Computer vision & multimodal· 2019
LXMERT: Learning Cross-Modality Encoder Representations from Transformers
On the reading lists
- #427 in the Top 500 (2026 edition)
- #67 in Computer vision & multimodal (2026 edition)
Why it matters
Established influential language, object, and cross-modality encoder architecture for visual reasoning.
Condensed from the expert lists' notes.
The record
- First released
- 2019 (from arXiv 1908.07490)
- Citations
- 3,070 citations, as counted by Papers With Code (CC BY-SA 4.0)
- Named by
- both expert lists
- Score
- 0.369 · computed rank 427 · consensus 0.75, must-read 0, citations percentile 0.412 (2010s · vision), 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.