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Jeong-In Hwang

dblp:231/7420 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Language models and text generation · 87% Trustworthy machine learning · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Language models and text generation › controllable text generation
text style transfer		 0.612022
Rethinking Style Transformer with Energy-based Interpretation: Adversarial Unsupervised Style Transfer using a Pretrained Model · EMNLP 2022
Natural language and speech › Language models and text generation › controllable text generation › text style transfer
unsupervised text style transfer		 0.612022
Rethinking Style Transformer with Energy-based Interpretation: Adversarial Unsupervised Style Transfer using a Pretrained Model · EMNLP 2022
Machine learning › Trustworthy machine learning › robustness › adversarial robustness
adversarial training		 0.212022
Rethinking Style Transformer with Energy-based Interpretation: Adversarial Unsupervised Style Transfer using a Pretrained Model · EMNLP 2022

Methods — techniques the papers use, named apart from their topics

pre-trained language model · 0.6energy-based interpretation · 0.6adversarial training · 0.6
YearPublicationVenuePosition
2022 Rethinking Style Transformer with Energy-based Interpretation: Adversarial Unsupervised Style Transfer using a Pretrained Model
abstract
Hojun Cho, Dohee Kim, Seungwoo Ryu, ChaeHun Park, Hyungjong Noh, Jeong-in Hwang, Minseok Choi, Edward Choi, Jaegul Choo. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. 2022.
Hojun Cho, Seungwoo Ryu, Chaehun Park, Hyungjong Noh, Jeong-In Hwang, Minseok Choi, Edward Choi 0003, Jaegul Choo
 EMNLP6