Computer vision & multimodal· 2023
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
On the reading lists
- #125 in the Top 500 (2026 edition)
- #25 in Computer vision & multimodal (2026 edition)
Why it matters
Established the Q-Former approach for efficiently connecting frozen vision encoders and LLMs.
Condensed from the expert lists' notes.
The record
- First released
- 2023 (from arXiv 2301.12597)
- Citations
- 9,535 citations, as counted by Papers With Code (CC BY-SA 4.0)
- Named by
- both expert lists
- Score
- 0.630 · computed rank 125 · consensus 0.91, must-read 0.5, citations percentile 0.877 (2020s · 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.