Youngjae Yu

2.1k total citations
35 papers, 852 citations indexed

About

Youngjae Yu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Youngjae Yu has authored 35 papers receiving a total of 852 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 18 papers in Artificial Intelligence and 4 papers in Signal Processing. Recurrent topics in Youngjae Yu's work include Multimodal Machine Learning Applications (16 papers), Topic Modeling (9 papers) and Domain Adaptation and Few-Shot Learning (8 papers). Youngjae Yu is often cited by papers focused on Multimodal Machine Learning Applications (16 papers), Topic Modeling (9 papers) and Domain Adaptation and Few-Shot Learning (8 papers). Youngjae Yu collaborates with scholars based in South Korea, United States and United Kingdom. Youngjae Yu's co-authors include Gunhee Kim, Yale Song, Youngjin Kim, Yunseok Jang, Hyungjin Ko, Jongwook Choi, Jong-Seok Kim, Yejin Choi, Ximing Lu and Liwei Jiang and has published in prestigious journals such as Applied Catalysis B: Environmental, International Journal of Computer Vision and BMC Pregnancy and Childbirth.

In The Last Decade

Youngjae Yu

32 papers receiving 831 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Youngjae Yu South Korea	14	665	475	49	18	16	35	852
Vedanuj Goswami United States	7	421 0.6×	410 0.9×	27 0.6×	3 0.2×	15 0.9×	13	581
Armen Aghajanyan United States	6	253 0.4×	290 0.6×	15 0.3×	4 0.2×	24 1.5×	7	427
Yash Goyal India	7	1.0k 1.6×	898 1.9×	13 0.3×	2 0.1×	16 1.0×	13	1.2k
Piyush Sharma United States	4	907 1.4×	707 1.5×	17 0.3×	2 0.1×	8 0.5×	10	1.1k
Kimmo Kärkkäinen United States	5	152 0.2×	133 0.3×	39 0.8×	12 0.7×	10 0.6×	10	311
Sebastian Goodman United States	2	875 1.3×	684 1.4×	16 0.3×	2 0.1×	6 0.4×	2	1.0k
Peipeng Yu China	11	322 0.5×	161 0.3×	85 1.7×	5 0.3×	46 2.9×	18	451
Yaohai Huang China	7	282 0.4×	135 0.3×	121 2.5×	4 0.2×	17 1.1×	10	371
Sheng-Yu Wang United States	7	586 0.9×	195 0.4×	37 0.8×	2 0.1×	16 1.0×	14	702
Houdong Hu United Kingdom	3	469 0.7×	345 0.7×	14 0.3×	2 0.1×	8 0.5×	3	568

Countries citing papers authored by Youngjae Yu

Since Specialization

Citations

This map shows the geographic impact of Youngjae Yu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Youngjae Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Youngjae Yu more than expected).

Fields of papers citing papers by Youngjae Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Youngjae Yu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Youngjae Yu. The network helps show where Youngjae Yu may publish in the future.

Co-authorship network of co-authors of Youngjae Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Youngjae Yu. A scholar is included among the top collaborators of Youngjae Yu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Youngjae Yu. Youngjae Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Kang, SeongKu, et al.. (2024). Pearl: A Review-driven Persona-Knowledge Grounded Conversational Recommendation Dataset. 1105–1120. 5 indexed citations

Yu, Youngjae, et al.. (2024). Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback. 923–940. 1 indexed citations

Han, Seungju, et al.. (2024). SMILE: Multimodal Dataset for Understanding Laughter in Video with Language Models. 1149–1167. 1 indexed citations

Lee, Sangkyu, Sungdong Kim, Ashkan Yousefpour, et al.. (2024). Aligning Large Language Models by On-Policy Self-Judgment. 11442–11459.

Kim, Min-Ju, Harim Kim, Minseok Kang, et al.. (2024). Cactus: Towards Psychological Counseling Conversations using Cognitive Behavioral Theory. 14245–14274. 1 indexed citations

Lee, Jae-Young, Ximing Lu, Jack Hessel, et al.. (2024). How to Train Your Fact Verifier: Knowledge Transfer with Multimodal Open Models. 13060–13077. 1 indexed citations

Cho, Hyunsouk, et al.. (2024). Can Large Language Models be Good Emotional Supporter? Mitigating Preference Bias on Emotional Support Conversation. 15232–15261. 4 indexed citations

Ong, Kai Wen, et al.. (2023). Dialogue Chain-of-Thought Distillation for Commonsense-aware Conversational Agents. 5606–5632. 1 indexed citations

Kim, Hyunwoo, Jack Hessel, Liwei Jiang, et al.. (2023). SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization. 12930–12949. 37 indexed citations

10.

Yu, Youngjae, et al.. (2023). A sustainable carbon-consuming cycle based on sequential activation of CO2 and CH4 using metal oxides. Applied Catalysis B: Environmental. 339. 123120–123120. 5 indexed citations

11.

Li, Liunian Harold, Jack Hessel, Youngjae Yu, et al.. (2023). Symbolic Chain-of-Thought Distillation: Small Models Can Also “Think” Step-by-Step. 2665–2679. 17 indexed citations

12.

Yu, Youngjae, et al.. (2023). VLIS: Unimodal Language Models Guide Multimodal Language Generation. 700–721.

13.

Kim, Hyunwoo, Youngjae Yu, Liwei Jiang, et al.. (2022). ProsocialDialog: A Prosocial Backbone for Conversational Agents. 4005–4029. 34 indexed citations

14.

Yu, Youngjae, et al.. (2022). Maternal disease factors associated with neonatal jaundice: a case–control study. BMC Pregnancy and Childbirth. 22(1). 247–247. 5 indexed citations

15.

Lu, Ximing, Sean Welleck, Peter West, et al.. (2022). NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 780–799. 30 indexed citations

16.

Yu, Youngjae, Sangho Lee, Gunhee Kim, & Yale Song. (2021). Self-Supervised Learning of Compressed Video Representations. International Conference on Learning Representations. 8 indexed citations

17.

Lee, Sangho, Youngjae Yu, Gunhee Kim, et al.. (2021). Parameter Efficient Multimodal Transformers for Video Representation Learning. International Conference on Learning Representations. 1 indexed citations

18.

Yu, Youngjae, et al.. (2021). Pano-AVQA: Grounded Audio-Visual Question Answering on 360deg Videos. 2031–2041. 1 indexed citations

19.

Jang, Yunseok, Yale Song, Youngjae Yu, Youngjin Kim, & Gunhee Kim. (2017). TGIF-QA: Toward Spatio-Temporal Reasoning in Visual Question Answering. 1359–1367. 285 indexed citations

20.

Yu, Youngjae, Hyungjin Ko, Jongwook Choi, & Gunhee Kim. (2016). Video Captioning and Retrieval Models with Semantic Attention.. arXiv (Cornell University). 20 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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