187 citations · 334 across the 15 of their papers we have counts for
18 papers
StraTune: Adaptive Selection of Revision Operators for Self-Evolving LLM Skills
Zeping Liu, Yan Li, Ni Lao +2
Large language models (LLMs) can learn reusable textual skills from execution feedback without updating their parameters, but effectively deciding how to revise these skills remain…
PolyTopoBench: A Benchmark for Complex Vector Polygon Generation from Remote Sensing Imagery
Zeping Liu, Ni Lao, Weiwei Sun +5
Vector polygon generation converts visual inputs, e.g., remote sensing (RS) images, into vectorized polygonal geometries, supporting applications such as autonomous driving, vector…
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 Representation Learning for Heterogeneous Vector Geoentities
Jina Kim, Gengchen Mai, Lingyi Zhao +2
Vector geospatial data represent the world as discrete geoentities, such as roads, buildings, and points of interest, each with semantic attributes, geometry, and spatial relations…
TrajGANR: Trajectory-Centric Urban Multimodal Learning via Geospatially Aligned Neural Representations
Maria Despoina Siampou, Gengchen Mai, Ni Lao +4
Many urban prediction tasks depend not only on the static attributes of a location, such as the visual appearance of its built environment, but also on its dynamic function: how pe…
Cross-View Geolocalization and Disaster Mapping with Street-View and VHR Satellite Imagery: A Case Study of Hurricane IAN
Hao Li, Fabian Deuser, Wenping Yina +5
Nature disasters play a key role in shaping human-urban infrastructure interactions. Effective and efficient response to natural disasters is essential for building resilience and…
TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning
Nemin Wu, Qian Cao, Zhangyu Wang +12
Spatial representation learning (SRL) aims at learning general-purpose neural network representations from various types of spatial data (e.g., points, polylines, polygons, network…
Img2Loc: Revisiting Image Geolocalization using Multi-modality Foundation Models and Image-based Retrieval-Augmented Generation
Zhongliang Zhou, Jielu Zhang, Zihan Guan +5
Geolocating precise locations from images presents a challenging problem in computer vision and information retrieval.Traditional methods typically employ either classification, wh…
TransFlower: An Explainable Transformer-Based Model with Flow-to-Flow Attention for Commuting Flow Prediction
Yan Luo, Zhuoyue Wan, Yuzhong Chen +3
Understanding the link between urban planning and commuting flows is crucial for guiding urban development and policymaking. This research, bridging computer science and urban stud…
Revolutionizing Finance with LLMs: An Overview of Applications and Insights
Huaqin Zhao, Zhengliang Liu, Zihao Wu +16
In recent years, Large Language Models (LLMs) like ChatGPT have seen considerable advancements and have been applied in diverse fields. Built on the Transformer architecture, these…
On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications
Chenjiao Tan, Qian Cao, Yiwei Li +15
The advent of large language models (LLMs) has heightened interest in their potential for multimodal applications that integrate language and vision. This paper explores the capabi…
Multimodality of AI for Education: Towards Artificial General Intelligence
Gyeong-Geon Lee, Lehong Shi, Ehsan Latif +10
This paper presents a comprehensive examination of how multimodal artificial intelligence (AI) approaches are paving the way towards the realization of Artificial General Intellige…
Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities
Zhengliang Liu, Yiwei Li, Qian Cao +9
Recent advances in artificial general intelligence (AGI), particularly large language models and creative image generation systems have demonstrated impressive capabilities on dive…
Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages
Yingjie Hu, Gengchen Mai, Chris Cundy +6
Social media messages posted by people during natural disasters often contain important location descriptions, such as the locations of victims. Recent research has shown that many…
Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges
Fei Dou, Jin Ye, Geng Yuan +22
Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and execute tasks with human cognitive abilities, engenders significant anticipation and intrig…