Demo Data from SIGIR 2026 / reviewers in the wild / expert
Leslie Kim
dblp:323/5042
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
Trustworthy machine learning · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Trustworthy machine learning › fairness
bias mitigation |
0.6 | 1 | 2022 | REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets · Int. J. Comput. Vis. 2022 |
Machine learning › Trustworthy machine learning
fairness |
0.6 | 1 | 2022 | REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets · Int. J. Comput. Vis. 2022 |
Machine learning › Trustworthy machine learning › dataset bias
visual dataset bias |
0.6 | 1 | 2022 | REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets · Int. J. Comput. Vis. 2022 |
Methods — techniques the papers use, named apart from their topics
dataset auditing · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets
Angelina Wang, Ryan Zhang, Anat Kleiman, Leslie Kim, Dora Zhao, Iroha Shirai, Arvind Narayanan, Olga Russakovsky |
Int. J. Comput. Vis. | 5 |