Junhao Fang — accepted AI-conference papers

2026

GeoBayes: Probabilistic Image Geo-Localization Inference via Sequential Bayesian Updating

Weimin Shi, Xiang Li, Kaige Li, Junhao Fang, Qiang Zhou, Qichuan Geng +1

AAAI 2026technical

Image geo-localization aims to determine the geographic location of a query image. While Multimodal Large Language Models (MLLMs) show potential for this task due to their rich world knowledge and explainable abilities, they often struggle with confirmation bias, i.e., committing to early, potential

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2025

Guiding Large Language Models in Modeling Optimization Problems via Question Partitioning

Xiaotian Pan, Junhao Fang, Feng Wu, Sijia Zhang, Yi-Xiang Hu, Shaoang Li +1

IJCAI 2025

Optimization problems are ubiquitous across various domains, such as resource scheduling, production planning, and sales management. Traditionally, they are modeled manually, leading to inefficiencies due to difficulties in communication and collaboration between modeling and domain experts. The eme

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