6 citations · 16 across the 9 of their papers we have counts for
10 papers
Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalization
Ayan Majumdar, Shounak Paul, Pushpdeep Singh +6
The growing complexity of content moderation policies presents a critical challenge for their consistent operationalization. While foundation models possess the basic capabilities…
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…
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…
Tabular Feature Discovery With Reasoning Type Exploration
Sungwon Han, Sungkyu Park, Seungeon Lee
Feature engineering for tabular data remains a critical yet challenging step in machine learning. Recently, large language models (LLMs) have been used to automatically generate ne…
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…
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…
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…
DualFair: Fair Representation Learning at Both Group and Individual Levels via Contrastive Self-supervision
Sungwon Han, Seungeon Lee, Fangzhao Wu +5
Algorithmic fairness has become an important machine learning problem, especially for mission-critical Web applications. This work presents a self-supervised model, called DualFair…
Self-explaining deep models with logic rule reasoning
Seungeon Lee, Xiting Wang, Sungwon Han +3
We present SELOR, a framework for integrating self-explaining capabilities into a given deep model to achieve both high prediction performance and human precision. By "human precis…
Elsa: Energy-based learning for semi-supervised anomaly detection
Sungwon Han, Hyeonho Song, Seungeon Lee +2
Anomaly detection aims at identifying deviant instances from the normal data distribution. Many advances have been made in the field, including the innovative use of unsupervised c…