Demo Data from VLDB 2026 / reviewers in the wild / expert
Iskander Bagautdinov
dblp:435/3462
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0006-2446-7125ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 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.
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 50% Recommender systems · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval › retrieval models
generative retrieval |
1.0 | 1 | 2026 | Mitigating Collaborative Semantic ID Staleness in Generative Retrieval · SIGIR 2026 |
Recommender systems › generative recommendation
semantic ID |
1.0 | 1 | 2026 | Mitigating Collaborative Semantic ID Staleness in Generative Retrieval · SIGIR 2026 |
Methods — techniques the papers use, named apart from their topics
sequence generation · 1.0semantic ID · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Mitigating Collaborative Semantic ID Staleness in Generative RetrievalabstractGenerative retrieval with Semantic IDs (SIDs) assigns each item a discrete identifier and treats retrieval as a sequence generation problem rather than a nearest-neighbor search. While content-only SIDs are stable, they do not take into account user-item interaction patterns, so recent systems construct interaction-informed SIDs. However, as interaction patterns drift over time, these identifiers become stale, i.e., their collaborative semantics no longer match recent logs. Vladimir Baikalov, Iskander Bagautdinov, Sergey Muravyov |
SIGIR | 2 |