Language, speech & LLMs· 2019
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
On the reading lists
- #402 in the Top 500 (2026 edition)
- #61 in Language, speech & LLMs (2026 edition)
Why it matters
Factorized embeddings and cross-layer sharing reduce BERT parameters.
Condensed from the expert lists' notes.
The record
- First released
- 2019 (from arXiv 1909.11942)
- Citations
- 7,796 citations, as counted by Papers With Code (CC BY-SA 4.0)
- Named by
- both expert lists
- Score
- 0.380 · computed rank 402 · consensus 0.345, must-read 0, citations percentile 0.789 (2010s · language), awards 0, existing lists 0. Method
Data sources
Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.