activity
20202026
most citedPathVQA: 30000+ Questions for Medical Visual Question Answering

85 citations · 86 across the 6 of their papers we have counts for

collaborators

6 papers

cs.MM2026

Mind the Couch! Eliciting MLLM Reasoning in Interior Design via Weak-to-Strong Task Vector Injection

Yuxuan Yang, Jingyao Wang, Luntian Mou

Multimodal Large Language Models (MLLMs) have demonstrated great performance, yet they often suffer from severe modality misalignment when confronted with densely constrained space…

cs.CV2024

Image-based Freeform Handwriting Authentication with Energy-oriented Self-Supervised Learning

Jingyao Wang, Luntian Mou, Changwen Zheng +1

Freeform handwriting authentication verifies a person's identity from their writing style and habits in messy handwriting data. This technique has gained widespread attention in re…

cs.CV2023

CSSL-RHA: Contrastive Self-Supervised Learning for Robust Handwriting Authentication

Jingyao Wang, Luntian Mou, Changwen Zheng +1

Handwriting authentication is a valuable tool used in various fields, such as fraud prevention and cultural heritage protection. However, it remains a challenging task due to the c…

cs.CV2020

Pathological Visual Question Answering

Xuehai He, Zhuo Cai, Wenlan Wei +4

Is it possible to develop an "AI Pathologist" to pass the board-certified examination of the American Board of Pathology (ABP)? To build such a system, three challenges need to be…

cs.CV2020★ 1 cited

TreeGAN: Incorporating Class Hierarchy into Image Generation

Ruisi Zhang, Luntian Mou, Pengtao Xie

Conditional image generation (CIG) is a widely studied problem in computer vision and machine learning. Given a class, CIG takes the name of this class as input and generates a set…

cs.CL2020★ 85 cited

PathVQA: 30000+ Questions for Medical Visual Question Answering

Xuehai He, Yichen Zhang, Luntian Mou +2

Is it possible to develop an "AI Pathologist" to pass the board-certified examination of the American Board of Pathology? To achieve this goal, the first step is to create a visual…