James Wexler

2.5k total citations · 1 hit paper
13 papers, 641 citations indexed

About

James Wexler is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, James Wexler has authored 13 papers receiving a total of 641 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 3 papers in Information Systems and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in James Wexler's work include Explainable Artificial Intelligence (XAI) (5 papers), Topic Modeling (5 papers) and Software Engineering Research (3 papers). James Wexler is often cited by papers focused on Explainable Artificial Intelligence (XAI) (5 papers), Topic Modeling (5 papers) and Software Engineering Research (3 papers). James Wexler collaborates with scholars based in United States and Canada. James Wexler's co-authors include Fernanda Viégas, Martin Wattenberg, Mahima Pushkarna, Tolga Bolukbasi, Dilip Krishnan, Kanit Wongsuphasawat, Daniel Smilkov, Ian Tenney, Emily Reif and Ann Yuan and has published in prestigious journals such as IEEE Transactions on Visualization and Computer Graphics, arXiv (Cornell University) and International Symposium/Conference on Music Information Retrieval.

In The Last Decade

James Wexler

12 papers receiving 615 citations

Hit Papers

align trajectories

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.

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
James Wexler United States	7	409	211	87	60	56	13	641
Tarek R. Besold Germany	12	450 1.1×	61 0.3×	56 0.6×	38 0.6×	39 0.7×	42	661
Luwei Xiao China	10	415 1.0×	99 0.5×	25 0.3×	44 0.7×	10 0.2×	27	682
Kartik Talamadupula United States	16	636 1.6×	147 0.7×	49 0.6×	73 1.2×	29 0.5×	55	841
Eric Wallace United States	12	857 2.1×	287 1.4×	36 0.4×	94 1.6×	10 0.2×	20	1.1k
Sarath Sreedharan United States	12	480 1.2×	70 0.3×	91 1.0×	15 0.3×	40 0.7×	44	604
Jay Pujara United States	15	488 1.2×	98 0.5×	22 0.3×	184 3.1×	29 0.5×	65	716
Thilo Stadelmann Switzerland	12	251 0.6×	112 0.5×	18 0.2×	33 0.6×	11 0.2×	63	482
Siva Sai India	14	175 0.4×	81 0.4×	34 0.4×	113 1.9×	14 0.3×	39	598
Caleb Chen Cao Hong Kong	11	350 0.9×	50 0.2×	10 0.1×	125 2.1×	17 0.3×	24	628
Anagha Kulkarni United States	14	331 0.8×	111 0.5×	41 0.5×	180 3.0×	19 0.3×	54	627

Countries citing papers authored by James Wexler

Since Specialization

Citations

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

Fields of papers citing papers by James Wexler

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Wexler

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

13 of 13 papers shown

1.

Wexler, James, et al.. (2026). Strategic Tradeoffs Between Humans and AI in Multi-Agent Bargaining. 1625–1646.

2.

Kahng, Minsuk, Ian Tenney, Mahima Pushkarna, et al.. (2024). LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models. 1–7. 13 indexed citations

3.

Petridis, Savvas, James Wexler, Mahima Pushkarna, et al.. (2024). ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles. 853–868. 11 indexed citations

4.

Petridis, Savvas, et al.. (2024). ConstitutionalExperts: Training a Mixture of Principle-based Prompts. 574–582. 2 indexed citations

5.

Kahng, Minsuk, Ian Tenney, Mahima Pushkarna, et al.. (2024). LLM Comparator: Interactive Analysis of Side-by-Side Evaluation of Large Language Models. IEEE Transactions on Visualization and Computer Graphics. 31(1). 503–513. 7 indexed citations

6.

Reif, Emily, et al.. (2024). Automatic Histograms: Leveraging Language Models for Text Dataset Exploration. 1–9. 3 indexed citations

7.

Mullins, Ryan, et al.. (2023). From Discovery to Adoption: Understanding the ML Practitioners’ Interpretability Journey. 2304–2325. 2 indexed citations

8.

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

9.

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

10.

Roberts, Adam P., et al.. (2019). Approachable Music Composition with Machine Learning at Scale.. International Symposium/Conference on Music Information Retrieval. 793–800. 2 indexed citations

11.

Ghorbani, Amirata, James Wexler, & Been Kim. (2019). Automating Interpretability: Discovering and Testing Visual Concepts Learned by Neural Networks.. arXiv (Cornell University). 7 indexed citations

12.

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 →

13.

Wongsuphasawat, Kanit, Daniel Smilkov, James Wexler, et al.. (2017). Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow. IEEE Transactions on Visualization and Computer Graphics. 24(1). 1–12. 222 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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