Methods › Natural Language Processing › Word Embeddings › TWEC

Temporal Word Embeddings with a Compass

TWEC

7 papers tagged archive 2025-07-28

Introduced by Valerio Di Carlo et al. in Training Temporal Word Embeddings with a Compass

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

TWEC is a method to generate temporal word embeddings: this method is efficient and it is based on a simple heuristic: we train an atemporal word embedding, the compass and we use this embedding to freeze one of the layers of the CBOW architecture. The frozen architecture is then used to train time-specific slices that are all comparable after training.

PaperSource

Papers archive 2025-07-28

7 shown of 7, 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.

Tasks archive 2025-07-28

9 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Word Embeddings6
Diachronic Word Embeddings5
Clustering1
De-aliasing1
Diversity1
General Classification1
Natural Language Understanding1
Relation1
regression1

Usage over time archive 2025-07-28

Papers per year tagged with TWEC: 2019 to 2021, peak 4 4 0 2019: 1 paper 2019 2020: 2 papers 2020 2021: 4 papers 2021
Papers per year the archive tags with this method, by the paper's archive date (7 dated). Bars are counts, not a trend claim.

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

Word Embeddings

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