activity
20232026
most citedReinforced UI Instruction Grounding: Towards a Generic UI Task Automation API

2 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

StableI2I: Spotting Unintended Changes in Image-to-Image Transition

Jiayang Li, Shuo Cao, Xiaohui Li +6

In most real-world image-to-image (I2I) scenarios, existing evaluations primarily focus on instruction following and the perceptual quality or aesthetics of the generated images. H…

cs.CV2025

WeGen: A Unified Model for Interactive Multimodal Generation as We Chat

Zhipeng Huang, Shaobin Zhuang, Canmiao Fu +7

Existing multimodal generative models fall short as qualified design copilots, as they often struggle to generate imaginative outputs once instructions are less detailed or lack th…

cs.LG2024

A General Theory for Compositional Generalization

Jingwen Fu, Zhizheng Zhang, Yan Lu +1

Compositional Generalization (CG) embodies the ability to comprehend novel combinations of familiar concepts, representing a significant cognitive leap in human intellectual advanc…

cs.CV2024★ 2 cited

VisualCritic: Making LMMs Perceive Visual Quality Like Humans

Zhipeng Huang, Zhizheng Zhang, Yiting Lu +3

At present, large multimodal models (LMMs) have exhibited impressive generalization capabilities in understanding and generating visual signals. However, they currently still lack…

cs.CV2024

RelationVLM: Making Large Vision-Language Models Understand Visual Relations

Zhipeng Huang, Zhizheng Zhang, Zheng-Jun Zha +2

The development of Large Vision-Language Models (LVLMs) is striving to catch up with the success of Large Language Models (LLMs), yet it faces more challenges to be resolved. Very…

cs.CV2023★ 2 cited

Reinforced UI Instruction Grounding: Towards a Generic UI Task Automation API

Zhizheng Zhang, Wenxuan Xie, Xiaoyi Zhang +1

Recent popularity of Large Language Models (LLMs) has opened countless possibilities in automating numerous AI tasks by connecting LLMs to various domain-specific models or APIs, w…