Fetching the paper…
Reading the bibliography…
While neural models show remarkable accuracy on individual predictions, their internal beliefs can be inconsistent across examples.
Theory of T-norms and fuzzy inference methods
Madan M Gupta and J Qi. 1991 · 1991
Earlier work this paper cites.
The Proper Place of Men and Machines in Language Translation
Martin Kay. 1997 · 1997
Earlier work this paper cites.
Posterior Regularization for Structured Latent Variable Models
Kuzman Ganchev, Jennifer Gillenwater, Ben Taskar, et al. 2010 · 2010
Earlier work this paper cites.
Structured Learning with Constrained Conditional Models
Ming-Wei Chang, Lev Ratinov, and Dan Roth. 2012 · 2012
Earlier work this paper cites.
A short Introduction to Probabilistic Soft Logic
Angelika Kimmig, Stephen Bach, Matthias Broecheler, Bert Huang, and Lise Getoor. 2012 · 2012
Earlier work this paper cites.
Recognizing Textual Entailment: Models and Applications
Ido Dagan, Dan Roth, Mark Sammons, and Fabio Massimo Zanzotto. 2013 · 2013
Earlier work this paper cites.
Triangular Norms
Erich Peter Klement, Radko Mesiar, and Endre Pap. 2013 · 2013
Earlier work this paper cites.
Microsoft COCO: Common Objects in Context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick. 2014 · 2014
Earlier work this paper cites.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
Earlier work this paper cites.
Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 2014
Earlier work this paper cites.
A Large Annotated Corpus for Learning Natural Language Inference
Samuel R Bowman, Gabor Angeli, Christopher Potts, and Christopher D Manning. 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.
Injecting Logical Background Knowledge into Embeddings for Relation Extraction
Tim Rocktäschel, Sameer Singh, and Sebastian Riedel. 2015 · 2015
Earlier work this paper cites.
Long Short-Term Memory-Networks for Machine Reading
Jianpeng Cheng, Li Dong, and Mirella Lapata. 2016 · 2016
Earlier work this paper cites.
Harnessing Deep Neural Networks with Logic Rules
Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, Eduard Hovy, and Eric Xing. 2016 · 2016
Cited alongside, same era.
A Decomposable Attention Model for Natural Language Inference
Ankur Parikh, Oscar Täckström, Dipanjan Das, and Jakob Uszkoreit. 2016 · 2016
Cited alongside, same era.
Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
Cited alongside, same era.
Adversarial examples for evaluating reading comprehension systems
Robin Jia and Percy Liang. 2017 · 2017
Cited alongside, same era.
Paraphrasing Revisited with Neural Machine Translation
Jonathan Mallinson, Rico Sennrich, and Mirella Lapata. 2017 · 2017
Cited alongside, same era.
Bidirectional Attention Flow for Machine Comprehension
Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi. 2017 · 2017
Stress Test Evaluation for Natural Language Inference
Aakanksha Naik, Abhilasha Ravichander, Norman Sadeh, Carolyn Rose, and Graham Neubig. 2018 · 2018
Later among the works it cites.
Analyzing Compositionality-Sensitivity of NLI Models
Yixin Nie, Yicheng Wang, and Mohit Bansal. 2018 · 2018
Later among the works it cites.
Deep Contextualized Word Representations
Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
Later among the works it cites.
GLUE: A Multi-task Benchmark and Analysis Platform for Natural Language Understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman. 2018 · 2018
Later among the works it cites.
A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
Later among the works it cites.
A Semantic Loss Function for Deep Learning with Symbolic Knowledge
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Attention is All You Need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Breaking NLI Systems with Sentences that Require Simple Lexical Inferences
Max Glockner, Vered Shwartz, and Yoav Goldberg. 2018 · 2018
Cited alongside, same era.
A Unified Model for Extractive and Abstractive Summarization using Inconsistency Loss
Wan-Ting Hsu, Chieh-Kai Lin, Ming-Ying Lee, Kerui Min, Jing Tang, and Min Sun. 2018 · 2018
Cited alongside, same era.
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks
Mohit Iyyer, John Wieting, Kevin Gimpel, and Luke Zettlemoyer. 2018 · 2018
Cited alongside, same era.
AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples
Dongyeop Kang, Tushar Khot, Ashish Sabharwal, and Eduard Hovy. 2018 · 2018
Cited alongside, same era.
Towards Semi-Supervised Learning for Deep Semantic Role Labeling
Sanket Vaibhav Mehta, Jay Yoon Lee, and Jaime Carbonell. 2018 · 2018
Cited alongside, same era.
Jingyi Xu, Zilu Zhang, Tal Friedman, Yitao Liang, and Guy Van den Broeck. 2018 · 2018
Later among the works it cites.
Synthetic QA Corpora Generation with Roundtrip Consistency
Chris Alberti, Daniel Andor, Emily Pitler, Jacob Devlin, and Michael Collins. 2019 · 2019
Closest in time.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Closest in time.
Be Consistent! Improving Procedural Text Comprehension using Label Consistency
Xinya Du, Bhavana Dalvi, Niket Tandon, Antoine Bosselut, Wen tau Yih, Peter Clark, and Claire Cardie. 2019 · 2019
Closest in time.
DL2: Training and Querying Neural Networks with Logic
Marc Fischer, Mislav Balunovic, Dana Drachsler-Cohen, Timon Gehr, Ce Zhang, and Martin Vechev. 2019 · 2019
Closest in time.
Augmenting Neural Networks with First-order Logic
Tao Li and Vivek Srikumar. 2019 · 2019
Closest in time.
Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets
Nelson F Liu, Roy Schwartz, and Noah A Smith. 2019 · 2019
Closest in time.
What If We Simply Swap the Two Text Fragments? A Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks
Haohan Wang, Da Sun, and Eric P Xing. 2019 · 2019
Closest in time.