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Iskander Bagautdinov

dblp:435/3462 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Information retrieval › retrieval models
generative retrieval
1.012026
Mitigating Collaborative Semantic ID Staleness in Generative Retrieval · SIGIR 2026
Recommender systems › generative recommendation
semantic ID
1.012026
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
YearPublicationVenuePosition
2026 Mitigating Collaborative Semantic ID Staleness in Generative Retrieval
abstract
Generative 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
SIGIR2