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1
Matching Tweets With Applicable Fact-Checks Across Languages ...
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Deep Learning for Text Style Transfer: A Survey ...
Jin, Di; Jin, Zhijing; Hu, Zhiting. - : ETH Zurich, 2022
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3
Deep Learning for Text Style Transfer: A Survey
In: Computational Linguistics, 48 (1) (2022)
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4
FIBER: Fill-in-the-Blanks as a Challenging Video Understanding Evaluation Framework ...
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5
Exploring Self-Identified Counseling Expertise in Online Support Forums ...
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6
Room to Grow: Understanding Personal Characteristics Behind Self Improvement Using Social Media ...
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7
Analyzing the Surprising Variability in Word Embedding Stability Across Languages ...
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8
STaCK: Sentence Ordering with Temporal Commonsense Knowledge ...
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9
Hitting your MARQ: Multimodal ARgument Quality Assessment in Long Debate Video ...
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10
How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impact ...
Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.273 Abstract: Recent years have seen many breakthroughs in natural language processing (NLP), transitioning it from a mostly theoretical field to one with vast real-world applications. Noting precursor applications in other machine learning and AI techniques with pervasive societal impact, we anticipate the rising importance of developing NLP technologies for social good. Inspired by theories in moral philosophy and global priority research, we aim to promote a future guideline for social good in the context of NLP. We lay the foundations via \textit{moral philosophy}'s definition of social good, and propose a framework to provide a categorization of NLP tasks on the basis of real-world impact, along with metrics to calculate the expected social impact of NLP technology. Based on these fundamental frameworks, we adopt the methodology of global priority research to identify priority causes for NLP research, and use thought experiments to illustrate ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/26364-how-good-is-nlpquestion-a-sober-look-at-nlp-tasks-through-the-lens-of-social-impact
https://dx.doi.org/10.48448/cvg4-8q33
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11
Presidential Address ...
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12
Distinguished Service and Test-Of-Time Awards ...
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13
BUSINESS MEETING ...
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14
Lifetime Award ...
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15
How Good Is NLP?A Sober Look at NLP Tasks through the Lens of Social Impact ...
Jin, Zhijing; Chauhan, Geeticka; Tse, Brian. - : ETH Zurich, 2021
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16
How Good Is NLP?A Sober Look at NLP Tasks through the Lens of Social Impact
In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (2021)
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17
Leveraging Longitudinal Data for Personalized Prediction and Word Representations
Welch, Charles. - 2021
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18
Leveraging Social Media as a Thermometer to Gauge Patient and Caregiver Concerns: COVID-19 and Prostate Cancer
In: Eur Urol Open Sci (2021)
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19
"Judge me by my size (noun), do you?'' YodaLib: A Demographic-Aware Humor Generation Framework ...
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20
Deep Learning for Text Style Transfer: A Survey ...
Jin, Di; Jin, Zhijing; Hu, Zhiting. - : arXiv, 2020
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