human and machine commonsense reading comprehension. arXiv:1810.12885.
Shujian Zhang, Chengyue Gong, and Eunsol Choi. 2021. Knowing more about questions can help: Improving calibration in question answering. In Findings of ACL.
Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, and Qun Liu. 2019. ERNIE: Enhanced language representation with informative entities. In Proc. of ACL.
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2017. Men also like shopping: Reducing gender bias amplification using corpus-level constraints. In Proc. of EMNLP.