Research lab

Z.ai / GLM

The GLM family of open language, reasoning, coding, agentic, and multimodal models.

Papers: 5
Citations: 732
Official code: 4

5 papers from Z.ai / GLM

Research paper

SCAIL-2: Unifying Controlled Character Animation with End-to-end In-Context Conditioning

SCAIL-2 is an end-to-end framework for controlled character animation that bypasses intermediate representations like pose skeletons or masked backgrounds, which cause information loss. It directly concatenates driving videos to the sequence, allowing the model to capture all visual information. To address the lack of end-to-end data, the authors unify…

Wenhao Yan, Fengjia Guo, Zhuoyi Yang, Jie Tang

Published: Jun 2026
Citations: 1
Code: 1.1K stars

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arXiv.org

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

GLM-5V-Turbo is a native multimodal foundation model for agentic tasks, integrating perception, reasoning, planning, and execution. It introduces CogViT, a vision encoder trained via distillation and contrastive learning, and Multimodal Multi-Token Prediction (MMTP) using a shared <|image|> token for efficiency. The model undergoes joint RL over 30+ task…

GLM-V Team, :, Wenyi Hong, Xiaotao Gu, et al.

Published: Apr 2026
Citations: 11
Code: Not linked

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arXiv.org

IndexCache: Accelerating Sparse Attention via Cross-Layer Index Reuse

IndexCache is a method to accelerate sparse attention in large language models by exploiting cross-layer redundancy in token selection. DeepSeek Sparse Attention (DSA) uses a lightning indexer at each layer to select top-k tokens, but this indexer still has O(L^2) complexity. IndexCache partitions layers into a small set of Full (F) layers that run their…

Yushi Bai, Qian Dong, Ting Jiang, Xin Lv, et al.

Published: Mar 2026
Citations: 16
Code: 131 stars

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arXiv.org

GLM-5: from Vibe Coding to Agentic Engineering

GLM-5, developed by Zhipu AI and Tsinghua University, is a next-generation foundation model that shifts from vibe coding to agentic engineering. It builds on the ARC (agentic, reasoning, coding) capabilities of its predecessor, GLM-4.7, and introduces DeepSeek Sparse Attention (DSA) to reduce training and inference costs while maintaining long-context…

GLM-5-Team, :, Aohan Zeng, Xin Lv, et al.

Published: Feb 2026
Citations: 295
Code: 6.9K stars

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arXiv.org

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

GLM-4.5 is an open-source Mixture-of-Experts (MoE) large language model with 355B total and 32B activated parameters, developed by Zhipu AI and Tsinghua University. It features a hybrid reasoning method supporting both thinking and direct response modes. Trained on 23T tokens with multi-stage pre-training and mid-training (including repo-level code,…

GLM-4. 5 Team, :, Aohan Zeng, Xin Lv, et al.

Published: Aug 2025
Citations: 409
Code: 4.4K stars

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