Dec 10, 2023 · We propose Compositional Foundation Models for Hierarchical Planning (HiP), a foundation model which leverages multiple expert foundation model trained on language, …

Apr 3, 2025 · We believe that foundation models will dramatically accelerate AI adoption in business. Reducing time spent labeling data and programming models will make it much …

Haoxiang Qiu, Daiki Kimura, Sakai Tomoya, and Katsuki Takayuki, "Exploring Different Types of Foundation Models on Flood Segmentation Datasets", American Geophysical Union Annual …

IBM Research biomedical foundation model (BMFM) technologies leverage multi-modal data of different types, including drug-like small molecules and proteins (covering a total of more than …

We evaluated the SPG-TED289M model's performance across a range of tasks including copolymer phase behavior, polymer membrane properties, multi-task learning, refractive index …

With that in mind, our Foundation Model Evaluation framework (FM-eval) aims at validating and evaluating new large language models (LLMs) coming out of the IBM model factory, alongside …

Here we investigate adding additional data and using weights from a previously trained model. We use Prithvi for the original model, which is a transformer-based model trained on Harmonized …

The second goal is to illustrate the effective integration of ZO-ML techniques with emerging ML/AI applications. This step aims to bridge the theoretical and practical aspects of ZO-ML, …

It is argued that FMs learning from diverse grid data and topologies, which we call grid foundation models (GridFMs), could unlock transformative capabilities, pioneering a new approach to …

Here we show the development and evaluation of a pre-trained geospatial model using downstream tasks specific to the UK and Ireland, such as flood segmentation and above …