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Hongyang Zhang

4 papers hereh-index 375 citations12 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author1

Across the 2 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.CY1
  • eess.SP1
same name
  • Hongyang Zhang — 5 papers, h 7
  • Hongyang Zhang — 3 papers, h 2
  • Hongyang Zhang — 3 papers, h 2
  • Hongyang Zhang — 3 papers, h 31
  • Hongyang Zhang — 2 papers, h 3
  • Hongyang Zhang — 2 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.CY2026

On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective

Yue Huang, Chujie Gao, Siyuan Wu +63

Generative Foundation Models (GenFMs) have emerged as transformative tools. However, their widespread adoption raises critical concerns regarding trustworthiness across dimensions.…

cs.CV2026

MedAD-R1: Eliciting Consistent Reasoning in Interpretible Medical Anomaly Detection via Consistency-Reinforced Policy Optimization

Haitao Zhang, Yingying Wang, Jiaxiang Wang +5

Medical Anomaly Detection (MedAD) presents a significant opportunity to enhance diagnostic accuracy using Large Multimodal Models (LMMs) to interpret and answer questions based on…

eess.SP2026

Position-Aware Self-supervised Representation Learning for Cross-mode Radar Signal Recognition

Hongyang Zhang, Haitao Zhang, Yinhao Liu +3

Radar signal recognition in open electromagnetic environments is challenging due to diverse operating modes and unseen radar types. Existing methods often overlook position relatio…

cs.CV2025

Unity in Diversity: Multi-expert Knowledge Confrontation and Collaboration for Generalizable Vehicle Re-identification

Zhenyu Kuang, Hongyang Zhang, Mang Ye +5

Generalizable vehicle re-identification (ReID) seeks to develop models that can adapt to unknown target domains without the need for additional fine-tuning or retraining. Previous…

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