Lingyu Zhou

Lingyu Zhou

PhD Candidate

Sichuan University

Research Interests

Hallucination Mitigation in Multimodal LLMs
Visual Evidence Grounding
World Model Construction
Medical Image Analysis

About

I am a PhD candidate at the College of Computer Science, Sichuan University, advised by Prof. Zhang Yi (Foreign Member of the Russian Academy of Engineering, IEEE Fellow). I am a member of the Machine Intelligence Lab.

Prior to this, I obtained my B.Eng. degree in Computer Science and Technology from Sichuan University in 2022.

My research centers on mitigating hallucinations in Multimodal Large Language Models (MLLMs) within real-world clinical scenarios. Specifically, I investigate how to effectively embed visual evidence grounding with rich semantic context into LLMs, enabling faithful and interpretable cross-modal reasoning. My work spans radiology report generation, medical image segmentation, and computer-aided diagnosis, aiming to build trustworthy AI systems that bridge the gap between multimodal intelligence and clinical practice.

Selected Publications

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Glance Before You Tell: Anomaly-Guided 3D Radiology Report Generation with Heat-Conduction Slice Encoders

Lingyu Zhou, Dingwen Pi, Zhang Yi, Jun Wu, Xiuyuan Xu

Proceedings of the Conference on Neural Information Processing Systems (NeurIPS) 2026 · CCF-A · Poster

Proposed HeatRAD, a glance-before-tell framework that routes anomaly-guided slice evidence into an organ-ordered visual prefix for 3D radiology report generation.

Mitigating Entity Hallucinations in 3D Radiology Report Generation via Dual-Stream Alignment

Lingyu Zhou†, Yue Yu†, Zhang Yi, Xiuyuan Xu

Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2026 · CCF-A · Poster

Proposed DEAR framework to mitigate entity hallucinations in 3D radiology report generation through dual-stream alignment.

ForeMatch: Rethinking Foreground Consistency for Efficient Semi-Supervised 3D Medical Image Segmentation

Lingyu Zhou, Zhengyang Xu, Zhang Yi, Deng Xiong, Xiuyuan Xu

Proceedings of the ACM International Conference on Multimedia (ACM MM) 2026 · CCF-A · Poster

Proposed ForeMatch for efficient semi-supervised 3D medical image segmentation via foreground consistency.

Navigate Before You Generate: Volume Evidence Grounding for 3D Radiology Reports

Lingyu Zhou, Dingwen Pi, Jun Wu, Zhang Yi, Xiuyuan Xu

IEEE Transactions on Image Processing (IEEE TIP) 2026 · CCF-A · IF=13.7 · Under Review

Proposed Vol-Nav, a volume evidence grounding paradigm for 3D radiology report generation.

Efficient and Gender-Adaptive Graph Vision Mamba for Pediatric Bone Age Assessment

Lingyu Zhou, Zhang Yi, Kai Zhou, Xiuyuan Xu

Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2024 · CCF-B · Poster

Proposed GGVMamba, a gender-adaptive Graph Vision Mamba framework for pediatric bone age assessment.

News

2026-09
One paper accepted as Poster at NeurIPS 2026! 🎉
2026-07
One paper accepted as Poster at ACM MM 2026! 🎉
2026-06
Led team to win First Prize at Sichuan Province "Challenge Cup" Competition! 🏆
2026-05
Two papers submitted to NeurIPS 2026.
2026-05
One paper narrowly missed acceptance at ICML 2026.
2026-03
One paper submitted to ACM MM 2026.
2026-01
One paper submitted to ICML 2026.
2025-11
One paper accepted as Poster at AAAI 2026! 🎉