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Hits 1 – 20 of 121
1
Comparative Error Analysis in Neural and Finite-state Models for Unsupervised Character-level Transduction ...
Ryskina, Maria
;
Hovy, Eduard
;
Berg-Kirkpatrick, Taylor
. - : arXiv, 2021
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2
Could you give me a hint? Generating inference graphs for defeasible reasoning ...
Madaan, Aman
;
Rajagopal, Dheeraj
;
Tandon, Niket
. - : arXiv, 2021
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3
Comparative Error Analysis in Neural and Finite-state Models for Unsupervised Character-level Transduction ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Berg-Kirkpatrick, Taylor
;
Gormley, Matthew
. - : Underline Science Inc., 2021
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4
Could you give me a hint ? Generating inference graphs for defeasible reasoning ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Hovy, Eduard
;
Madaan, Aman
;
Rajagopal, Dheeraj
;
Tandon, Niket
;
Yang, Yiming
. - : Underline Science Inc., 2021
Abstract:
Read paper: https://www.aclanthology.org/2021.findings-acl.456 Abstract: Defeasible reasoning is a mode of reasoning where conclusions can be overturned by taking into account new evidence. A commonly used method in cognitive science and logic literature is to handcraft argumentation supporting inference graphs. While humans find inference graphs very useful for reasoning, constructing them at scale is difficult. In this paper, we automatically generate such inference graphs through transfer learning from a related NLP task that shares the kind of reasoning that inference graphs support. Through automated metrics and human evaluation, we find that our method generates meaningful graphs for the defeasible inference task. Human accuracy on this task improves by 20% by consulting the generated graphs. Our findings open up exciting new research avenues for cases where machine reasoning can help human reasoning. ...
Keyword:
Computational Linguistics
;
Condensed Matter Physics
;
Deep Learning
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Electromagnetism
;
FOS Physical sciences
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Information and Knowledge Engineering
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Neural Network
;
Semantics
URL:
https://underline.io/lecture/26547-could-you-give-me-a-hint-question-generating-inference-graphs-for-defeasible-reasoning
https://dx.doi.org/10.48448/pnvq-vt55
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5
Investigating Robustness of Dialog Models to Popular Figurative Language Constructs ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Berg-Kirkpatrick, Taylor
;
Gangal, Varun
. - : Underline Science Inc., 2021
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6
Measuring and Improving Consistency in Pretrained Language Models ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Elazar, Yanai
;
Goldberg, Yoav
. - : Underline Science Inc., 2021
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7
More Identifiable yet Equally Performant Transformers for Text Classification ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Bhardwaj, Rishabh
;
Hovy, Eduard
. - : Underline Science Inc., 2021
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8
Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Berg-Kirkpatrick, Taylor
;
Gangal, Varun Prashant
. - : Underline Science Inc., 2021
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9
Style is NOT a single variable: Case Studies for Cross-Stylistic Language Understanding ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Hovy, Eduard
;
Kang, Dongyeop
. - : Underline Science Inc., 2021
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10
SelfExplain: A Self-Explaining Architecture for Neural Text Classifiers ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Balachandran, Vidhisha
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Hovy, Eduard
. - : Underline Science Inc., 2021
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11
Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes ...
Jo, Yohan
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Bang, Seojin
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Reed, Chris
. - : arXiv, 2021
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12
StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer ...
Lyu, Yiwei
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Liang, Paul Pu
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Pham, Hai
. - : arXiv, 2021
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13
StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer ...
NAACL 2021 2021
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Hovy, Eduard
;
Liang, Paul Pu
. - : Underline Science Inc., 2021
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14
Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Bang, Seojin
;
Hovy, Eduard
. - : Underline Science Inc., 2021
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15
Extracting Implicitly Asserted Propositions in Argumentation ...
Jo, Yohan
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Visser, Jacky
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Reed, Chris
. - : arXiv, 2020
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16
Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance? ...
Ravichander, Abhilasha
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Belinkov, Yonatan
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Hovy, Eduard
. - : arXiv, 2020
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17
Measuring Forecasting Skill from Text ...
Zong, Shi
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Ritter, Alan
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Hovy, Eduard
. - : arXiv, 2020
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18
On the Systematicity of Probing Contextualized Word Representations: The Case of Hypernymy in BERT ...
The 28th International Conference on Computational Linguistics 2020
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Cheung, Jackie Chi Kit
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Hovy, Eduard
. - : Underline Science Inc., 2020
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19
On aligning OpenIE extractions with Knowledge Bases: A case study
Gashteovski, Kiril
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Gemulla, Rainer
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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
Sachan, Mrinmaya
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Dubey, Avinava
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Hovy, Eduard H.
...
In: Computational Linguistics, Vol 45, Iss 4, Pp 627-665 (2020) (2020)
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