Tolga Bolukbasi

3.7k total citations · 2 hit papers
15 papers, 1.2k citations indexed

About

Tolga Bolukbasi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Safety Research. According to data from OpenAlex, Tolga Bolukbasi has authored 15 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Safety Research. Recurrent topics in Tolga Bolukbasi's work include Topic Modeling (6 papers), Natural Language Processing Techniques (4 papers) and Machine Learning and Data Classification (3 papers). Tolga Bolukbasi is often cited by papers focused on Topic Modeling (6 papers), Natural Language Processing Techniques (4 papers) and Machine Learning and Data Classification (3 papers). Tolga Bolukbasi collaborates with scholars based in United States, India and Canada. Tolga Bolukbasi's co-authors include Venkatesh Saligrama, Kai-Wei Chang, Adam Tauman Kalai, James Zou, Fernanda Viégas, James Wexler, Mahima Pushkarna, Martin Wattenberg, Andrei Kapishnikov and Michael Terry and has published in prestigious journals such as IEEE Transactions on Visualization and Computer Graphics, arXiv (Cornell University) and PolyPublie (École Polytechnique de Montréal).

In The Last Decade

Tolga Bolukbasi

13 papers receiving 1.1k citations

Hit Papers

align trajectories sort by overperformance

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.

Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings

2016 625 citations Tolga Bolukbasi, Kai-Wei Chang et al. arXiv (Cornell University) profile →
The What-If Tool: Interactive Probing of Machine Learning Models

2019 294 citations James Wexler, Mahima Pushkarna et al. IEEE Transactions on Visualization and Computer Graphics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tolga Bolukbasi United States	6	810	217	217	123	95	15	1.2k
Jieyu Zhao China	14	804 1.0×	328 1.5×	178 0.8×	82 0.7×	50 0.5×	95	1.3k
Dallas Card United States	13	766 0.9×	51 0.2×	147 0.7×	225 1.8×	38 0.4×	24	1.1k
Yulia Tsvetkov United States	21	1.4k 1.7×	154 0.7×	56 0.3×	145 1.2×	34 0.4×	96	1.7k
Mark Yatskar United States	12	1.3k 1.6×	663 3.1×	153 0.7×	67 0.5×	42 0.4×	23	1.6k
Jahna Otterbacher Cyprus	22	1.0k 1.3×	134 0.6×	179 0.8×	396 3.2×	39 0.4×	88	1.7k
Alexandra Olteanu United States	16	725 0.9×	39 0.2×	212 1.0×	534 4.3×	45 0.5×	44	1.5k
Kuntal Dey India	15	638 0.8×	141 0.6×	311 1.4×	78 0.6×	88 0.9×	54	1.1k
Amy X. Zhang United States	18	501 0.6×	99 0.5×	92 0.4×	451 3.7×	17 0.2×	79	1.2k
Joseph O’Brien United States	6	285 0.4×	64 0.3×	43 0.2×	78 0.6×	18 0.2×	22	643
Isabelle Augenstein Denmark	22	1.3k 1.7×	138 0.6×	30 0.1×	386 3.1×	59 0.6×	88	1.6k

Countries citing papers authored by Tolga Bolukbasi

Since Specialization

Citations

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

Fields of papers citing papers by Tolga Bolukbasi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tolga Bolukbasi

This figure shows the co-authorship network connecting the top 25 collaborators of Tolga Bolukbasi. A scholar is included among the top collaborators of Tolga Bolukbasi 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 Tolga Bolukbasi. Tolga Bolukbasi 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:

15 of 15 papers shown

Bolukbasi, Tolga, et al.. (2023). Self-Influence Guided Data Reweighting for Language Model Pre-training. PolyPublie (École Polytechnique de Montréal). 2033–2045. 2 indexed citations

Mozes, Maximilian, Jessica D. Hoffmann, Katrin Tomanek, et al.. (2023). Towards Agile Text Classifiers for Everyone. 400–414. 2 indexed citations

Akyürek, Ekin, et al.. (2022). Towards Tracing Knowledge in Language Models Back to the Training Data. 2429–2446. 16 indexed citations

Tenney, Ian, James Wexler, Jasmijn Bastings, et al.. (2020). The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models. 107–118. 73 indexed citations

Wexler, James, et al.. (2020). Probing ML models for fairness with the what-if tool and SHAP. 705–705. 5 indexed citations

Kapishnikov, Andrei, Tolga Bolukbasi, Fernanda Viégas, & Michael Terry. (2019). Segment Integrated Gradients: Better attributions through regions.. arXiv (Cornell University). 3 indexed citations

Kapishnikov, Andrei, Tolga Bolukbasi, Fernanda Viégas, & Michael Terry. (2019). XRAI: Better Attributions Through Regions. 4947–4956. 123 indexed citations

Prost, Flavien, Nithum Thain, & Tolga Bolukbasi. (2019). Debiasing Embeddings for Fairer Text Classification. 1 indexed citations

Wexler, James, et al.. (2019). The What-If Tool: Interactive Probing of Machine Learning Models. IEEE Transactions on Visualization and Computer Graphics. 26(1). 1–1. 294 indexed citations breakdown →

10.

Bolukbasi, Tolga, et al.. (2019). Robust Text Classifier on Test-Time Budgets. 1167–1172. 1 indexed citations

11.

Bolukbasi, Tolga, et al.. (2018). Building a Robust Text Classifier on a Test-Time Budget.. arXiv (Cornell University). 1 indexed citations

12.

Bolukbasi, Tolga, Joseph Wang, Ofer Dekel, & Venkatesh Saligrama. (2017). Adaptive Neural Networks for Fast Test-Time Prediction.. arXiv (Cornell University). 21 indexed citations

13.

Bolukbasi, Tolga, Kai-Wei Chang, Joseph Wang, & Venkatesh Saligrama. (2017). Resource Constrained Structured Prediction. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 1 indexed citations

14.

Bolukbasi, Tolga, Kai-Wei Chang, Joseph Wang, & Venkatesh Saligrama. (2016). Resource Constrained Structured Prediction. arXiv (Cornell University). 31(1). 1756–1762. 1 indexed citations

15.

Bolukbasi, Tolga, Kai-Wei Chang, James Zou, Venkatesh Saligrama, & Adam Tauman Kalai. (2016). Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. arXiv (Cornell University). 625 indexed citations breakdown →

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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