Demo Data from EDBT 2026 / reviewers in the wild / expert
Han Zhang 0066
dblp:26/4189-66
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2026
0009-0007-7917-2460ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 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 |
Language models and text generation · 67% Trustworthy machine learning · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Language models and text generation
alignment |
1.0 | 1 | 2026 | Expectation-Guided Self-Verification for Aligning Large Reasoning Models with Domain Knowledge · WWW 2026 |
Natural language and speech › Language models and text generation › alignment
domain knowledge alignment |
1.0 | 1 | 2026 | Expectation-Guided Self-Verification for Aligning Large Reasoning Models with Domain Knowledge · WWW 2026 |
Machine learning › Trustworthy machine learning › verification
self-verification |
1.0 | 1 | 2026 | Expectation-Guided Self-Verification for Aligning Large Reasoning Models with Domain Knowledge · WWW 2026 |
Methods — techniques the papers use, named apart from their topics
expectation-guided decoding · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Expectation-Guided Self-Verification for Aligning Large Reasoning Models with Domain Knowledge
Han Zhang 0066 |
WWW | 1 |