Haozhe Luo

Orcid: 0000-0001-8821-3737

According to our database1, Haozhe Luo authored at least 14 papers between 2022 and 2025.

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Bibliography

2025
XBench: A Comprehensive Benchmark for Visual-Language Explanations in Chest Radiography.
CoRR, October, 2025

RadDiagSeg-M: A Vision Language Model for Joint Diagnosis and Multi-Target Segmentation in Radiology.
CoRR, October, 2025

Hybrid Explanation-Guided Learning for Transformer-Based Chest X-Ray Diagnosis.
CoRR, October, 2025

Beyond Survival: Evaluating LLMs in Social Deduction Games with Human-Aligned Strategies.
CoRR, October, 2025

ACE: Anatomically Consistent Embeddings in Composition and Decomposition.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

[inline-graphic not available: see fulltext] Lamps: Learning Anatomy from Multiple Perspectives via Self-supervision in Chest Radiographs.
Proceedings of the Foundation Models for General Medical AI - Third International Workshop, 2025

On the Interplay of Human-AI Alignment, Fairness, and Performance Trade-Offs in Medical Imaging.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025

2024
Orchestrating explainable artificial intelligence for multimodal and longitudinal data in medical imaging.
npj Digit. Medicine, 2024

DWARF: Disease-weighted network for attention map refinement.
CoRR, 2024

DeViDe: Faceted medical knowledge for improved medical vision-language pre-training.
CoRR, 2024

DWARF: Disease-Weighted Network for Attention Map Refinement.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 Workshops, 2024

2023
Learning Anatomically Consistent Embedding for Chest Radiography.
Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022
A Cascaded Convolutional Neural Network for Two-Phase Flow PIV of an Object Entering Water.
IEEE Trans. Instrum. Meas., 2022

Hybrid Ladder Transformers with Efficient Parallel-Cross Attention for Medical Image Segmentation.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022


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