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BEACON: Behavioral and Semantic Enrichment of AlphaEarth Embeddings through Tri-Modal Contrastive Learning

Paper recorded by Signals 4 on 2026-08-30 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-30 on arXiv · recorded by Signals 4 on 2026-09-01

Category: cs.LG · 机器学习 · first seen 2026-09-01

Abstract

Geospatial foundation models such as the AlphaEarth Foundation produce compact and globally consistent representations of the Earth's surface that transfer effectively to a wide range of downstream tasks. However, because these models are trained primarily on Earth-observation imagery, their embeddings mainly capture physical and spectral characteristics while encoding human activity and urban fun

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#197 most recent of 215 cs.LG papers we have recorded · ↑ newer: Which LLM for Which Work? Budgeted Model Allocation under Uncertain Ev · ↓ older: LoGo: Token-Level Dynamic Local-Global Attention
Cite this page: BEACON: Behavioral and Semantic Enrichment of AlphaEarth Embeddings through Tri-Modal Contrastive Learning: the #197 most recent of 215 cs.LG papers we have recorded (as of 2026-08-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/beacon-behavioral-and-semantic-enrichment-of-alphaearth-embeddings-through-tri-m.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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