Zhengjian Kang — accepted AI-conference papers

2026

PaQ-DETR: Learning Pattern and Quality-Aware Dynamic Queries for Object Detection

Zhengjian Kang, Jun Zhuang, Kangtong Mo, Qi Chen, Rui Liu, Ye Zhang

CVPR 2026

Detection Transformer (DETR) has redefined object detection by casting it as a set prediction task within an end-to-end framework. Despite its elegance, DETR and its variants still rely on fixed learnable queries and suffer from severe query utilization imbalance, which limits adaptability and leave

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2025

Exploring the Vulnerability of the Content Moderation Guardrail in Large Language Models via Intent Manipulation

Jun Zhuang, Haibo Jin, Ye Zhang, Zhengjian Kang, Wenbin Zhang, Gaby G. Dagher +1

EMNLP 2025

Intent detection, a core component of natural language understanding, has considerably evolved as a crucial mechanism in safeguarding large language models (LLMs). While prior work has applied intent detection to enhance LLMs’ moderation guardrails, showing a significant success against content-leve

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