From the 1 of 7 linked papers with an AI index.
7 papers
Instruction-Tuned Language Models Cannot Sample from Distributions They Can Describe
Chaemin Jang, Dongman Lee, Jihee Kim
The paper demonstrates that instruction-tuned language models collapse to a single answer when asked to sample from a persona's response distribution, even though they can accurate…
Ideological Bias in LLMs' Economic Causal Reasoning
Donggyu Lee, Hyeok Yun, Jungwon Kim +4
Do large language models (LLMs) exhibit systematic ideological bias when reasoning about economic causal effects? As LLMs are increasingly used in policy analysis and economic repo…
EconCausal: A Context-Aware Economic Reasoning Benchmark for Large Language Models
Donggyu Lee, Hyeok Yun, Meeyoung Cha +3
Socio-economic causal effects depend heavily on their institutional and environmental contexts. The same intervention can produce different, even opposite, effects across regulator…
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…
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…
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…