2 citations · 7 across the 18 of their papers we have counts for
20 papers
GeoX: Mastering Geospatial Reasoning Through Self-Play and Verifiable Rewards
Kyeongjin Ahn, Seungeon Lee, Krishna P. Gummadi +1
Geospatial reasoning requires solving image-grounded problems over the complex spatial structure of a scene. However, developing this capability is hindered by the cost of annotati…
ERA: Evidence-based Reliability Alignment for Honest Retrieval-Augmented Generation
Sunguk Shin, Meeyoung Cha, Byung-Jun Lee +1
Retrieval-Augmented Generation (RAG) grounds language models in factual evidence but introduces critical challenges regarding knowledge conflicts between internalized parameters an…
Dual-Margin Embedding for Fine-Grained Long-Tailed Plant Taxonomy
Cheng Yaw Low, Heejoon Koo, Jaewoo Park +1
Taxonomic classification of ecological families, genera, and species underpins biodiversity monitoring and conservation. Existing computer vision methods typically address fine-gra…
Generalizable Slum Detection from Satellite Imagery with Mixture-of-Experts
Sumin Lee, Sungwon Park, Jeasurk Yang +2
Satellite-based slum segmentation holds significant promise in generating global estimates of urban poverty. However, the morphological heterogeneity of informal settlements presen…
Semi-supervised Shelter Mapping for WASH Accessibility Assessment in Rohingya Refugee Camps
Kyeongjin Ahn, YongHun Suh, Sungwon Han +3
Lack of access to Water, Sanitation, and Hygiene (WASH) services is a major public health concern in refugee camps, where extreme crowding accelerates the spread of communicable di…
Learning Multidimensional Urban Poverty Representation with Satellite Imagery
Sungwon Park, Sumin Lee, Jihee Kim +4
Recent advances in deep learning have enabled the inference of urban socioeconomic characteristics from satellite imagery. However, models relying solely on urbanization traits oft…
GeoReg: Weight-Constrained Few-Shot Regression for Socio-Economic Estimation using LLM
Kyeongjin Ahn, Sungwon Han, Seungeon Lee +6
Socio-economic indicators like regional GDP, population, and education levels, are crucial to shaping policy decisions and fostering sustainable development. This research introduc…
Classifying and Tracking International Aid Contribution Towards SDGs
Sungwon Park, Dongjoon Lee, Kyeongjin Ahn +4
International aid is a critical mechanism for promoting economic growth and well-being in developing nations, supporting progress toward the Sustainable Development Goals (SDGs). H…
Retrieval Augmented Time Series Forecasting
Sungwon Han, Seungeon Lee, Meeyoung Cha +2
Time series forecasting uses historical data to predict future trends, leveraging the relationships between past observations and available features. In this paper, we propose RAFT…
Poverty mapping in Mongolia with AI-based Ger detection reveals urban slums persist after the COVID-19 pandemic
Jeasurk Yang, Sumin Lee, Sungwon Park +2
Mongolia is among the countries undergoing rapid urbanization, and its temporary nomadic dwellings-known as Ger-have expanded into urban areas. Ger settlements in cities are increa…
GeoSEE: Regional Socio-Economic Estimation With a Large Language Model
Sungwon Han, Donghyun Ahn, Seungeon Lee +5
Moving beyond traditional surveys, combining heterogeneous data sources with AI-driven inference models brings new opportunities to measure socio-economic conditions, such as pover…
Adversarial Style Augmentation via Large Language Model for Robust Fake News Detection
Sungwon Park, Sungwon Han, Xing Xie +2
The spread of fake news harms individuals and presents a critical social challenge that must be addressed. Although numerous algorithmic and insightful features have been developed…
Generalizable Disaster Damage Assessment via Change Detection with Vision Foundation Model
Kyeongjin Ahn, Sungwon Han, Sungwon Park +3
The increasing frequency and intensity of natural disasters call for rapid and accurate damage assessment. In response, disaster benchmark datasets from high-resolution satellite i…
FedMID: A Data-Free Method for Using Intermediate Outputs as a Defense Mechanism Against Poisoning Attacks in Federated Learning
Sungwon Han, Hyeonho Song, Sungwon Park +1
Federated learning combines local updates from clients to produce a global model, which is susceptible to poisoning attacks. Most previous defense strategies relied on vectors deri…
Self Supervised Vision for Climate Downscaling
Karandeep Singh, Chaeyoon Jeong, Naufal Shidqi +4
Climate change is one of the most critical challenges that our planet is facing today. Rising global temperatures are already bringing noticeable changes to Earth's weather and cli…
Explainable Product Classification for Customs
Eunji Lee, Sihyeon Kim, Sundong Kim +3
The task of assigning internationally accepted commodity codes (aka HS codes) to traded goods is a critical function of customs offices. Like court decisions made by judges, this t…
Fine-Grained Socioeconomic Prediction from Satellite Images with Distributional Adjustment
Donghyun Ahn, Minhyuk Song, Seungeon Lee +5
While measuring socioeconomic indicators is critical for local governments to make informed policy decisions, such measurements are often unavailable at fine-grained levels like mu…
Towards Attack-tolerant Federated Learning via Critical Parameter Analysis
Sungwon Han, Sungwon Park, Fangzhao Wu +4
Federated learning is used to train a shared model in a decentralized way without clients sharing private data with each other. Federated learning systems are susceptible to poison…
FedDefender: Client-Side Attack-Tolerant Federated Learning
Sungwon Park, Sungwon Han, Fangzhao Wu +4
Federated learning enables learning from decentralized data sources without compromising privacy, which makes it a crucial technique. However, it is vulnerable to model poisoning a…
GraphFC: Customs Fraud Detection with Label Scarcity
Karandeep Singh, Yu-Che Tsai, Cheng-Te Li +2
Custom officials across the world encounter huge volumes of transactions. With increased connectivity and globalization, the customs transactions continue to grow every year. Assoc…