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04/27/2023
string2string: A Modern Python Library for String-to-String Algorithms
We introduce string2string, an open-source library that offers a compreh...
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07/08/2022
The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications
Innovation is a major driver of economic and social development, and inf...
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11/08/2019
Memory-Augmented Recurrent Neural Networks Can Learn Generalized Dyck Languages
We introduce three memory-augmented Recurrent Neural Networks (MARNNs) a...
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07/09/2019
On Adversarial Removal of Hypothesis-only Bias in Natural Language Inference
Popular Natural Language Inference (NLI) datasets have been shown to be ...
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07/09/2019
Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference
Natural Language Inference (NLI) datasets often contain hypothesis-only ...
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06/09/2019
LSTM Networks Can Perform Dynamic Counting
In this paper, we systematically assess the ability of standard recurren...
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11/02/2018
On Evaluating the Generalization of LSTM Models in Formal Languages
Recurrent Neural Networks (RNNs) are theoretically Turing-complete and e...
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08/30/2018
Learning Neural Templates for Text Generation
While neural, encoder-decoder models have had significant empirical succ...
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07/27/2017
Adapting Sequence Models for Sentence Correction
In a controlled experiment of sequence-to-sequence approaches for the ta...
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07/25/2017
Challenges in Data-to-Document Generation
Recent neural models have shown significant progress on the problem of g...
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04/28/2016
Word Ordering Without Syntax
Recent work on word ordering has argued that syntactic structure is impo...
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04/16/2016
Sentence-Level Grammatical Error Identification as Sequence-to-Sequence Correction
We demonstrate that an attention-based encoder-decoder model can be used...
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04/11/2016
