activity
20192026
most cited3D-Rotation-Equivariant Quaternion Neural Networks

13 citations · 19 across the 10 of their papers we have counts for

collaborators

11 papers

cs.AI2026

Authorization Closure Graph: Minimal Repair for LLM Agents with Evolving User Instructions

Qingzhuo Wang, CaiYi Wang, Jinglu Meng +4

Tool-using large language model (LLM) agents increasingly perform state-changing actions that require user authorization. Yet existing approaches do not provide a principled mechan…

cs.LG2026

Evaluating and Explaining Prompt Sensitivity of LLMs Using Interactions

Ruiyang Qin, Qingzhuo Wang, Tian Wang +2

The remarkable capabilities of large language models (LLMs) are often undermined by their instability. Even subtle and semantically irrelevant changes in prompts can cause dramatic…

cs.LG2026

A Unified Approach to Interpreting Knowledge Distillation for Large Language Models via Interactions

Qingzhuo Wang, Ruiyang Qin, Zhenxin Qin +2

Despite the success of knowledge distillation (KD) in Large Language Models (LLMs), the underlying mechanism behind its efficacy remains unclear. In this paper, we propose a unifie…

cs.CV2026

Mitigating Action-Relation Hallucinations in LVLMs via Relation-aware Visual Enhancement

Zhenxin Qin, Qiang Li, Qingzhuo Wang +3

Large Vision-Language Models (LVLMs) have achieved remarkable performance on diverse vision-language tasks. However, LVLMs still suffer from hallucinations, generating text that co…

cs.LG2026

Multilingual Safety Alignment via Self-Distillation

Ruiyang Qin, Qingzhuo Wang, Dongrui Liu +3

Large language models (LLMs) exhibit severe multilingual safety misalignment: they possess strong safeguards in high-resource languages but remain highly vulnerable to jailbreak at…

cs.IR2026

TME-PSR: Time-aware, Multi-interest, and Explanation Personalization for Sequential Recommendation

Qingzhuo Wang, Leilei Wen, Juntao Chen +4

In this paper, we propose a sequential recommendation model that integrates Time-aware personalization, Multi-interest personalization, and Explanation personalization for Personal…

cs.CV2025

FOLK: Fast Open-Vocabulary 3D Instance Segmentation via Label-guided Knowledge Distillation

Hongrui Wu, Zhicheng Gao, Jin Cao +3

Open-vocabulary 3D instance segmentation seeks to segment and classify instances beyond the annotated label space. Existing methods typically map 3D instances to 2D RGB-D images, a…

cs.CV2025

M3-AGIQA: Multimodal, Multi-Round, Multi-Aspect AI-Generated Image Quality Assessment

Chuan Cui, Kejiang Chen, Zhihua Wei +3

The rapid advancement of AI-generated image (AIGI) models presents new challenges for evaluating image quality, particularly across three aspects: perceptual quality, prompt corres…

cs.CV2021★ 6 cited

Interpretable Compositional Convolutional Neural Networks

Wen Shen, Zhihua Wei, Shikun Huang +4

The reasonable definition of semantic interpretability presents the core challenge in explainable AI. This paper proposes a method to modify a traditional convolutional neural netw…

cs.CV2019

Verifiability and Predictability: Interpreting Utilities of Network Architectures for Point Cloud Processing

Wen Shen, Zhihua Wei, Shikun Huang +4

In this paper, we diagnose deep neural networks for 3D point cloud processing to explore utilities of different intermediate-layer network architectures. We propose a number of hyp…

cs.CV2019★ 13 cited

3D-Rotation-Equivariant Quaternion Neural Networks

Wen Shen, Binbin Zhang, Shikun Huang +2

This paper proposes a set of rules to revise various neural networks for 3D point cloud processing to rotation-equivariant quaternion neural networks (REQNNs). We find that when a…