海豚：透過思考、實踐和反饋的封閉迴路開放式自主研究。

摘要

科學研究範式正在深刻轉變，這歸因於人工智慧（AI）的發展。最近的研究表明，各種AI輔助的研究方法可以大大提高研究效率，通過改善數據分析、加速計算和促進新思想的產生。為了更進一步朝著最終目標（即自動科學研究）邁進，在本文中，我們提出了Dolphin，這是第一個封閉迴路的開放式自動研究框架，以進一步構建整個人類科學研究過程。Dolphin能夠產生研究思想，執行實驗，並從實驗結果中獲得反饋，以生成更高質量的思想。具體而言，Dolphin首先基於按主題和任務屬性排名的相關論文生成新思想。然後，代碼將根據異常-回溯引導的本地代碼結構自動生成和調試。最後，Dolphin自動分析每個思想的結果，並將結果反饋給下一輪的思想生成。在不同主題的基準數據集上進行實驗，結果顯示Dolphin能夠持續生成新思想並完成循環實驗。我們強調Dolphin能夠自動提出與某些任務（如2D圖像分類和3D點分類）中的最新技術相媲美的方法。

English

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.

海豚：透過思考、實踐和反饋的封閉迴路開放式自主研究。

Dolphin: Closed-loop Open-ended Auto-research through Thinking, Practice, and Feedback

摘要

Summary

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