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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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More Identifiable yet Equally Performant Transformers for Text Classification ...
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Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation ...
Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.357 Abstract: Multiple different responses are often plausible for a given open domain dialog context. Prior work has shown the importance of having multiple valid reference responses for meaningful and robust automated evaluations. In such cases, common practice has been to collect more human written references. However, such collection can be expensive, time consuming, and not easily scalable. Instead, we propose a novel technique for automatically expanding a human generated reference to a set of candidate references. We fetch plausible references from knowledge sources, and adapt them so that they are more fluent in context of the dialog instance in question. More specifically, we use (1) a commonsense knowledge base to elicit a large number of plausible reactions given the dialog history (2) relevant instances retrieved from dialog corpus, using similar past as well as future contexts. We demonstrate that our automatically expanded reference ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Neural Network; Semantics
URL: https://underline.io/lecture/26448-improving-automated-evaluation-of-open-domain-dialog-via-diverse-reference-augmentation
https://dx.doi.org/10.48448/ht6j-r850
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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
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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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