Eugene Yang

1.0k total citations · 1 hit paper
28 papers, 480 citations indexed

About

Eugene Yang is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Eugene Yang has authored 28 papers receiving a total of 480 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 8 papers in Information Systems and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Eugene Yang's work include Topic Modeling (9 papers), Information Retrieval and Search Behavior (5 papers) and Natural Language Processing Techniques (5 papers). Eugene Yang is often cited by papers focused on Topic Modeling (9 papers), Information Retrieval and Search Behavior (5 papers) and Natural Language Processing Techniques (5 papers). Eugene Yang collaborates with scholars based in United States, Taiwan and United Kingdom. Eugene Yang's co-authors include Ophir Frieder, Sean MacAvaney, Katina Russell, Nazli Goharian, Jon W. Tolle, Oded Berman, David Lewis, Nathanael Chambers, Eric Van Young and Douglas W. Oard and has published in prestigious journals such as PLoS ONE, European Journal of Operational Research and Journal of the Operational Research Society.

In The Last Decade

Eugene Yang

21 papers receiving 443 citations

Hit Papers

Hate speech detection: Challenges and solutions 2019 2026 2021 2023 2019 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Hate speech detection: Challenges and solutions
    2019 323 citations Sean MacAvaney, Eugene Yang et al. PLoS ONE profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eugene Yang United States 7 364 96 87 64 56 28 480
Roy Ka-Wei Lee Singapore 15 537 1.5× 117 1.2× 46 0.5× 108 1.7× 58 1.0× 63 721
Lisa Kaati Sweden 14 385 1.1× 254 2.6× 66 0.8× 339 5.3× 84 1.5× 52 697
Marcelo G. Armentano Argentina 11 162 0.4× 187 1.9× 14 0.2× 64 1.0× 9 0.2× 36 365
Delip Rao United States 8 780 2.1× 241 2.5× 70 0.8× 127 2.0× 25 0.4× 18 976
Shuiqiao Yang Australia 12 326 0.9× 91 0.9× 14 0.2× 89 1.4× 43 0.8× 26 496
Constantinos Djouvas Cyprus 9 387 1.1× 101 1.1× 86 1.0× 49 0.8× 41 0.7× 34 539
Ahmed Abdelalí Qatar 18 924 2.5× 180 1.9× 21 0.2× 93 1.5× 27 0.5× 76 1.0k
Mike Develin United States 10 53 0.1× 11 0.1× 22 0.3× 39 0.6× 12 0.2× 29 526
Bharat Ram Ambati India 9 675 1.9× 100 1.0× 14 0.2× 45 0.7× 19 0.3× 22 808
Hatem Haddad Tunisia 9 286 0.8× 146 1.5× 31 0.4× 16 0.3× 20 0.4× 33 398

Countries citing papers authored by Eugene Yang

Since Specialization
Citations

This map shows the geographic impact of Eugene Yang'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 Eugene Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eugene Yang more than expected).

Fields of papers citing papers by Eugene Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eugene Yang. 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 Eugene Yang. The network helps show where Eugene Yang may publish in the future.

Co-authorship network of co-authors of Eugene Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Eugene Yang. A scholar is included among the top collaborators of Eugene Yang 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 Eugene Yang. Eugene Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yates, Andrew, et al.. (2025). MMMORRF: Multimodal Multilingual MOdularized Reciprocal Rank Fusion. 4004–4009.
2.
Yang, Eugene, Andrew Yates, Kenton Murray, et al.. (2025). Video-ColBERT: Contextualized Late Interaction for Text-to-Video Retrieval. 19691–19701.
3.
4.
Yang, Eugene, Dawn Lawrie, & James Mayfield. (2024). Distillation for Multilingual Information Retrieval. arXiv (Cornell University). 2368–2373. 1 indexed citations
5.
Mayfield, James, Eugene Yang, Dawn Lawrie, et al.. (2024). On the Evaluation of Machine-Generated Reports. arXiv (Cornell University). 1904–1915. 6 indexed citations
6.
Yang, Eugene, et al.. (2024). Language Fairness in Multilingual Information Retrieval. arXiv (Cornell University). 2487–2491. 1 indexed citations
7.
Nair, Suraj, Eugene Yang, Dawn Lawrie, James Mayfield, & Douglas W. Oard. (2023). BLADE: Combining Vocabulary Pruning and Intermediate Pretraining for Scaleable Neural CLIR. 1219–1229. 1 indexed citations
8.
Yang, Eugene, et al.. (2022). C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrieval. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2507–2512. 10 indexed citations
9.
MacAvaney, Sean, et al.. (2019). Hate speech detection: Challenges and solutions. PLoS ONE. 14(8). e0221152–e0221152. 323 indexed citations breakdown →
10.
Yang, Eugene, David Lewis, & Ophir Frieder. (2019). A Regularization Approach to Combining Keywords and Training Data in Technology-Assisted Review. 153–162. 4 indexed citations
11.
Yang, Eugene, David Lewis, & Ophir Frieder. (2019). Text Retrieval Priors for Bayesian Logistic Regression. 1045–1048. 2 indexed citations
12.
Yang, Eugene, et al.. (2018). Retrieval and Richness when Querying by Document.. 68–75. 1 indexed citations
13.
Yang, Eugene. (2018). Fuzz testing & software composition analysis in software engineering. 1–3. 3 indexed citations
14.
Yang, Eugene, David A. Grossman, Ophir Frieder, & Roman Yurchak. (2017). Effectiveness results for popular e-discovery algorithms. 261–264. 10 indexed citations
15.
Yang, Eugene, et al.. (2013). USNA: A Dual-Classifier Approach to Contextual Sentiment Analysis. Joint Conference on Lexical and Computational Semantics. 2. 390–394.
16.
Lin, Chih‐Jen, Eugene Yang, Shu-Cherng Fang, & Soon‐Yi Wu. (1995). Implementation of an inexact approach to solving linear semi-infinite programming problems. Journal of Computational and Applied Mathematics. 61(1). 87–103. 5 indexed citations
17.
Yang, Eugene, et al.. (1992). Rank revealing LU factorizations. Linear Algebra and its Applications. 175. 115–141. 17 indexed citations
18.
Yang, Eugene, et al.. (1992). A barrier method for dynamic Leontief-type linear programs. European Journal of Operational Research. 60(3). 296–305. 1 indexed citations
19.
Berman, Oded & Eugene Yang. (1991). Medi-centre Location Problems. Journal of the Operational Research Society. 42(4). 313–322.
20.
Yang, Eugene & Jon W. Tolle. (1991). A class of methods for solving large, convex quadratic programs subject to box constraints. Mathematical Programming. 51(1-3). 223–228. 46 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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