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Compositional, structured models are appealing because they explicitly decompose problems and provide interpretable intermediate outputs that give confidence that the model is not simply latching onto data artifacts.
Joe Stacey, Pasquale Minervini, Haim Dubossarsky, Sebastian Riedel, and Tim Rocktäschel. 2020 · 2004
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Contrastive estimation: Training log-linear models on unlabeled data
Noah A. Smith and J. Eisner. 2005 · 2005
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Guiding semi-supervision with constraint-driven learning
Ming-Wei Chang, Lev Ratinov, and Dan Roth. 2007 · 2007
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Expectation maximization and posterior constraints
J. Graça, K. Ganchev, and B. Taskar. 2007 · 2007
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Why doesn’t em find good hmm pos-taggers?
Mark Johnson. 2007 · 2007
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Span-based semantic parsing for compositional generalization
Jonathan Herzig and Jonathan Berant. 2020 · 2009
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Structured output learning with indirect supervision
Ming-Wei Chang, V. Srikumar, Dan Goldwasser, and D. Roth. 2010 · 2010
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Posterior regularization for structured latent variable models
Kuzman Ganchev, Joao Graça, Jennifer Gillenwater, and Ben Taskar. 2010 · 2010
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Illinois-lh: A denotational and distributional approach to semantics
A. Lai and Julia Hockenmaier. 2014 · 2014
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
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Neural module networks
Jacob Andreas, Marcus Rohrbach, Trevor Darrell, and Dan Klein. 2016 · 2016
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Recurrent neural network grammars
Chris Dyer, Adhiguna Kuncoro, Miguel Ballesteros, and Noah A. Smith. 2016 · 2016
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Globally coherent text generation with neural checklist models
Chloé Kiddon, Luke Zettlemoyer, and Yejin Choi. 2016 · 2016
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Squad: 100, 000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Learning to ask: Neural question generation for reading comprehension
X. Du, Junru Shao, and Claire Cardie. 2017 · 2017
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Dynamic entity representations in neural language models
Yangfeng Ji, Chenhao Tan, Sebastian Martschat, Yejin Choi, and Noah A. Smith. 2017 · 2017
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Improving text-to-sql evaluation methodology
Catherine Finegan-Dollak, Jonathan K. Kummerfeld, Li Zhang, Karthik Ramanathan, Sesh Sadasivam, Rui Zhang, and Dragomir Radev. 2018 · 2018
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Allennlp: A deep semantic natural language processing platform
Matt Gardner, Joel Grus, Mark Neumann, Oyvind Tafjord, Pradeep Dasigi, Nelson F. Liu, Matthew E. Peters, Michael Schmitz, and Luke S. Zettlemoyer. 2018 · 2018
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Annotation artifacts in natural language inference data
Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel R. Bowman, and Noah A. Smith. 2018 · 2018
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Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks
B. M. Lake and M. Baroni. 2018 · 2018
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Barack’s wife hillary: Using knowledge-graphs for fact-aware language modeling
IV Robert L. Logan, Nelson F. Liu, Matthew E. Peters, Matt Gardner, and Sameer Singh. 2019 · 2019
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Compositional questions do not necessitate multi-hop reasoning
Sewon Min, Eric Wallace, Sameer Singh, Matt Gardner, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2019 · 2019
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Are red roses red? evaluating consistency of question-answering models
Marco Tulio Ribeiro, Carlos Guestrin, and Sameer Singh. 2019 · 2019
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Good-enough compositional data augmentation
Jacob Andreas. 2020 · 2020
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Logic-guided data augmentation and regularization for consistent question answering
Akari Asai and Hannaneh Hajishirzi. 2020 · 2020
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Adversarial filters of dataset biases
Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew E. Peters, A. Sabharwal, and Yejin Choi. 2020 · 2020
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Adversarially regularising neural nli models to integrate logical background knowledge
Pasquale Minervini and S. Riedel. 2018 · 2018
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CLOSURE: Assessing Systematic Generalization of CLEVR Models
Dzmitry Bahdanau, H. D. Vries, Timothy J. O’Donnell, Shikhar Murty, Philippe Beaudoin, Yoshua Bengio, and Aaron C. Courville. 2019 · 2019
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Don’t take the easy way out: Ensemble based methods for avoiding known dataset biases
Christopher Clark, Mark Yatskar, and Luke Zettlemoyer. 2019 · 2019
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DROP: A reading comprehension benchmark requiring discrete reasoning over paragraphs
Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, and Matt Gardner. 2019 · 2019
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A multi-type multi-span network for reading comprehension that requires discrete reasoning
Minghao Hu, Yuxing Peng, Zhiheng Huang, and Dongsheng Li. 2019 · 2019
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Transcoding compositionally: using attention to find more generalizable solutions
K. Korrel, Dieuwke Hupkes, Verna Dankers, and Elia Bruni. 2019 · 2019
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Generating question-answer hierarchies
Kalpesh Krishna and Mohit Iyyer. 2019 · 2019
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Neural symbolic reader: Scalable integration of distributed and symbolic representations for reading comprehension
Xinyun Chen, Chen Liang, Adams Wei Yu, Denny Zhou, D. Song, and Quoc V. Le. 2020 · 2020
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Evaluating models’ local decision boundaries via contrast sets
Matt Gardner, Yoav Artzi, Victoria Basmova, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hanna Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, A. Zhang, and Ben Zhou. 2020 · 2020
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Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
M. Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, A. Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2020 · 2020
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Improving compositional generalization in semantic parsing
Inbar Oren, Jonathan Herzig, Nitish Gupta, Matt Gardner, and Jonathan Berant. 2020 · 2020
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Obtaining Faithful Interpretations from Compositional Neural Networks
Sanjay Subramanian, Ben Bogin, Nitish Gupta, Tomer Wolfson, Sameer Singh, Jonathan Berant, and Matt Gardner. 2020 · 2020
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Asking and answering questions to evaluate the factual consistency of summaries
Alex Wang, Kyunghyun Cho, and M. Lewis. 2020 · 2020
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Break it down: A question understanding benchmark
Tomer Wolfson, Mor Geva, Ankit Gupta, Matt Gardner, Yoav Goldberg, Daniel Deutch, and Jonathan Berant. 2020 · 2020
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BERTScore: Evaluating Text Generation with BERT
Tianyi Zhang*, Varsha Kishore*, Felix Wu*, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
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