arXiv Machine Learning By Gabriel Tseng, Yawen Zhang, Favyen Bastani, Henry Herzog, Joseph Redmon, Hadrien Sablon, Piper Wolters, Ando Shah, Patrick Alan Johnson, Christopher Wilhelm, Patrick Beukema

OlmoEarth v1.2: A more efficient family of OlmoEarth models

Read the original on arXiv Machine Learning →

arXiv:2605. 20804v2 Announce Type: replace-cross Abstract: We present a set of improvements to the OlmoEarth family.

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arXiv Machine Learning
Aug 4

AdaDINO: Context-Adaptive DINO-Distilled Vision Foundation Models for Efficient Open-Vocabulary Edge Inference

arXiv:2604. 15622v3 Announce Type: replace-cross Abstract: Always-on contextual AI runs language-aligned vision foundation models (VFMs) on edge devices, where the on-device model is the dominant continuous compute cost under strict latency and power limits.

By Yiwei Zhao, Yi Zheng, Huapeng Su, Jieyu Lin, Stefano Ambrogio, Cijo Jose, Michael Ramamonjisoa, Patrick Labatut, Barbara De Salvo, Chiao Liu, Phillip B. Gibbons, Ziyun Li