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Hits 1 – 20 of 33
1
WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation ...
Liu, Alisa
;
Swayamdipta, Swabha
;
Smith, Noah A.
. - : arXiv, 2022
BASE
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2
COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics ...
Qin, Lianhui
;
Welleck, Sean
;
Khashabi, Daniel
. - : arXiv, 2022
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3
Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection ...
Sap, Maarten
;
Swayamdipta, Swabha
;
Vianna, Laura
. - : arXiv, 2021
BASE
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4
PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World ...
Zellers, Rowan
;
Holtzman, Ari
;
Peters, Matthew
. - : arXiv, 2021
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5
Contrastive Explanations for Model Interpretability ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Choi, Yejin
;
Elazar, Yanai
. - : Underline Science Inc., 2021
BASE
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6
PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World ...
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
;
., Matthew
;
Choi, Yejin
. - : Underline Science Inc., 2021
BASE
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7
Reflective Decoding: Beyond Unidirectional Generation with Off-the-Shelf Language Models ...
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
;
Bhagavatula, Chandra
;
Choi, Yejin
. - : Underline Science Inc., 2021
BASE
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8
Conversational Multi-Hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Arabshahi, Forough
;
Bosselut, Antoine
. - : Underline Science Inc., 2021
BASE
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9
Edited Media Understanding Frames: Reasoning About the Intent and Implications of Visual Misinformation ...
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
;
Bosselut, antoineb@allenai.org
;
Choi, Yejin
. - : Underline Science Inc., 2021
BASE
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10
GO FIGURE: A Meta Evaluation of Factuality in Summarization ...
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
;
Celikyilmaz, Asli
;
Choi, Yejin
. - : Underline Science Inc., 2021
BASE
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11
CLIPScore: A Reference-free Evaluation Metric for Image Captioning ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Choi, Yejin
;
Forbes, Maxwell
. - : Underline Science Inc., 2021
BASE
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12
Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequences ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Choi, Yejin
;
D. Hwang, Jena
. - : Underline Science Inc., 2021
BASE
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13
DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts ...
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
;
Bhagavatula, Chandra
;
Choi, Yejin
. - : Underline Science Inc., 2021
BASE
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14
Challenges in Automated Debiasing for Toxic Language Detection ...
Zhou, Xuhui
;
Sap, Maarten
;
Swayamdipta, Swabha
. - : arXiv, 2021
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15
NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics ...
Lu, Ximing
;
Welleck, Sean
;
West, Peter
. - : arXiv, 2021
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16
From Physical to Social Commonsense: Natural Language and the Natural World
Forbes, Maxwell
. - 2021
Abstract:
Thesis (Ph.D.)--University of Washington, 2021 ; Along with the meteoric rise of computation-hungry models, NLP research has also produced new handcrafted datasets. These datasets allow us to study problems that are difficult by web scraping alone. We can use such data to evaluate and extend machine learning models into new areas. One area of natural interest is work that connects NLP to the outside world. This dissertation describes four projects that present such datasets and computational models. Each project attempts to situate NLP in a context broader than text alone. As a common thread throughout, we make use of commonsense knowledge, either explicitly or implicitly. The first half of the dissertation covers two projects, Verb Physics and Social Chemistry, which contain explicit representations of commonsense knowledge. Respectively, they capture physical commonsense (e.g., that my house is bigger than I am) and social commonsense (e.g., that it's rude for my roommate to run the blender at 5am). The second half studies language production and evaluation. In this half, commonsense implicitly informs the work. Neural Naturalist addresses language generation from image comparisons. Scarecrow focuses on evaluating text generated by large language models. In the conclusion, we urge the field to embrace communication—not merely natural language—and thereby extend the richness of groundings we consider.
Keyword:
commonsense
;
Computer science
;
Computer science and engineering
;
computer vision
;
machine learning
;
natural language processing
;
NLP
;
social norms
URL:
http://hdl.handle.net/1773/48229
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17
Positive AI with Social Commonsense Models
Sap, Maarten
. - 2021
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18
Generative Data Augmentation for Commonsense Reasoning ...
Yang, Yiben
;
Malaviya, Chaitanya
;
Fernandez, Jared
. - : arXiv, 2020
BASE
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19
NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints ...
Lu, Ximing
;
West, Peter
;
Zellers, Rowan
. - : arXiv, 2020
BASE
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20
Understanding Natural Language with Commonsense Knowledge Representation, Reasoning, and Simulation
Bosselut, Antoine
. - 2020
BASE
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