2 citations · 3 across the 8 of their papers we have counts for
4 papers · 1 filter
Evaluating the Interpretability of Sparse Autoencoders with Concept Annotations
Jonas Klotz, Cassio F. Dantas, Pallavi Jain +2
Sparse autoencoders (SAEs) are increasingly used to extract interpretable concepts from vision and vision language models, yet existing evaluation methods largely rely on proxy met…
TimeSenCLIP: A Time Series Vision-Language Model for Remote Sensing
Pallavi Jain, Diego Marcos, Dino Ienco +2
Vision-language models (VLMs) have shown significant promise in remote sensing applications, particularly for land-use and land-cover (LULC) mapping via zero-shot classification an…
EcoWikiRS: Learning Ecological Representation of Satellite Images from Weak Supervision with Species Observations and Wikipedia
Valerie Zermatten, Javiera Castillo-Navarro, Pallavi Jain +2
The presence of species provides key insights into the ecological properties of a location such as land cover, climatic conditions or even soil properties. We propose a method to p…
SenCLIP: Enhancing zero-shot land-use mapping for Sentinel-2 with ground-level prompting
Pallavi Jain, Dino Ienco, Roberto Interdonato +2
Pre-trained vision-language models (VLMs), such as CLIP, demonstrate impressive zero-shot classification capabilities with free-form prompts and even show some generalization in sp…