title: Dolphin: Closed-loop Open-ended Auto-research through Thinking,
    Practice, and Feedback
summary: The scientific research paradigm is undergoing a profound transformation
  owing to the development of Artificial Intelligence (AI). Recent works
  demonstrate that various AI-assisted research methods can largely improve
  research efficiency by improving data analysis, accelerating computation, and
  fostering novel idea generation. To further move towards the ultimate goal
  (i.e., automatic scientific research), in this paper, we propose Dolphin, the
  first closed-loop open-ended auto-research framework to further build the
  entire process of human scientific research. Dolphin can generate research
  ideas, perform experiments, and get feedback from experimental results to
  generate higher-quality ideas. More specifically, Dolphin first generates novel
  ideas based on relevant papers which are ranked by the topic and task
  attributes. Then, the codes are automatically generated and debugged with the
  exception-traceback-guided local code structure. Finally, Dolphin automatically
  analyzes the results of each idea and feeds the results back to the next round
  of idea generation. Experiments are conducted on the benchmark datasets of
  different topics and results show that Dolphin can generate novel ideas
  continuously and complete the experiment in a loop. We highlight that Dolphin
  can automatically propose methods that are comparable to the state-of-the-art
  in some tasks such as 2D image classification and 3D point classification.
paper_authors._id: 677e3b1ddbff7b495e8f0424
paper_authors.name: Jiakang Yuan
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-01-08T13:52:54.625Z
paper_authors._id: 64a3d1ddb3239f3e3892b24b
paper_authors.avatarUrl: /avatars/7ce585f5fc1d077fb1d70cc18c4da2c1.svg
paper_authors.fullname: Jiakang Yuan
paper_authors.type: user
paper_authors.user: JiakangYuan
paper_authors._id: 677e3b1ddbff7b495e8f0425
paper_authors.name: Xiangchao Yan
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-01-08T13:53:08.361Z
paper_authors._id: 65b88b92e0bde92c176a888a
paper_authors.avatarUrl: /avatars/fc1cb54328ca93860e97fc73a3c1eb2f.svg
paper_authors.fullname: Xiangchao Yan
paper_authors.type: user
paper_authors.user: yxc97
paper_authors._id: 677e3b1ddbff7b495e8f0426
paper_authors.name: Botian Shi
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-01-08T13:53:16.461Z
paper_authors._id: 643df87f7cd64d872cb9fabd
paper_authors.avatarUrl: /avatars/c53bfabcee08de448dde973915e8b31d.svg
paper_authors.fullname: Botian Shi
paper_authors.type: user
paper_authors.user: friskit
paper_authors._id: 677e3b1ddbff7b495e8f0427
paper_authors.name: Tao Chen
paper_authors._id: 677e3b1ddbff7b495e8f0428
paper_authors.name: Wanli Ouyang
paper_authors._id: 677e3b1ddbff7b495e8f0429
paper_authors.name: Bo Zhang
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-01-08T09:44:24.813Z
paper_authors._id: 643dfd235aafbdca3a5792c0
paper_authors.avatarUrl: /avatars/ce8553cf5936012c692e08054ee27937.svg
paper_authors.fullname: Bo Zhang
paper_authors.type: user
paper_authors.user: BoZhang
paper_authors._id: 677e3b1ddbff7b495e8f042a
paper_authors.name: Lei Bai
paper_authors._id: 677e3b1ddbff7b495e8f042b
paper_authors.name: Yu Qiao
paper_authors._id: 677e3b1ddbff7b495e8f042c
paper_authors.name: Bowen Zhou
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-01-08T13:53:56.271Z
paper_authors._id: 669f614b59adf5b56e05bce3
paper_authors.avatarUrl: /avatars/ffd4189efbceb0e63a03db273065a44b.svg
paper_authors.fullname: BowenZhou
paper_authors.type: user
paper_authors.user: bowenZhou
paper_title: Dolphin: Closed-loop Open-ended Auto-research through Thinking,
    Practice, and Feedback
paper_summary: The scientific research paradigm is undergoing a profound transformation
  owing to the development of Artificial Intelligence (AI). Recent works
  demonstrate that various AI-assisted research methods can largely improve
  research efficiency by improving data analysis, accelerating computation, and
  fostering novel idea generation. To further move towards the ultimate goal
  (i.e., automatic scientific research), in this paper, we propose Dolphin, the
  first closed-loop open-ended auto-research framework to further build the
  entire process of human scientific research. Dolphin can generate research
  ideas, perform experiments, and get feedback from experimental results to
  generate higher-quality ideas. More specifically, Dolphin first generates novel
  ideas based on relevant papers which are ranked by the topic and task
  attributes. Then, the codes are automatically generated and debugged with the
  exception-traceback-guided local code structure. Finally, Dolphin automatically
  analyzes the results of each idea and feeds the results back to the next round
  of idea generation. Experiments are conducted on the benchmark datasets of
  different topics and results show that Dolphin can generate novel ideas
  continuously and complete the experiment in a loop. We highlight that Dolphin
  can automatically propose methods that are comparable to the state-of-the-art
  in some tasks such as 2D image classification and 3D point classification.