mlsanityData to 14 Oct 2026

NeuCo-Bench: A Novel Benchmark Framework for Neural Embeddings in Earth Observation

arXiv 2510.17914 ↗First posted 19 Oct 2025cs.LG cs.AI cs.CVcited by 7

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Abstract (arXiv)

We introduce NeuCo-Bench, a novel benchmark framework for evaluating (lossy) neural compression and representation learning in the context of Earth Observation (EO). Our approach builds on fixed-size embeddings that act as compact, task-agnostic representations applicable to a broad range of downstream tasks. NeuCo-Bench comprises three components: (i) an evaluation pipeline built around embeddings, (ii) a challenge mode with a hidden-task leaderboard designed to mitigate pretraining bias, and (iii) a scoring system that balances accuracy and stability. To support reproducibility, we release SSL4EO-S12-downstream, a curated multispectral, multitemporal EO dataset. We present results from a public challenge at the 2025 CVPR EARTHVISION workshop and conduct ablations with state-of-the-art foundation models. NeuCo-Bench provides a step towards community-driven, standardized evaluation of neural embeddings for EO and beyond.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 41 of its 79 references that are in the map. First posted on arXiv 19 Oct 2025.

Builds on

41 of 79 references.

References · 41

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29 more
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Citing papers per year: 2026: 7.

7 papers.