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Found 5 papers, 3 papers with code
SRAI: Towards Standardization of Geospatial AI
Spatial Representations for Artificial Intelligence (srai) is a Python library for working with geospatial data.
Resources and Few-shot Learners for In-context Learning in Slavic Languages
Despite the rapid recent progress in creating accurate and compact in-context learners, most recent work focuses on in-context learning (ICL) for tasks in English.
Assessment of Massively Multilingual Sentiment Classifiers
We use these to assess 11 models and 80 high-quality sentiment datasets (out of 342 raw datasets collected) in 27 languages and included results on the internally annotated datasets.
Unsupervised embedding and similarity detection of microregions using public transport schedules
To use them in machine learning models, it is often necessary to transform them into a vector representation, which has led to the development in the field of spatial data representation learning.
gtfs2vec -- Learning GTFS Embeddings for comparing Public Transport Offer in Microregions
We selected 48 European cities and gathered their public transport timetables in the GTFS format.
