OlmoEarth v1.3: Embeddings
Overview & Synopsis
We make some OlmoEarth embeddings. To do this, we train a new model: OlmoEarth v1.3. OlmoEarth v1.3 is designed to condense multimodal, multitemporal remote sensing data into a single digestible 64 or 128-dimensional vector. OlmoEarth v1.3 produces state-of-the-art embeddings. In addition, OlmoEarth v1.3 is a strong encoder backbone -- competitive with OlmoEarth v1 and v1.2 -- while requiring 18% and 53% of the GPU hours to train, respectively. We use OlmoEarth v1.3 to compute global, annualized 10m embeddings, which we release under the OlmoEarth artifact license.
Indexed from repository: arXiv
(
arxiv.org)
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Document Information
| Document Title | OlmoEarth v1.3: Embeddings |
|---|---|
| Author / Organization | Gabriel Tseng, Favyen Bastani, Patrick Alan Johnson, Yawen Zhang, Piper Wolters, Ando Shah, Hadrien Sablon, Joseph Redmon, Heather DeHaven, Rachel Ratner, Sasha Levy, Jordan Steward, Katrina Midgley, Andrew Howe, Hunter Pitelka, Ted Schmitt |
| Subject & Discipline | cs.CV |
| Categories | Science & Mathematics |
| Publication Year | 2026 |
| License / Rights | arXiv Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
arXiv
(arxiv.org)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-120382 |
| Original Source Link | Visit Source Page on arxiv.org » |