Yiming Miao — accepted AI-conference papers

2026

Bridging the Objective Gap: A Unified Pre-Training Framework for Few-Shot Medical Image Segmentation

Shoupeng Chen, Yiming Miao, Limei Peng, Pin-Han Ho

IJCAI 2026

Few-shot medical image segmentation relies on dense, boundary-sensitive prototype matching, yet common pre-training objectives mainly optimize global alignment or reconstruction, creating an objective gap that hurts boundary delineation and increases adaptation cost. This raises the question: how to

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2024

Rethinking the Effectiveness of Graph Classification Datasets in Benchmarks for Assessing GNNs

Zhengdao Li, Yong Cao, Kefan Shuai, Yiming Miao, Kai Hwang

IJCAI 2024poster

Graph classification benchmarks, vital for assessing and developing graph neural network (GNN) models, have recently been scrutinized, as simple methods like MLPs have demonstrated comparable performance. This leads to an important question: Do these benchmarks effectively distinguish the advancemen…

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