Methods › Natural Language Processing › Entity Retrieval Models › MuVER
MuVER
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Multi-View Entity Representations, or MuVER, is an approach for entity retrieval that constructs multi-view representations for entity descriptions and approximates the optimal view for mentions via a heuristic searching method. It matches a mention to the appropriate entity by comparing it with entity descriptions. Motivated by the fact that mentions with different contexts correspond to different parts in descriptions, multi-view representations are constructed for each description. Specifically, we segment a description into several sentences. We refer to each sentence as a view v, which contains partial information, to form a view set 𝒱 of the entity e. The Figure illustrates an example that constructs a view set 𝒱 for “Kobe Bryant”.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
-
MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity Representations 13 Sep 2021 · 1 repository · arXiv:2109.05716
Tasks archive 2025-07-28
3 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Entity Linking | 1 |
| Entity Retrieval | 1 |
| Retrieval | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections