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We introduce MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Empirical evaluation of gated recurrent neural networks on sequence modeling
Junyoung Chung and Ç · 2014
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Parallelizing linear recurrent neural nets over sequence length
Eric Martin and Chris Cundy · 2018
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
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Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan · 2020
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Hippo: Recurrent memory with optimal polynomial projections
Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, and Christopher Ré · 2020
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Transformers are RNNs: Fast autoregressive transformers with linear attention
Angelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas, and François Fleuret · 2020
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Big Bird: Transformers for longer sequences
Manzil Zaheer, Guru Guruganesh, Kumar Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, et al · 2020
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Rethinking attention with Performers
Krzysztof Marcin Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Quincy Davis, Afroz Mohiuddin, Lukasz Kaiser, David Benjamin Belanger, Lucy J Colwell, and Adrian Weller · 2021
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Measuring mathematical problem solving with the math dataset
Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt · 2021
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Random feature attention
Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah Smith, and Lingpeng Kong · 2021
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cosformer: Rethinking softmax in attention
Zhen Qin, Weixuan Sun, Hui Deng, Dongxu Li, Yunshen Wei, Baohong Lv, Junjie Yan, Lingpeng Kong, and Yiran Zhong · 2021
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Efficiently modeling long sequences with structured state spaces
Albert Gu, Karan Goel, and Christopher Ré · 2022
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Diagonal state spaces are as effective as structured state spaces
Ankit Gupta, Albert Gu, and Jonathan Berant · 2022
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The devil in linear transformer
Zhen Qin, Xiaodong Han, Weixuan Sun, Dongxu Li, Lingpeng Kong, Nick Barnes, and Yiran Zhong · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
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How to train your HIPPO: State space models with generalized orthogonal basis projections
Albert Gu, Isys Johnson, Aman Timalsina, Atri Rudra, and Christopher Re · 2023
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A theory on adam instability in large-scale machine learning
Igor Molybog, Peter Albert, Moya Chen, Zachary DeVito, David Esiobu, Naman Goyal, Punit Singh Koura, Sharan Narang, Andrew Poulton, Ruan Silva, Binh Tang, Diana Liskovich, Puxin Xu, Yuchen Zhang, Melanie Kambadur, Stephen Roller, and Susan Zhang · 2023
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Rwkv: Reinventing rnns for the transformer era
Bo Peng, Eric Alcaide, Quentin Gregory Anthony, Alon Albalak, Samuel Arcadinho, Stella Biderman, Huanqi Cao, Xin Cheng, Michael Nguyen Chung, Leon Derczynski, et al · 2023
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Hierarchically gated recurrent neural network for sequence modeling
Zhen Qin, Songlin Yang, and Yiran Zhong · 2023
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Retentive network: A successor to transformer for large language models
Yutao Sun, Li Dong, Shaohan Huang, Shuming Ma, Yuqing Xia, Jilong Xue, Jianyong Wang, and Furu Wei · 2023
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Simple linear attention language models balance the recall-throughput tradeoff
Simran Arora, Sabri Eyuboglu, Michael Zhang, Aman Timalsina, Silas Alberti, Dylan Zinsley, James Zou, Atri Rudra, and Ré · 2024
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Yushi Bai, Shangqing Tu, Jiajie Zhang, Hao Peng, Xiaozhi Wang, Xin Lv, Shulin Cao, Jiazheng Xu, Lei Hou, Yuxiao Dong, Jie Tang, and Juanzi Li · 2024
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Titans: Learning to memorize at test time
Ali Behrouz, Peilin Zhong, and Vahab Mirrokni · 2024
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Metala: Unified optimal linear approximation to softmax attention map
Yuhong Chou, Man Yao, Kexin Wang, Yuqi Pan, Rui-Jie Zhu, Jibin Wu, Yiran Zhong, Yu Qiao, Bo Xu, and Guoqi Li · 2024
Cited alongside, same era.
Tri Dao and Albert Gu · 2024
Cited alongside, same era.
Paolo Glorioso, Quentin Anthony, Yury Tokpanov, James Whittington, Jonathan Pilault, Adam Ibrahim, and Beren Millidge · 2024
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Mamba: Linear-time sequence modeling with selective state spaces
Albert Gu and Tri Dao · 2024
Mom: Linear sequence modeling with mixture-of-memories
Jusen Du, Weigao Sun, Disen Lan, Jiaxi Hu, and Yu Cheng · 2025
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Gemini pro
Google DeepMind · 2025
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Open-reasoner-zero: An open source approach to scaling up reinforcement learning on the base model
Jingcheng Hu, Yinmin Zhang, Qi Han, Daxin Jiang, Xiangyu Zhang, and Heung-Yeung Shum · 2025
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Livecodebench: Holistic and contamination free evaluation of large language models for code
Naman Jain, King Han, Alex Gu, Wen-Ding Li, Fanjia Yan, Tianjun Zhang, Sida Wang, Armando Solar-Lezama, Koushik Sen, and Ion Stoica · 2025
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Kimi k1. 5: Scaling reinforcement learning with llms
Kimi Team · 2025
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Cited alongside, same era.
Rodimus*: Breaking the accuracy-efficiency trade-off with efficient attentions
Zhihao He, Hang Yu, Zi Gong, Shizhan Liu, Jianguo Li, and Weiyao Lin · 2024
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Jamba Team · 2024
Cited alongside, same era.
SWE-bench: Can language models resolve real-world github issues?
Carlos E. Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik Narasimhan · 2024
Cited alongside, same era.
Fullstack bench: Evaluating llms as full stack coders
Siyao Liu, He Zhu, Jerry Liu, Shulin Xin, Aoyan Li, Rui Long, Li Chen, Jack Yang, Jinxiang Xia, Z. Y. Peng, Shukai Liu, Zhaoxiang Zhang, Ge Zhang, Wenhao Huang, Kai Shen, and Liang Xiang · 2024
Cited alongside, same era.
Introducing openai o1
OpenAI · 2024
Cited alongside, same era.
Gpqa: A graduate-level google-proof q&a benchmark
David Rein, Betty Li Hou, Asa Cooper Stickland, Jackson Petty, Richard Yuanzhe Pang, Julien Dirani, Julian Michael, and Samuel R Bowman · 2024
Cited alongside, same era.
Samba: Simple hybrid state space models for efficient unlimited context language modeling
Liliang Ren, Yang Liu, Yadong Lu, Yelong Shen, Chen Liang, and Weizhu Chen · 2024
Cited alongside, same era.
Zebralogic: On the scaling limits of llms for logical reasoning
Bill Yuchen Lin, Ronan Le Bras, Kyle Richardson, Ashish Sabharwal, Radha Poovendran, Peter Clark, and Yejin Choi · 2025
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Moba: Mixture of block attention for long-context llms
Enzhe Lu, Zhejun Jiang, Jingyuan Liu, Yulun Du, Tao Jiang, Chao Hong, Shaowei Liu, Weiran He, Enming Yuan, Yuzhi Wang, et al · 2025
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Minimax-01: Scaling foundation models with lightning attention
MiniMax, Aonian Li, Bangwei Gong, Bo Yang, Boji Shan, Chang Liu, Cheng Zhu, Chunhao Zhang, Congchao Guo, Da Chen, Dong Li, et al · 2025
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Openai mrcr dataset
OpenAI · 2025
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Introducing deep research, 2025
OpenAI · 2025
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Long Phan, Alice Gatti, Ziwen Han, Nathaniel Li, Josephina Hu, Hugh Zhang, Chen Bo Calvin Zhang, Mohamed Shaaban, John Ling, Sean Shi, et al · 2025
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Qwen, :, An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, Huan Lin, Jian Yang, Jianhong Tu, Jianwei Zhang, Jianxin Yang, Jiaxi Yang, Jingren Zhou, Junyang Lin, Kai Dang, Keming Lu, Keqin Bao, Kexin Yang, Le Yu, Mei Li, Mingfeng Xue, Pei Zhang, Qin Zhu, Rui Men, Runji Lin, Tianhao Li, Tianyi Tang, Tingyu Xia, Xingzhang Ren, Xuancheng Ren, Yang Fan, Yang Su, Yichang Zhang, Yu Wan, Yuqiong Liu, Zeyu Cui, Zhenru Zhang, and Zihan Qiu · 2025
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Seed1. 5-thinking: Advancing superb reasoning models with reinforcement learning
ByteDance Seed, Jiaze Chen, Tiantian Fan, Xin Liu, Lingjun Liu, Zhiqi Lin, Mingxuan Wang, Chengyi Wang, Xiangpeng Wei, Wenyuan Xu, et al · 2025
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Deltaproduct: Improving state-tracking in linear rnns via householder products
Julien Siems, Timur Carstensen, Arber Zela, Frank Hutter, Massimiliano Pontil, and Riccardo Grazzi · 2025
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Ved Sirdeshmukh, Kaustubh Deshpande, Johannes Mols, Lifeng Jin, Ed-Yeremai Cardona, Dean Lee, Jeremy Kritz, Willow Primack, Summer Yue, and Chen Xing · 2025
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Linear-moe: Linear sequence modeling meets mixture-of-experts
Weigao Sun, Disen Lan, Tong Zhu, Xiaoye Qu, and Yu Cheng · 2025
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Hunyuan-t1: Reasoning efficiency redefined
Tencent AI Lab · 2025
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Mesanet: Sequence modeling by locally optimal test-time training
Johannes von Oswald, Nino Scherrer, Seijin Kobayashi, Luca Versari, Songlin Yang, Maximilian Schlegel, Kaitlin Maile, Yanick Schimpf, Oliver Sieberling, Alexander Meulemans, et al · 2025
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Shenzhi Wang, Le Yu, Chang Gao, Chujie Zheng, Shixuan Liu, Rui Lu, Kai Dang, Xionghui Chen, Jianxin Yang, Zhenru Zhang, Yuqiong Liu, An Yang, Andrew Zhao, Yang Yue, Shiji Song, Bowen Yu, Gao Huang, and Junyang Lin · 2025
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Theagentcompany: Benchmarking llm agents on consequential real world tasks
Frank F. Xu, Yufan Song, Boxuan Li, Yuxuan Tang, Kritanjali Jain, Mengxue Bao, Zora Z. Wang, Xuhui Zhou, Zhitong Guo, Murong Cao, Mingyang Yang, Hao Yang Lu, Amaad Martin, Zhe Su, Leander Maben, Raj Mehta, Wayne Chi, Lawrence Jang, Yiqing Xie, Shuyan Zhou, and Graham Neubig · 2025
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τ \tau -bench: A benchmark for tool-agent-user interaction in real-world domains
Shunyu Yao, Noah Shinn, Pedram Razavi, and Karthik R Narasimhan · 2025
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Dapo: An open-source llm reinforcement learning system at scale
Qiying Yu, Zheng Zhang, Ruofei Zhu, Yufeng Yuan, Xiaochen Zuo, Yu Yue, Weinan Dai, Tiantian Fan, Gaohong Liu, Lingjun Liu, Xin Liu, Haibin Lin, Zhiqi Lin, Bole Ma, Guangming Sheng, Yuxuan Tong, Chi Zhang, Mofan Zhang, Wang Zhang, Hang Zhu, Jinhua Zhu, Jiaze Chen, Jiangjie Chen, Chengyi Wang, Hongli Yu, Yuxuan Song, Xiangpeng Wei, Hao Zhou, Jingjing Liu, Wei-Ying Ma, Ya-Qin Zhang, Lin Yan, Mu Qiao, Yonghui Wu, and Mingxuan Wang · 2025
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Native sparse attention: Hardware-aligned and natively trainable sparse attention
Jingyang Yuan, Huazuo Gao, Damai Dai, Junyu Luo, Liang Zhao, Zhengyan Zhang, Zhenda Xie, YX Wei, Lean Wang, Zhiping Xiao, et al · 2025
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Simplerl-zoo: Investigating and taming zero reinforcement learning for open base models in the wild
Weihao Zeng, Yuzhen Huang, Qian Liu, Wei Liu, Keqing He, Zejun Ma, and Junxian He · 2025
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