most citedMulti-Task Contrastive Learning for 8192-Token Bilingual Text Embeddings

3 citations · 5 across the 2 of their papers we have counts for

collaborators
Showing cs.CLShow all

2 papers · 1 filter

cs.CL2024★ 2 cited

Jina CLIP: Your CLIP Model Is Also Your Text Retriever

Andreas Koukounas, Georgios Mastrapas, Michael Günther +11

Contrastive Language-Image Pretraining (CLIP) is widely used to train models to align images and texts in a common embedding space by mapping them to fixed-sized vectors. These mod…

cs.CL2024★ 3 cited

Multi-Task Contrastive Learning for 8192-Token Bilingual Text Embeddings

Isabelle Mohr, Markus Krimmel, Saba Sturua +16

We introduce a novel suite of state-of-the-art bilingual text embedding models that are designed to support English and another target language. These models are capable of process…