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20232025
most citedMany-Shot In-Context Learning in Multimodal Foundation Models

5 citations · 11 across the 7 of their papers we have counts for

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cs.CV2025

Spatiotemporal Pyramid Flow Matching for Climate Emulation

Jeremy Andrew Irvin, Jiaqi Han, Zikui Wang +6

Generative models have the potential to transform the way we emulate Earth's changing climate. Previous generative approaches rely on weather-scale autoregression for climate emula…

cs.CV2024

CloudTracks: A Dataset for Localizing Ship Tracks in Satellite Images of Clouds

Muhammad Ahmed Chaudhry, Lyna Kim, Jeremy Irvin +5

Clouds play a significant role in global temperature regulation through their effect on planetary albedo. Anthropogenic emissions of aerosols can alter the albedo of clouds, but th…

cs.CV2023

An Empirical Study of Automated Mislabel Detection in Real World Vision Datasets

Maya Srikanth, Jeremy Irvin, Brian Wesley Hill +3

Major advancements in computer vision can primarily be attributed to the use of labeled datasets. However, acquiring labels for datasets often results in errors which can harm mode…

cs.CV2023★ 4 cited

USat: A Unified Self-Supervised Encoder for Multi-Sensor Satellite Imagery

Jeremy Irvin, Lucas Tao, Joanne Zhou +4

Large, self-supervised vision models have led to substantial advancements for automatically interpreting natural images. Recent works have begun tailoring these methods to remote s…

cs.CV2023★ 1 cited

Weakly-semi-supervised object detection in remotely sensed imagery

Ji Hun Wang, Jeremy Irvin, Beri Kohen Behar +4

Deep learning for detecting objects in remotely sensed imagery can enable new technologies for important applications including mitigating climate change. However, these models oft…