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Good-enough compositional data augmentation
Original
Jacob Andreas. 2019 · 1904
Earlier work this paper cites.
An empirical investigation of global and local normalization for recurrent neural sequence models using a continuous relaxation to beam search
Original
Kartik Goyal, Chris Dyer, and Taylor Berg-Kirkpatrick. 2019 · 1904
Earlier work this paper cites.
Counterfactual data augmentation for mitigating gender stereotypes in languages with rich morphology
Original
Ran Zmigrod, Sabrina J Mielke, Hanna Wallach, and Ryan Cotterell. 2019 · 1906
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Original
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Reasoning over paragraph effects in situations
Original
Kevin Lin, Oyvind Tafjord, Peter Clark, and Matt Gardner. 2019 · 1908
Earlier work this paper cites.
Neural text generation with unlikelihood training
Original
Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, and Jason Weston. 2019 · 1908
Earlier work this paper cites.
On incorporating semantic prior knowledge in deep learning through embedding-space constraints
Original
Damien Teney, Ehsan Abbasnejad, and Anton van den Hengel. 2019 · 1909
Earlier work this paper cites.
Qainfomax: Learning robust question answering system by mutual information maximization
Original
Yi-Ting Yeh and Yun-Nung Chen. 2019 · 1909
Earlier work this paper cites.
Evaluating the factual consistency of abstractive text summarization
Original
Wojciech Kryściński, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 1910
Earlier work this paper cites.
Adaptive mixtures of local experts
Robert A Jacobs, Michael I Jordan, Steven J Nowlan, and Geoffrey E Hinton. 1991 · 1991
Earlier work this paper cites.
Solving the multiple instance problem with axis-parallel rectangles
Thomas G Dietterich, Richard H Lathrop, and Tomás Lozano-Pérez. 1997 · 1997
Earlier work this paper cites.
Logic-guided data augmentation and regularization for consistent question answering
Original
Akari Asai and Hannaneh Hajishirzi. 2020b · 2004
Earlier work this paper cites.
An analysis of the utility of explicit negative examples to improve the syntactic abilities of neural language models
Original
Hiroshi Noji and Hiroya Takamura. 2020 · 2004
Earlier work this paper cites.
Learning what makes a difference from counterfactual examples and gradient supervision
Original
Damien Teney, Ehsan Abbasnedjad, and Anton van den Hengel. 2020 · 2004
Earlier work this paper cites.

Similar

Unifiedqa: Crossing format boundaries with a single qa system
Original
Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, and Hannaneh Hajishirzi. 2020 · 2005
Cited alongside, same era.
Contrastive estimation: Training log-linear models on unlabeled data
Noah A. Smith and Jason Eisner. 2005 · 2005
Cited alongside, same era.
Cascaded text generation with markov transformers
Original
Yuntian Deng and Alexander M Rush. 2020 · 2006
Cited alongside, same era.
Dimensionality reduction by learning an invariant mapping
Raia Hadsell, Sumit Chopra, and Yann LeCun. 2006 · 2006
Cited alongside, same era.
Group-wise contrastive learning for neural dialogue generation
Original
Hengyi Cai, Hongshen Chen, Yonghao Song, Zhuoye Ding, Yongjun Bao, Weipeng Yan, and Xiaofang Zhao. 2020 · 2009

Then

Generative question answering: Learning to answer the whole question
Mike Lewis and Angela Fan. 2018 · 2018
Later among the works it cites.
Adversarially regularising neural nli models to integrate logical background knowledge
Pasquale Minervini and S. Riedel. 2018 · 2018
Later among the works it cites.
Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Original
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W Cohen, Ruslan Salakhutdinov, and Christopher D Manning. 2018 · 2018
Later among the works it cites.
Quoref: A reading comprehension dataset with questions requiring coreferential reasoning
Pradeep Dasigi, Nelson F. Liu, Ana Marasović, Noah A. Smith, and Matt Gardner. 2019 · 2019
Later among the works it cites.
A logic-driven framework for consistency of neural models
Tao Li, Vivek Gupta, Maitrey Mehta, and Vivek Srikumar. 2019 · 2019
Later among the works it cites.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

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Reading the bibliography…

2021

Learning with Instance Bundles for Reading Comprehension

Dua, Dheeru, Dasigi, Pradeep, Singh, Sameer et al.

Understand

When training most modern reading comprehension models, all the questions associated with a context are treated as being independent from each other.

However, closely related questions and their corresponding answers are not independent, and leveraging these relationships could provide a strong supervision signal to a model.
Drawing on ideas from contrastive estimation, we introduce several new supervision techniques that compare question-answer scores across multiple related instances.
Specifically, we normalize these scores across various neighborhoods of closely contrasting questions and/or answers, adding another cross entropy loss term that is used in addition to traditional maximum likelihood estimation.

