9 citations · 39 across the 11 of their papers we have counts for
12 papers
OlmoEarth v1.2: A more efficient family of OlmoEarth models
Gabriel Tseng, Yawen Zhang, Favyen Bastani +8
We present a set of improvements to the OlmoEarth family. These improvements allow us to cut compute costs during training ( reduction in GPU hours required to train ou…
MolmoWeb: Open Visual Web Agent and Open Data for the Open Web
Tanmay Gupta, Piper Wolters, Zixian Ma +13
Web agents--autonomous systems that navigate and execute tasks on the web on behalf of users--have the potential to transform how people interact with the digital world. However, t…
MolmoB0T: Large-Scale Simulation Enables Zero-Shot Manipulation
Abhay Deshpande, Maya Guru, Rose Hendrix +23
A prevailing view in robot learning is that simulation alone is not enough; effective sim-to-real transfer is widely believed to require at least some real-world data collection or…
MolmoSpaces: A Large-Scale Open Ecosystem for Robot Navigation and Manipulation
Yejin Kim, Wilbert Pumacay, Omar Rayyan +23
Deploying robots at scale demands robustness to the long tail of everyday situations. The countless variations in scene layout, object geometry, and task specifications that charac…
OPTIMUS: Observing Persistent Transformations in Multi-temporal Unlabeled Satellite-data
Raymond Yu, Paul Han, Josh Myers-Dean +2
In the face of pressing environmental issues in the 21st century, monitoring surface changes on Earth is more important than ever. Large-scale remote sensing, such as satellite ima…
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models
Matt Deitke, Christopher Clark, Sangho Lee +47
Today's most advanced vision-language models (VLMs) remain proprietary. The strongest open-weight models rely heavily on synthetic data from proprietary VLMs to achieve good perfor…
On the Generalizability of Foundation Models for Crop Type Mapping
Yi-Chia Chang, Adam J. Stewart, Favyen Bastani +5
Foundation models pre-trained using self-supervised learning have shown powerful transfer learning capabilities on various downstream tasks, including language understanding, text…
Satellite Imagery and AI: A New Era in Ocean Conservation, from Research to Deployment and Impact (Version. 2.0)
Patrick Beukema, Favyen Bastani, Yawen Zheng +3
Illegal, unreported, and unregulated (IUU) fishing poses a global threat to ocean habitats. Publicly available satellite data offered by NASA, the European Space Agency (ESA), and…
Zooming Out on Zooming In: Advancing Super-Resolution for Remote Sensing
Piper Wolters, Favyen Bastani, Aniruddha Kembhavi
Super-Resolution for remote sensing has the potential for huge impact on planet monitoring by producing accurate and realistic high resolution imagery on a frequent basis and a glo…
SatlasPretrain: A Large-Scale Dataset for Remote Sensing Image Understanding
Favyen Bastani, Piper Wolters, Ritwik Gupta +2
Remote sensing images are useful for a wide variety of planet monitoring applications, from tracking deforestation to tackling illegal fishing. The Earth is extremely diverse -- th…
Proposal-based Few-shot Sound Event Detection for Speech and Environmental Sounds with Perceivers
Piper Wolters, Logan Sizemore, Chris Daw +2
Many applications involve detecting and localizing specific sound events within long, untrimmed documents, including keyword spotting, medical observation, and bioacoustic monitori…
A Study of Few-Shot Audio Classification
Piper Wolters, Chris Careaga, Brian Hutchinson +1
Advances in deep learning have resulted in state-of-the-art performance for many audio classification tasks but, unlike humans, these systems traditionally require large amounts of…