Aussie AI

Fast and Slow Reasoning

Last Updated 27 August, 2025

by David Spuler, Ph.D.

Research on Fast and Slow Reasoning

Research papers include:

Jiabao Pan, Yan Zhang, Chen Zhang, Zuozhu Liu, Hongwei Wang, Haizhou Li, 1 Jul 2024, DynaThink: Fast or Slow? A Dynamic Decision-Making Framework for Large Language Models, https://arxiv.org/abs/2407.01009
Xiaoyu Tian, Liangyu Chen, Na Liu, Yaxuan Liu, Wei Zou, Kaijiang Chen, Ming Cui, 24 Nov 2023 (v4), DUMA: a Dual-Mind Conversational Agent with Fast and Slow Thinking, https://arxiv.org/abs/2310.18075
Daniele Paliotta, Junxiong Wang, Matteo Pagliardini, Kevin Y. Li, Aviv Bick, J. Zico Kolter, Albert Gu, François Fleuret, Tri Dao, 27 Feb 2025, Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners, https://arxiv.org/abs/2502.20339
Jianyuan Zhong, Zeju Li, Zhijian Xu, Xiangyu Wen, Qiang Xu, 16 Feb 2025, Dyve: Thinking Fast and Slow for Dynamic Process Verification, https://arxiv.org/abs/2502.11157
Xiaoxue Cheng, Junyi Li, Wayne Xin Zhao, Ji-Rong Wen, 3 Jan 2025 (v2), Think More, Hallucinate Less: Mitigating Hallucinations via Dual Process of Fast and Slow Thinking, https://arxiv.org/abs/2501.01306
Kangan Qian, Zhikun Ma, Yangfan He, Ziang Luo, Tianyu Shi, Tianze Zhu, Jiayin Li, Jianhui Wang, Ziyu Chen, Xiao He, Yining Shi, Zheng Fu, Xinyu Jiao, Kun Jiang, Diange Yang, Takafumi Matsumaru, 27 Nov 2024, FASIONAD : FAst and Slow FusION Thinking Systems for Human-Like Autonomous Driving with Adaptive Feedback, https://arxiv.org/abs/2411.18013
Ming Li, Yanhong Li, Tianyi Zhou, 31 Oct 2024, What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective, https://arxiv.org/abs/2410.23743
DiJia Su, Sainbayar Sukhbaatar, Michael Rabbat, Yuandong Tian, Qinqing Zheng, 13 Oct 2024, Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces, https://arxiv.org/abs/2410.09918
Konstantina Christakopoulou, Shibl Mourad, Maja Matarić, 10 Oct 2024, Agents Thinking Fast and Slow: A Talker-Reasoner Architecture, https://arxiv.org/abs/2410.08328
Zhiheng Lyu, Zhijing Jin, Fernando Gonzalez, Rada Mihalcea, Bernhard Schölkopf, Mrinmaya Sachan, 27 Oct 2024 (v2), Do LLMs Think Fast and Slow? A Causal Study on Sentiment Analysis, https://arxiv.org/abs/2404.11055
Biqing Qi, Xingquan Chen, Junqi Gao, Dong Li, Jianxing Liu, Ligang Wu, Bowen Zhou, 19 Mar 2024 (v2), Interactive Continual Learning: Fast and Slow Thinking, https://arxiv.org/abs/2403.02628
Pengbo Hu, Ji Qi, Xingyu Li, Hong Li, Xinqi Wang, Bing Quan, Ruiyu Wang, Yi Zhou, 21 Aug 2023 (v2), Tree-of-Mixed-Thought: Combining Fast and Slow Thinking for Multi-hop Visual Reasoning, https://arxiv.org/abs/2308.09658
Thilo Hagendorff, Sarah Fabi, Michal Kosinski, 2 Aug 2023 (v2), Thinking Fast and Slow in Large Language Models, https://arxiv.org/abs/2212.05206
Wenlin Yao, Haitao Mi, Dong Yu, 25 Sep 2024, HDFlow: Enhancing LLM Complex Problem-Solving with Hybrid Thinking and Dynamic Workflows, https://arxiv.org/abs/2409.17433
Fei Tang, Yongliang Shen, Hang Zhang, Siqi Chen, Guiyang Hou, Wenqi Zhang, Wenqiao Zhang, Kaitao Song, Weiming Lu, Yueting Zhuang, 9 Mar 2025, Think Twice, Click Once: Enhancing GUI Grounding via Fast and Slow Systems, https://arxiv.org/abs/2503.06470
Guan Wang, Jin Li, Yuhao Sun, Xing Chen, Changling Liu, Yue Wu, Meng Lu, Sen Song, Yasin Abbasi Yadkori, 22 Jul 2025 (v2), Hierarchical Reasoning Model, https://arxiv.org/abs/2506.21734 https://github.com/sapientinc/HRM
Ben Dickson, July 25, 2025, New AI architecture delivers 100x faster reasoning than LLMs with just 1,000 training examples, https://venturebeat.com/ai/new-ai-architecture-delivers-100x-faster-reasoning-than-llms-with-just-1000-training-examples/
Jason Zhu, Hongyu Li, 13 Jul 2025, Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey, https://arxiv.org/abs/2507.09662
Qianjun Pan, Wenkai Ji, Yuyang Ding, Junsong Li, Shilian Chen, Junyi Wang, Jie Zhou, Qin Chen, Min Zhang, Yulan Wu, Liang He, 8 May 2025 (v2), A Survey of Slow Thinking-based Reasoning LLMs using Reinforced Learning and Inference-time Scaling Law, https://arxiv.org/abs/2505.02665
Chang Xiao, Brenda Yang, 23 Jul 2025, Streaming, Fast and Slow: Cognitive Load-Aware Streaming for Efficient LLM Serving, https://arxiv.org/abs/2504.17999
Lori Dajose, December 17, 2024, Thinking Slowly: The Paradoxical Slowness of Human Behavior, https://www.caltech.edu/about/news/thinking-slowly-the-paradoxical-slowness-of-human-behavior
Zhong-Zhi Li, Duzhen Zhang, Ming-Liang Zhang, Jiaxin Zhang, Zengyan Liu, Yuxuan Yao, Haotian Xu, Junhao Zheng, Pei-Jie Wang, Xiuyi Chen, Yingying Zhang, Fei Yin, Jiahua Dong, Zhijiang Guo, Le Song, Cheng-Lin Liu, 25 Feb 2025 (v2), From System 1 to System 2: A Survey of Reasoning Large Language Models, https://arxiv.org/abs/2502.17419
Zhihao Dou and Dongfei Cui and Jun Yan and Weida Wang and Benteng Chen and Haoming Wang and Zeke Xie and Shufei Zhang, 25 Aug 2025, DSADF: Thinking Fast and Slow for Decision Making, https://arxiv.org/abs/2505.08189