activity
20242026
collaborators

11 papers

cs.CV2026

UI2Code^N: UI-to-Code Generation as Interactive Visual Optimization

Zhen Yang, Wenyi Hong, Mingde Xu +5

UI-to-code aims to translate UI screenshots into executable front-end code. Despite progress with vision-language models (VLMs), most existing methods formulate UI-to-code as a sin…

cs.CV2026

GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents

V Team, Wenyi Hong, Xiaotao Gu +94

We present GLM-5V-Turbo, a step toward native foundation models for multimodal agents. As foundation models are increasingly deployed in real environments, agentic capability depen…

cs.CV2026

MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models

Wenyi Hong, Yean Cheng, Zhuoyi Yang +6

In recent years, vision language models (VLMs) have made significant advancements in video understanding. However, a crucial capability - fine-grained motion comprehension - remain…

cs.CL2026

GLM-OCR Technical Report

Shuaiqi Duan, Yadong Xue, Weihan Wang +20

GLM-OCR is an efficient 0.9B-parameter compact multimodal model designed for real-world document understanding. It combines a 0.4B-parameter CogViT visual encoder with a 0.5B-param…

cs.CV2025

Glyph: Scaling Context Windows via Visual-Text Compression

Jiale Cheng, Yusen Liu, Xinyu Zhang +11

Large language models (LLMs) increasingly rely on long-context modeling for tasks such as document understanding, code analysis, and multi-step reasoning. However, scaling context…

cs.CV2025

LVBench: An Extreme Long Video Understanding Benchmark

Weihan Wang, Zehai He, Wenyi Hong +9

Recent progress in multimodal large language models has markedly enhanced the understanding of short videos (typically under one minute), and several evaluation datasets have emerg…