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

Chuanqi Tan works on LLM research and applications. His personal homepage says he earned a PhD from Tsinghua University in 2019 and is also a postdoctoral fellow at The University of Hong Kong.

Alibaba senior technology leader and researcher associated with Qwen. Public profiles list him with Alibaba Group, and official Alibaba Cloud coverage identifies him as a chief technology officer leading large-model work.

Distinguished software engineer at Google Brain focused on large-scale computer systems and machine learning applications.

Z.ai researcher focused on multimodal large language models and computer vision, with interests in large-model training and post-training.

Research scientist at Z.ai focused on multimodal understanding and generation, large language models, and reinforcement learning. He works on pre-training, post-training, and evaluation of multimodal models.

Research scientist at Z.ai focused on multimodal understanding and generation, reinforcement learning, AI agents, and end-to-end models. He received a bachelor's degree from Tsinghua University and a master's degree from UCLA.

Research scientist at Z.ai focused on multimodal understanding and generation, reinforcement learning, AI agents, and end-to-end models. He received a bachelor's degree from Tsinghua University and a master's degree from Peking University.

Research scientist at Z.ai with research interests in multimodal understanding and generation, large language models, and reinforcement learning. He received a bachelor's degree from the University of Science and Technology of China and a master's degree from Tsinghua University.

Researcher at Moonshot AI and co-author of the Kimi K2.5 report on visual agentic intelligence.

Co-author of GLM-4.1V-Thinking and GLM-4.5V, multimodal reasoning models trained with scalable reinforcement learning.

Profile still being enriched.

Profile still being enriched.