Demo Data from EDBT 2026 / reviewers in the wild / expert
Luiza Pozzobon
dblp:345/8535
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 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 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Trustworthy machine learning › AI safety › content safety
toxicity analysis |
0.7 | 1 | 2023 | On the Challenges of Using Black-Box APIs for Toxicity Evaluation in Research · EMNLP 2023 |
Methods — techniques the papers use, named apart from their topics
black-box API scoring · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | On the Challenges of Using Black-Box APIs for Toxicity Evaluation in ResearchabstractPerception of toxicity evolves over time and often differs between geographies and cultural backgrounds.Similarly, black-box commercially available APIs for detecting toxicity, such as the Perspective API, are not static, but frequently retrained to address any unattended weaknesses and biases.We evaluate the implications of these changes on the reproducibility of findings that compare the relative merits of models and methods that aim to curb toxicity.Our findings suggest that research that relied on inherited automatic toxicity scores to compare models and techniques may have resulted in inaccurate findings.Rescoring all models from HELM, a widely respected living benchmark, for toxicity with the recent version of the API led to a different ranking of widely used foundation models.We suggest caution in applying apples-to-apples comparisons between studies and lay recommendations for a more structured approach to evaluating toxicity over time. 1 Luiza Pozzobon, Beyza Ermis, Patrick Lewis 0002, Sara Hooker |
EMNLP | 1 |