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Comparative Error Analysis in Neural and Finite-state Models for Unsupervised Character-level Transduction ...
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Abstract:
Traditionally, character-level transduction problems have been solved with finite-state models designed to encode structural and linguistic knowledge of the underlying process, whereas recent approaches rely on the power and flexibility of sequence-to-sequence models with attention. Focusing on the less explored unsupervised learning scenario, we compare the two model classes side by side and find that they tend to make different types of errors even when achieving comparable performance. We analyze the distributions of different error classes using two unsupervised tasks as testbeds: converting informally romanized text into the native script of its language (for Russian, Arabic, and Kannada) and translating between a pair of closely related languages (Serbian and Bosnian). Finally, we investigate how combining finite-state and sequence-to-sequence models at decoding time affects the output quantitatively and qualitatively. ... : Accepted to SIGMORPHON 2021 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.2106.12698 https://arxiv.org/abs/2106.12698
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Could you give me a hint? Generating inference graphs for defeasible reasoning ...
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Comparative Error Analysis in Neural and Finite-state Models for Unsupervised Character-level Transduction ...
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Could you give me a hint ? Generating inference graphs for defeasible reasoning ...
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Investigating Robustness of Dialog Models to Popular Figurative Language Constructs ...
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Measuring and Improving Consistency in Pretrained Language Models ...
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Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation ...
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Style is NOT a single variable: Case Studies for Cross-Stylistic Language Understanding ...
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SelfExplain: A Self-Explaining Architecture for Neural Text Classifiers ...
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Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes ...
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StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer ...
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Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes ...
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Extracting Implicitly Asserted Propositions in Argumentation ...
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Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance? ...
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On the Systematicity of Probing Contextualized Word Representations: The Case of Hypernymy in BERT ...
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On aligning OpenIE extractions with Knowledge Bases: A case study
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Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks
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In: Computational Linguistics, Vol 45, Iss 4, Pp 627-665 (2020) (2020)
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