Atlas / Reports / Detail
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
Reasoning Large Language Models report from MiniMax with 20 connected researchers in the LLMpeople atlas.
Connected researchers
Researcher
3 reports
Jifeng Dai
DeepSeek / MiniMax
Researcher focused on computer vision, multimodal learning, and generative AI. His public homepage says he is currently with Stepfun, after serving as a principal scientist at SenseTime Research and a researcher at Microsoft Research Asia, and that he earned a PhD in computer science from Tsinghua University.
Researcher
2 reports
Chunlin Li
MiniMax
Chunlin Li is a research scientist at MiniMax.
Researcher
1 reports
Yuxiang Zheng
MiniMax
Research scientist at MiniMax focused on reasoning, efficient large language models, reinforcement learning, and multimodal understanding and generation.
Researcher
17 reports
Jingren Zhou
Moonshot AI / Alibaba Qwen
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.
Researcher
5 reports
Binyuan Hui
DeepSeek / Alibaba Qwen
AI researcher whose public work includes large language models, vision-language models, and multimodal systems. His public profile notes prior work as a senior algorithm expert at Alibaba and co-authorship of Qwen technical reports.
Researcher
3 reports
Yu Liu
ByteDance Seed / MiniMax
Yu Liu is publicly listed as a co-author on the 2025 Seed1.5-VL, MiniMax-01, and MiniMax-M1 technical reports.
Researcher
5 reports
Jie Zhou
DeepSeek / Moonshot AI
Jie Zhou is a Moonshot AI contributor and co-author of Kimi k1.5: Scaling Reinforcement Learning with LLMs.
Researcher
2 reports
Zeyu Wang
ByteDance Seed / MiniMax
Public sources list Zeyu Wang as an author of ByteDance Seed's Seed1.5-VL Technical Report and the Seed publication "Emerging Properties in Unified Multimodal Pretraining" (BAGEL), and as a coauthor of the MiniMax-M1 technical report.
Researcher
3 reports
Jinyuan Jia
MiniMax
Researcher working on speech and multimodal language models, including MiniMax-Speech and related speech understanding work.
Researcher
3 reports
Ming Ding
MiniMax
Lead of foundation models at MiniMax working on large language models, multimodal pretraining, and efficient training systems. He completed a PhD in computer science at Tsinghua University.
Researcher
3 reports
Qingyang Ge
MiniMax
Research scientist at MiniMax AI Research interested in large language models, machine learning, and computer vision. He earned a PhD from Shanghai Jiao Tong University and previously worked at Alibaba DAMO Academy on vision-language reasoning and video understanding.
Researcher
3 reports
Wenchao Zhou
MiniMax
Research scientist at MiniMax AI Research focused on large language models, machine learning, and recommendation systems. He received a PhD from Shanghai Jiao Tong University and previously worked at Alibaba DAMO Academy on machine learning and distributed databases.
Researcher
3 reports
Yusheng Zhao
MiniMax
Research scientist at MiniMax AI Research focused on reinforcement learning, reasoning, multimodal learning, large language models, and large-scale distributed systems. He received a PhD in machine learning from Carnegie Mellon University.
Researcher
2 reports
Shang Yang
DeepSeek / MiniMax
Researcher focused on reinforcement learning, large language model reasoning, and multimodal foundation models; coauthor of Janus-Pro and MiniMax-M1.
Researcher
2 reports
Wenbo Bi
MiniMax
Research scientist at MiniMax AI Research whose interests include large language models, machine learning, and code intelligence. He earned a PhD from Nanyang Technological University and previously worked on code intelligence, search, and recommender systems at Alibaba DAMO Academy.
Researcher
1 reports
Jiahan Xu
MiniMax
Researcher working on efficient large language models and reasoning systems, including MiniMax-M1.
Researcher
1 reports
Weiran Huang
MiniMax
Researcher focused on reinforcement learning and multimodal foundation models; arXiv author results include the MiniMax-M1 paper.
Researcher
1 reports
Xianxin Lin
MiniMax
Research scientist at MiniMax AI Research focused on large language models, reinforcement learning, and AI for science. He received a PhD from Peking University and has published at NeurIPS, ICML, ICLR, AAAI, and IJCAI.
Researcher
1 reports
Yefeng Zheng
MiniMax
Research scientist at MiniMax AI Research focused on AI for science, large language models, and deep generative models. He received a PhD from Stanford University and a bachelor's degree in computer science from Rice University.
Researcher
1 reports
Zhihao Wu
MiniMax
Research scientist at MiniMax AI Research focused on multimodal large language models, AI agents, and reasoning. He previously worked on multimodal understanding and generation and holds a master's degree from Tsinghua University.