activity
20242026
most citedChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

180 citations · 243 across the 28 of their papers we have counts for

collaborators

29 papers

cs.CV2026

Video2Code: Generating Interactive Webpages from UI Videos via Action-Aware Revisit

Mingde Xu, Zhen Yang, Yan Wang +7

UI videos provide a natural input for generating interactive webpages, as they capture both webpage appearance and action-triggered state transitions. However, directly applying vi…

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

HoWToBench: Holistic Evaluation for LLM's Capability in Human-level Writing using Tree of Writing

Andrew Zhuoer Feng, Cunxiang Wang, Yu Luo +7

Evaluating the writing capabilities of large language models (LLMs) remains a significant challenge due to the multidimensional nature of writing skills and the limitations of exis…

cs.SE2026

Vision2Web: A Hierarchical Benchmark for Visual Website Development with Agent Verification

Zehai He, Wenyi Hong, Zhen Yang +4

Recent advances in large language models have improved the capabilities of coding agents, yet systematic evaluation of complex, end-to-end website development remains limited. To a…

cs.SD2025

GLM-TTS Technical Report

Jiayan Cui, Zhihan Yang, Naihan Li +10

This work proposes GLM-TTS, a production-level TTS system designed for efficiency, controllability, and high-fidelity speech generation. GLM-TTS follows a two-stage architecture, c…

cs.CV2025★ 1 cited

SCAIL: Towards Studio-Grade Character Animation via In-Context Learning of 3D-Consistent Pose Representations

Wenhao Yan, Sheng Ye, Zhuoyi Yang +6

Achieving controllable character animation that meets studio-grade standards remains challenging despite recent progress. Existing approaches can transfer motion from a driving vid…

cs.CV2025

Delving into Latent Spectral Biasing of Video VAEs for Superior Diffusability

Shizhan Liu, Xinran Deng, Zhuoyi Yang +3

Latent diffusion models pair VAEs with diffusion backbones, and the structure of VAE latents strongly influences the difficulty of diffusion training. However, existing video VAEs…

cs.SE2025

WebVIA: A Web-based Vision-Language Agentic Framework for Interactive and Verifiable UI-to-Code Generation

Mingde Xu, Zhen Yang, Wenyi Hong +6

User interface (UI) development requires translating design mockups into functional code, a process that remains repetitive and labor-intensive. While recent Vision-Language Models…

cs.CV2025

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.CL2025

InvestAlign: Overcoming Data Scarcity in Aligning Large Language Models with Investor Decision-Making Processes under Herd Behavior

Huisheng Wang, Zhuoshi Pan, Hangjing Zhang +3

Aligning Large Language Models (LLMs) with investor decision-making processes under herd behavior is a critical challenge in behavioral finance, which grapples with a fundamental l…

cs.CV2025★ 1 cited

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.AI2025

StepMathAgent: A Step-Wise Agent for Evaluating Mathematical Processes through Tree-of-Error

Shu-Xun Yang, Cunxiang Wang, Yidong Wang +3

Evaluating mathematical capabilities is critical for assessing the overall performance of large language models (LLMs). However, existing evaluation methods often focus solely on f…

cs.CV2025

VPO: Aligning Text-to-Video Generation Models with Prompt Optimization

Jiale Cheng, Ruiliang Lyu, Xiaotao Gu +9

Video generation models have achieved remarkable progress in text-to-video tasks. These models are typically trained on text-video pairs with highly detailed and carefully crafted…

cs.CV2025★ 1 cited

Concat-ID: Towards Universal Identity-Preserving Video Synthesis

Yong Zhong, Zhuoyi Yang, Jiayan Teng +2

We present Concat-ID, a unified framework for identity-preserving video generation. Concat-ID employs variational autoencoders to extract image features, which are then concatenate…

cs.CL2025★ 1 cited

LongSafety: Evaluating Long-Context Safety of Large Language Models

Yida Lu, Jiale Cheng, Zhexin Zhang +7

As Large Language Models (LLMs) continue to advance in understanding and generating long sequences, new safety concerns have been introduced through the long context. However, the…

cs.CL2025

HPSS: Heuristic Prompting Strategy Search for LLM Evaluators

Bosi Wen, Pei Ke, Yufei Sun +6

Since the adoption of large language models (LLMs) for text evaluation has become increasingly prevalent in the field of natural language processing (NLP), a series of existing wor…

cs.CV2025

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.CV2024

VisionReward: Fine-Grained Multi-Dimensional Human Preference Learning for Image and Video Generation

Jiazheng Xu, Yu Huang, Jiale Cheng +19

Visual generative models have achieved remarkable progress in synthesizing photorealistic images and videos, yet aligning their outputs with human preferences across critical dimen…

cs.CL2024

SPaR: Self-Play with Tree-Search Refinement to Improve Instruction-Following in Large Language Models

Jiale Cheng, Xiao Liu, Cunxiang Wang +7

Instruction-following is a fundamental capability of language models, requiring the model to recognize even the most subtle requirements in the instructions and accurately reflect…

cs.CV2024★ 7 cited

CogVLM2: Visual Language Models for Image and Video Understanding

Wenyi Hong, Weihan Wang, Ming Ding +22

Beginning with VisualGLM and CogVLM, we are continuously exploring VLMs in pursuit of enhanced vision-language fusion, efficient higher-resolution architecture, and broader modalit…

cs.AI2024★ 1 cited

VisualAgentBench: Towards Large Multimodal Models as Visual Foundation Agents

Xiao Liu, Tianjie Zhang, Yu Gu +27

Large Multimodal Models (LMMs) have ushered in a new era in artificial intelligence, merging capabilities in both language and vision to form highly capable Visual Foundation Agent…

cs.AI2024

LogicGame: Benchmarking Rule-Based Reasoning Abilities of Large Language Models

Jiayi Gui, Yiming Liu, Jiale Cheng +6

Large Language Models (LLMs) have demonstrated notable capabilities across various tasks, showcasing complex problem-solving abilities. Understanding and executing complex rules, a…

cs.CV2024★ 18 cited

CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Zhuoyi Yang, Jiayan Teng, Wendi Zheng +15

We present CogVideoX, a large-scale text-to-video generation model based on diffusion transformer, which can generate 10-second continuous videos aligned with text prompt, with a f…

cs.CL2024★ 180 cited

ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Team GLM, :, Aohan Zeng +56

We introduce ChatGLM, an evolving family of large language models that we have been developing over time. This report primarily focuses on the GLM-4 language series, which includes…