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1
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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3
Comparative Error Analysis in Neural and Finite-state Models for Unsupervised Character-level Transduction ...
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4
Could you give me a hint ? Generating inference graphs for defeasible reasoning ...
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5
Investigating Robustness of Dialog Models to Popular Figurative Language Constructs ...
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6
Measuring and Improving Consistency in Pretrained Language Models ...
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7
More Identifiable yet Equally Performant Transformers for Text Classification ...
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8
Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation ...
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9
Style is NOT a single variable: Case Studies for Cross-Stylistic Language Understanding ...
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10
SelfExplain: A Self-Explaining Architecture for Neural Text Classifiers ...
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11
Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes ...
Jo, Yohan; Bang, Seojin; Reed, Chris. - : arXiv, 2021
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12
StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer ...
Lyu, Yiwei; Liang, Paul Pu; Pham, Hai. - : arXiv, 2021
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13
StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer ...
NAACL 2021 2021; Hovy, Eduard; Liang, Paul Pu. - : Underline Science Inc., 2021
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14
Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes ...
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15
Extracting Implicitly Asserted Propositions in Argumentation ...
Jo, Yohan; Visser, Jacky; Reed, Chris. - : arXiv, 2020
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16
Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance? ...
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17
Measuring Forecasting Skill from Text ...
Zong, Shi; Ritter, Alan; Hovy, Eduard. - : arXiv, 2020
Abstract: People vary in their ability to make accurate predictions about the future. Prior studies have shown that some individuals can predict the outcome of future events with consistently better accuracy. This leads to a natural question: what makes some forecasters better than others? In this paper we explore connections between the language people use to describe their predictions and their forecasting skill. Datasets from two different forecasting domains are explored: (1) geopolitical forecasts from Good Judgment Open, an online prediction forum and (2) a corpus of company earnings forecasts made by financial analysts. We present a number of linguistic metrics which are computed over text associated with people's predictions about the future including: uncertainty, readability, and emotion. By studying linguistic factors associated with predictions, we are able to shed some light on the approach taken by skilled forecasters. Furthermore, we demonstrate that it is possible to accurately predict forecasting ... : Accepted at ACL 2020 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2006.07425
https://arxiv.org/abs/2006.07425
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18
On the Systematicity of Probing Contextualized Word Representations: The Case of Hypernymy in BERT ...
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19
On aligning OpenIE extractions with Knowledge Bases: A case study
Gashteovski, Kiril; Gemulla, Rainer; Kotnis, Bhushan. - : Association for Computational Linguistics (ACL), 2020
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20
Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks
In: Computational Linguistics, Vol 45, Iss 4, Pp 627-665 (2020) (2020)
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