collaborators

6 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.LG2026

Norm Anchors Make Model Edits Last

Mingda Liu, Zhenghan Zhu, Ze'an Miao +1

Sequential Locate-and-Edit (L&E) model editing can fail abruptly after many edits. We identify and formalize this failure as a positive norm-feedback loop, in which solved value ve…

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.LG2026

GLM-5: from Vibe Coding to Agentic Engineering

GLM-5-Team, :, Aohan Zeng +184

We present GLM-5, a next-generation foundation model designed to transition the paradigm of vibe coding to agentic engineering. Building upon the agentic, reasoning, and coding (AR…

cs.CL2025

GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

5 Team, Aohan Zeng, Xin Lv +167

We present GLM-4.5, an open-source Mixture-of-Experts (MoE) large language model with 355B total parameters and 32B activated parameters, featuring a hybrid reasoning method that s…

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…