187 citations · 235 across the 10 of their papers we have counts for
16 papers
Earth System World Model for What-If Simulations: A Case Study for Terrestrial Ecosystems
Zhihao Wang, Ruichen Wang, Ruohan Li +6
Machine learning emulators have become essential for accelerating expensive Earth-system simulations, but most existing approaches remain passive forecasters: they reproduce simula…
When AI Writes, Who Gets Cited? Evidence of Citation Monoculture Across Language Models
Sina Alemohammad, Denghui Zhang, Bolong Tang +5
As language models move from drafting prose to running literature-search agents with tool calls, fabricated references are becoming easier to catch and constrain. The harder failur…
Spatial Representation Learning Beyond Pixels: Unifying Raster Data and Vector Semantics for Human-Centric Geospatial Foundation Models
Steffen Knoblauch, Hao Li, Gengchen Mai +3
Earth Observation (EO) has fundamentally transformed the monitoring of environmental processes and human activities up to planetary scale. Recent advances in self-supervised learni…
Beyond Visual Fidelity: Benchmarking Super-Resolution Models for Large-Scale Remote Sensing Imagery via Downstream Task Integration
Zhili Li, Kangyang Chai, Zhihao Wang +6
Super-resolution (SR) techniques have made major advances in reconstructing high-resolution images from low-resolution inputs. The increased resolution provides visual enhancement…
NARA: Anchor-Conditioned Relation-Aware Contextualization of Heterogeneous Geoentities
Jina Kim, Gengchen Mai, Lingyi Zhao +2
Geospatial foundation models have primarily focused on raster data such as satellite imagery, where self-supervised learning has been widely studied. Vector geospatial data instead…
TRAJGANR: Trajectory-Centric Urban Multimodal Learning via Geospatially Aligned Neural Representations
Maria Despoina Siampou, Gengchen Mai, Ni Lao +4
Multimodal self-supervised learning (MSSL) has emerged as a key paradigm for pretraining geospatial foundation models. However, existing geospatial MSSL methods are mainly designed…