collaborators

5 papers

cs.CV2026

ProMSA:Progressive Multimodal Search Agents for Knowledge-Based Visual Question Answering

ZhengXian Wu, Hangrui Xu, Kai Shi +8

Knowledge-based Visual Question Answering (KB-VQA) requires models to combine image understanding with external knowledge. Most prior methods use a fixed retrieve-then-generate pip…

cs.CV2026

Stabilizing Unsupervised Self-Evolution of MLLMs via Continuous Softened Retracing reSampling

Yunyao Yu, Zhengxian Wu, Zhuohong Chen +6

In the unsupervised self-evolution of Multimodal Large Language Models, the quality of feedback signals during post-training is pivotal for stable and effective learning. However,…

cs.CV2026

When Models Judge Themselves: Unsupervised Self-Evolution for Multimodal Reasoning

Zhengxian Wu, Kai Shi, Chuanrui Zhang +10

Recent progress in multimodal large language models has led to strong performance on reasoning tasks, but these improvements largely rely on high-quality annotated data or teacher-…

cs.CV2026

Language-Guided and Motion-Aware Gait Representation for Generalizable Recognition

Zhengxian Wu, Chuanrui Zhang, Shenao Jiang +6

Gait recognition is emerging as a promising technology and an innovative field within computer vision, with a wide range of applications in remote human identification. However, ex…

cs.AI2025

EcphoryRAG: Re-Imagining Knowledge-Graph RAG via Human Associative Memory

Zirui Liao

Cognitive neuroscience research indicates that humans leverage cues to activate entity-centered memory traces (engrams) for complex, multi-hop recollection. Inspired by this mechan…