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Kun Yu

7 accepted papers

2026

CliCARE: Grounding Large Language Models in Clinical Guidelines for Decision Support over Longitudinal Cancer Electronic Health Records

AAAI 2026technical

Large Language Models (LLMs) hold significant promise for improving clinical decision support and reducing physician burnout by synthesizing complex, longitudinal cancer Electronic Health Records (EHRs). However, their implementation in this critical field faces three primary challenges: the inabili

Cited by 0SourcePDFScholar
2023

An Application of Quantum Mechanics to Attention Methods in Computer Vision

ICASSP 2023accepted

This work proposes the quantum-state-based mapping (QSM) for machine learning. QSM uses wave functions that describe microscopic particle systems as mappings. By QSM, original inputs or features extracted by neural networks are processed as quantum states to train wave function parameters. QSM has a…

Cited by 0SourceScholar
2023

Dynamic Graph Learning With Content-Guided Spatial-Frequency Relation Reasoning for Deepfake Detection

CVPR 2023poster

With the springing up of face synthesis techniques, it is prominent in need to develop powerful face forgery detection methods due to security concerns. Some existing methods attempt to employ auxiliary frequency-aware information combined with CNN backbones to discover the forged clues. Due to the…

Cited by 110SourcePDFScholar
2023

Make Your Enemy Your Friend: Improving Image Rotation Angle Estimation with Harmonics

ICASSP 2023accepted

It is well known that rotation introduces periodic artifacts into the resulting image. By measuring such periodicities, the rotation angle θ can be estimated from the rotated image without the availability of the original unrotated image. However, existing methods suffer from harmonics, especially w…

Cited by 0SourceScholar
2020

Feature-metric Loss for Self-supervised Learning of Depth and Egomotion

ECCV 2020poster

Photometric loss is widely used for self-supervised depth and egomotion estimation. However, the loss landscapes induced by photometric differences are often problematic for optimization, caused by plateau landscapes for pixels in texture-less regions or multiple local minima for less discriminative…