Seunghak Yu

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Citations	1337	1255
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Preslav NakovMBZUAIVerified email at mbzuai.ac.ae
Giovanni Da San MartinoAssociate Professor, Department of Mathematics, University of Padova, ItalyVerified email at math.unipd.it
Alberto Barrón-CedeñoUniversità di BolognaVerified email at unibo.it
Heriberto CuayáhuitlUniversity of Lincoln, School of Computer Science, UKVerified email at lincoln.ac.uk
Sungroh YoonProfessor, Electrical and Computer Engineering & Artificial Intelligence, Seoul National UniversityVerified email at snu.ac.kr
Nilesh KulkarniUniversity of MichiganVerified email at umich.edu
Seohyun BackSamsung Research AI Center & KAISTVerified email at samsung.com
James GlassMIT Computer Science and Artificial Intelligence LaboratoryVerified email at mit.edu
Roberto Di PietroIEEE Fellow; ACM Distinguished Scientist; Full Professor of Cybersecurity, KAUSTVerified email at kaust.edu.sa
Stefano CresciIIT-CNR, ItalyVerified email at iit.cnr.it
Alexander SchwingUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
Alessandro MoschittiPrincipal Scientist at Amazon AlexaVerified email at amazon.com
Mitra MohtaramiResearch Scientist at MIT CSAILVerified email at csail.mit.edu
Tianxing HeUniversity of WashingtonVerified email at cs.washington.edu
Rhiju DasHHMI & Stanford UniversityVerified email at stanford.edu
Hanjoo KimGauss Labs Inc.Verified email at gausslabs.ai
Jinkyu KimUC BerkeleyVerified email at berkeley.edu
Jaegul ChooAssociate Professor, Graduate School of Artificial Intelligence, KAISTVerified email at kaist.ac.kr
Hongyin LuoMIT CSAILVerified email at mit.edu
Jisoo MokSeoul National UniversityVerified email at snu.ac.kr

Seunghak Yu

NAVER Search US

Verified email at mit.edu - Homepage

artificial intelligence machine learning natural language processing


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Fine-grained analysis of propaganda in news article G Da San Martino, Y Seunghak, A Barrón-Cedeno, R Petrov, P Nakov Proceedings of the 2019 conference on empirical methods in natural language …, 2019	378	2019
A survey on computational propaganda detection GDS Martino, S Cresci, A Barrón-Cedeño, S Yu, R Di Pietro, P Nakov arXiv preprint arXiv:2007.08024, 2020	200	2020
Factor graph attention I Schwartz, S Yu, T Hazan, AG Schwing Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	130	2019
Ensemble-based deep reinforcement learning for chatbots H Cuayáhuitl, D Lee, S Ryu, Y Cho, S Choi, S Indurthi, S Yu, H Choi, ... Neurocomputing 366, 118-130, 2019	95	2019
Prta: A system to support the analysis of propaganda techniques in the news GDS Martino, S Shaar, Y Zhang, S Yu, A Barrón-Cedeno, P Nakov arXiv preprint arXiv:2005.05854, 2020	62	2020
Deep Reinforcement Learning for Multi-Domain Dialogue Systems H Cuayáhuitl, S Yu, A Williamson, J Carse Thirtieth Annual Conference on Neural Information Processing Systems (NIPS …, 2016	49	2016
Supervised clustering of questions into intents for dialog system applications I Haponchyk, A Uva, S Yu, O Uryupina, A Moschitti Proceedings of the 2018 conference on empirical methods in natural language …, 2018	47	2018
Interpretable propaganda detection in news articles S Yu, GDS Martino, M Mohtarami, J Glass, P Nakov arXiv preprint arXiv:2108.12802, 2021	32	2021
Scaling up deep reinforcement learning for multi-domain dialogue systems H Cuayahuitl, S Yu, A Williamson, J Carse International Joint Conference on Neural Networks (IJCNN), Anchorage, Alaska …, 2017	32	2017
On-device neural language model based word prediction S Yu, N Kulkarni, H Lee, J Kim Proceedings of the 27th international conference on computational …, 2018	31	2018
A Multi-Stage Memory Augmented Neural Network for Machine Reading Comprehension S Yu, SR Indurthi, S Back, H Lee MRQA @ ACL 2018 (2018): 21., 2018	28	2018
A robust peak detection method for RNA structure inference by high-throughput contact mapping J Kim, S Yu, B Shim, H Kim, H Min, EY Chung, R Das, S Yoon Bioinformatics 25 (9), 1137-1144, 2009	28	2009
Ensemble learning can significantly improve human microRNA target prediction S Yu, J Kim, H Min, S Yoon Methods 69 (3), 220-229, 2014	26	2014
Cut to the Chase: A Context Zoom-in Network for Reading Comprehension S Indurthi, S Yu, S Back, H Cuayáhuitl Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018	18*	2018
Deep reinforcement learning of dialogue policies with less weight updates H Cuayahuitl, S Yu Interspeech, Stockholm, Sweden, August 2017, 2017	18	2017
Experiments in detecting persuasion techniques in the news S Yu, GDS Martino, P Nakov arXiv preprint arXiv:1911.06815, 2019	17	2019
MemoReader: Large-scale reading comprehension through neural memory controller S Back, S Yu, SR Indurthi, J Kim, J Choo Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018	17	2018
Syllable-level Neural Language Model for Agglutinative Language S Yu, N Kulkarni, H Lee, J Kim SCLeM @ EMNLP 2017 (2017): 92., 2017	16	2017
Answer message recommendation method and device therefor YU Seung-Hak, E Ko, D Kim, HJ Lee US Patent 10,469,412, 2019	14	2019
Autokg: Constructing virtual knowledge graphs from unstructured documents for question answering S Yu, T He, J Glass arXiv preprint arXiv:2008.08995, 2020	12*	2020

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