activity
20242026
collaborators

7 papers

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.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.CV2026

GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning

V Team, Wenyi Hong, Wenmeng Yu +90

We present GLM-4.1V-Thinking, GLM-4.5V, and GLM-4.6V, a family of vision-language models (VLMs) designed to advance general-purpose multimodal understanding and reasoning. In this…

cs.HC2025

PlotGen-Bench: Evaluating VLMs on Generating Visualization Code from Diverse Plots across Multiple Libraries

Yi Zhao, Zhen Yang, Shuaiqi Duan +4

Recent advances in vision-language models (VLMs) have expanded their multimodal code generation capabilities, yet their ability to generate executable visualization code from plots…

cs.CL2025

AlignMMBench: Evaluating Chinese Multimodal Alignment in Large Vision-Language Models

Yuhang Wu, Wenmeng Yu, Yean Cheng +5

Evaluating the alignment capabilities of large Vision-Language Models (VLMs) is essential for determining their effectiveness as helpful assistants. However, existing benchmarks pr…

cs.CV2024

CogAgent: A Visual Language Model for GUI Agents

Wenyi Hong, Weihan Wang, Qingsong Lv +11

People are spending an enormous amount of time on digital devices through graphical user interfaces (GUIs), e.g., computer or smartphone screens. Large language models (LLMs) such…