worldbench/awesome-ai-auto-research
GitHub: worldbench/awesome-ai-auto-research
该仓库是一份系统梳理 AI 自动化科研全生命周期的论文追踪与资源列表，按研究流程的八个阶段分类整理相关前沿工作。
Stars: 459 | Forks: 35
[](https://github.com/sindresorhus/awesome)
[](https://arxiv.org/abs/2605.18661)
[](https://worldbench.github.io/awesome-ai-auto-research)
[](https://github.com/worldbench/awesome-ai-auto-research/pulls)
# :sunglasses: Awesome AI Auto-Research
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This repository accompanies the survey paper **"[AI for Auto-Research: Roadmap & User Guide](https://worldbench.github.io/awesome-ai-auto-research)"** and tracks papers on AI-assisted and automated scientific research, covering the **full research lifecycle**.
### :robot: AI Auto-Research
We organize the academic research lifecycle as eight interconnected stages grouped into four epistemological phases. Each phase serves a distinct function in producing, scrutinizing, and communicating scientific knowledge.
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| **Phase 1: Creation**
Generating novel research ideas, searching and synthesizing literature, running coding experiments, and creating publication-quality tables and figures. This phase spans **Idea Generation**, **Literature Review**, **Coding & Experiments**, and **Tables & Figures**. | |
| **Phase 2: Writing**
Drafting, editing, and polishing academic manuscripts. AI assistance ranges from semi-automated grammar and citation tools to fully automated paper generation — the most commercially mature yet ethically contested stage. | |
| **Phase 3: Validation**
Automated peer review generation, reviewer-paper matching, review quality assessment, and AI-assisted author rebuttals. This phase covers **Peer Review** and **Rebuttal & Revision**. | |
| **Phase 4: Dissemination**
Converting papers into slides, posters, videos, websites, and social media content. Each output format targets a different audience and demands its own design logic and AI tool chain. | | | | For additional details, kindly refer to our :books: [**Paper**](https://worldbench.github.io/assets_common/papers/survey-ai-auto-research.pdf) and :earth_asia: [**Project Page**](https://worldbench.github.io/awesome-ai-auto-research). ### :books: Citation If you find this work helpful for your research, please kindly consider citing our paper: @article{survey-ai-auto-research, title = {{AI} for {Auto-Research}: Roadmap \& User Guide}, author = {Kong, Lingdong and Sun, Xian and Chow, Wei and Li, Linfeng and Lin, Kevin Qinghong and Zhang, Xuan Billy and Wang, Song and Li, Rong and Wu, Qing and Gao, Wei and Wang, Yingshuo and Xie, Shaoyuan and Liu, Jiachen and Qu, Leigang and Li, Shijie and Ng, Lai Xing and Cottereau, Benoit R. and Liu, Ziwei and Chua, Tat-Seng and Ooi, Wei Tsang}, journal = {arXiv preprint arXiv:2605.18661}, year = {2026} } ## Table of Contents - [**0. Background**](#background)
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|:-:|
This repository accompanies the survey paper **"[AI for Auto-Research: Roadmap & User Guide](https://worldbench.github.io/awesome-ai-auto-research)"** and tracks papers on AI-assisted and automated scientific research, covering the **full research lifecycle**.
### :robot: AI Auto-Research
We organize the academic research lifecycle as eight interconnected stages grouped into four epistemological phases. Each phase serves a distinct function in producing, scrutinizing, and communicating scientific knowledge.
| | |
|:-:|:-|
| | **Phase 1: Creation**Generating novel research ideas, searching and synthesizing literature, running coding experiments, and creating publication-quality tables and figures. This phase spans **Idea Generation**, **Literature Review**, **Coding & Experiments**, and **Tables & Figures**. | |
| **Phase 2: Writing**Drafting, editing, and polishing academic manuscripts. AI assistance ranges from semi-automated grammar and citation tools to fully automated paper generation — the most commercially mature yet ethically contested stage. | |
| **Phase 3: Validation**Automated peer review generation, reviewer-paper matching, review quality assessment, and AI-assisted author rebuttals. This phase covers **Peer Review** and **Rebuttal & Revision**. | |
| **Phase 4: Dissemination**Converting papers into slides, posters, videos, websites, and social media content. Each output format targets a different audience and demands its own design logic and AI tool chain. | | | | For additional details, kindly refer to our :books: [**Paper**](https://worldbench.github.io/assets_common/papers/survey-ai-auto-research.pdf) and :earth_asia: [**Project Page**](https://worldbench.github.io/awesome-ai-auto-research). ### :books: Citation If you find this work helpful for your research, please kindly consider citing our paper: @article{survey-ai-auto-research, title = {{AI} for {Auto-Research}: Roadmap \& User Guide}, author = {Kong, Lingdong and Sun, Xian and Chow, Wei and Li, Linfeng and Lin, Kevin Qinghong and Zhang, Xuan Billy and Wang, Song and Li, Rong and Wu, Qing and Gao, Wei and Wang, Yingshuo and Xie, Shaoyuan and Liu, Jiachen and Qu, Leigang and Li, Shijie and Ng, Lai Xing and Cottereau, Benoit R. and Liu, Ziwei and Chua, Tat-Seng and Ooi, Wei Tsang}, journal = {arXiv preprint arXiv:2605.18661}, year = {2026} } ## Table of Contents - [**0. Background**](#background)