Built on

Good-enough compositional data augmentation
Original
Jacob Andreas. 2019 · 1904
Earlier work this paper cites.
An empirical investigation of global and local normalization for recurrent neural sequence models using a continuous relaxation to beam search
Original
Kartik Goyal, Chris Dyer, and Taylor Berg-Kirkpatrick. 2019 · 1904
Earlier work this paper cites.
Counterfactual data augmentation for mitigating gender stereotypes in languages with rich morphology
Original
Ran Zmigrod, Sabrina J Mielke, Hanna Wallach, and Ryan Cotterell. 2019 · 1906
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Original
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Reasoning over paragraph effects in situations
Original
Kevin Lin, Oyvind Tafjord, Peter Clark, and Matt Gardner. 2019 · 1908
Earlier work this paper cites.
Neural text generation with unlikelihood training
Original
Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, and Jason Weston. 2019 · 1908
Earlier work this paper cites.
On incorporating semantic prior knowledge in deep learning through embedding-space constraints
Original
Damien Teney, Ehsan Abbasnejad, and Anton van den Hengel. 2019 · 1909
Earlier work this paper cites.
Qainfomax: Learning robust question answering system by mutual information maximization
Original
Yi-Ting Yeh and Yun-Nung Chen. 2019 · 1909
Earlier work this paper cites.
Evaluating the factual consistency of abstractive text summarization
Original
Wojciech Kryściński, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 1910
Earlier work this paper cites.
Adaptive mixtures of local experts
Robert A Jacobs, Michael I Jordan, Steven J Nowlan, and Geoffrey E Hinton. 1991 · 1991
Earlier work this paper cites.
Solving the multiple instance problem with axis-parallel rectangles
Thomas G Dietterich, Richard H Lathrop, and Tomás Lozano-Pérez. 1997 · 1997
Earlier work this paper cites.
Logic-guided data augmentation and regularization for consistent question answering
Original
Akari Asai and Hannaneh Hajishirzi. 2020b · 2004
Earlier work this paper cites.
An analysis of the utility of explicit negative examples to improve the syntactic abilities of neural language models
Original
Hiroshi Noji and Hiroya Takamura. 2020 · 2004
Earlier work this paper cites.
Learning what makes a difference from counterfactual examples and gradient supervision
Original
Damien Teney, Ehsan Abbasnedjad, and Anton van den Hengel. 2020 · 2004
Earlier work this paper cites.

Similar

Unifiedqa: Crossing format boundaries with a single qa system
Original
Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, and Hannaneh Hajishirzi. 2020 · 2005
Cited alongside, same era.
Contrastive estimation: Training log-linear models on unlabeled data
Noah A. Smith and Jason Eisner. 2005 · 2005
Cited alongside, same era.
Cascaded text generation with markov transformers
Original
Yuntian Deng and Alexander M Rush. 2020 · 2006
Cited alongside, same era.
Dimensionality reduction by learning an invariant mapping
Raia Hadsell, Sumit Chopra, and Yann LeCun. 2006 · 2006
Cited alongside, same era.
Group-wise contrastive learning for neural dialogue generation
Original
Hengyi Cai, Hongshen Chen, Yonghao Song, Zhuoye Ding, Yongjun Bao, Weipeng Yan, and Xiaofang Zhao. 2020 · 2009

Then

Generative question answering: Learning to answer the whole question
Mike Lewis and Angela Fan. 2018 · 2018
Later among the works it cites.
Adversarially regularising neural nli models to integrate logical background knowledge
Pasquale Minervini and S. Riedel. 2018 · 2018
Later among the works it cites.
Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Original
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W Cohen, Ruslan Salakhutdinov, and Christopher D Manning. 2018 · 2018
Later among the works it cites.
Quoref: A reading comprehension dataset with questions requiring coreferential reasoning
Pradeep Dasigi, Nelson F. Liu, Ana Marasović, Noah A. Smith, and Matt Gardner. 2019 · 2019
Later among the works it cites.
A logic-driven framework for consistency of neural models
Tao Li, Vivek Gupta, Maitrey Mehta, and Vivek Srikumar. 2019 · 2019
Later among the works it cites.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

Cited alongside, same era.

Noise-contrastive estimation: A new estimation principle for unnormalized statistical models

Michael Gutmann and Aapo Hyvärinen. 2010 · 2010

Cited alongside, same era.

Explaining the efficacy of counterfactually-augmented data

Original

Divyansh Kaushik, Amrith Setlur, Eduard Hovy, and Zachary C Lipton. 2020 · 2010

Cited alongside, same era.

Inference protocols for coreference resolution

Kai-Wei Chang, Rajhans Samdani, Alla Rozovskaya, Nick Rizzolo, Mark Sammons, and Dan Roth. 2011 · 2011

Cited alongside, same era.

Explaining nlp models via minimal contrastive editing (mice)

Original

Alexis Ross, Ana Marasović, and Matthew E. Peters. 2020 · 2012

Cited alongside, same era.

Distributed representations of words and phrases and their compositionality

Original

Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013

Cited alongside, same era.

Contrastive learning for image captioning

Original

Bo Dai and Dahua Lin. 2017 · 2017

Cited alongside, same era.

Adversarial examples for evaluating reading comprehension systems

Original

Robin Jia and Percy Liang. 2017 · 2017

Cited alongside, same era.

Evaluating models’ local decision boundaries via contrast sets

Matt Gardner, Yoav Artzi, Victoria Basmov, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh 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, Ally Zhang, and Ben Zhou. 2020 · 2020

Later among the works it cites.

Multi-step inference for reasoning over paragraphs

Jiangming Liu, Matt Gardner, Shay B. Cohen, and Mirella Lapata. 2020 · 2020

Later among the works it cites.

Beyond accuracy: Behavioral testing of NLP models with CheckList

Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin, and Sameer Singh. 2020 · 2020

Later among the works it cites.

Measuring and improving consistency in pretrained language models

Original

Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard Hovy, Hinrich Schütze, and Yoav Goldberg. 2021 · 2021

Closest in time.

Paired examples as indirect supervision in latent decision models