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Found 5 papers, 5 papers with code
Temporal Attention for Language Models
We leverage these representations for the task of semantic change detection; we apply our proposed mechanism to BERT and experiment on three datasets in different languages (English, German, and Latin) that also vary in time, size, and genre.
Time Masking for Temporal Language Models
Our world is constantly evolving, and so is the content on the web.
Event-Driven Query Expansion
A significant number of event-related queries are issued in Web search.
Generating Timelines by Modeling Semantic Change
Though languages can evolve slowly, they can also react strongly to dramatic world events.
Learning Word Relatedness over Time
Search systems are often focused on providing relevant results for the "now", assuming both corpora and user needs that focus on the present.
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