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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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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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More Identifiable yet Equally Performant Transformers for Text Classification ...
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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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Abstract:
While argument mining has achieved significant success in classifying argumentative relations between statements (support, attack, and neutral), we have a limited computational understanding of logical mechanisms that constitute those relations. Most recent studies rely on black-box models, which are not as linguistically insightful as desired. On the other hand, earlier studies use rather simple lexical features, missing logical relations between statements. To overcome these limitations, our work classifies argumentative relations based on four logical and theory-informed mechanisms between two statements, namely (i) factual consistency, (ii) sentiment coherence, (iii) causal relation, and (iv) normative relation. We demonstrate that our operationalization of these logical mechanisms classifies argumentative relations without directly training on data labeled with the relations, significantly better than several unsupervised baselines. We further demonstrate that these mechanisms also improve supervised ... : To Appear in TACL 2021 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2105.07571 https://dx.doi.org/10.48550/arxiv.2105.07571
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StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer ...
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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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