@inproceedings{zhou-etal-2025-hypothesis,
title = "From Hypothesis to Publication: A Comprehensive Survey of {AI}-Driven Research Support Systems",
author = "Zhou, Zekun and
Feng, Xiaocheng and
Huang, Lei and
Feng, Xiachong and
Song, Ziyun and
Chen, Ruihan and
Zhao, Liang and
Ma, Weitao and
Gu, Yuxuan and
Wang, Baoxin and
Wu, Dayong and
Hu, Guoping and
Liu, Ting and
Qin, Bing",
editor = "Christodoulopoulos, Christos and
Chakraborty, Tanmoy and
Rose, Carolyn and
Peng, Violet",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-emnlp.631/",
pages = "11773--11803",
ISBN = "979-8-89176-335-7",
abstract = "Research is a fundamental process driving the advancement of human civilization, yet it demands substantial time and effort from researchers. In recent years, the rapid development of artificial intelligence (AI) technologies has inspired researchers to explore how AI can accelerate and enhance research. To monitor relevant advancements, this paper presents a systematic review of the progress in this domain. Specifically, we organize the relevant studies into three main categories: hypothesis formulation, hypothesis validation, and manuscript publication. Hypothesis formulation involves knowledge synthesis and hypothesis generation. Hypothesis validation includes the verification of scientific claims, theorem proving, and experiment validation. Manuscript publication encompasses manuscript writing and the peer review process. Furthermore, we identify and discuss the current challenges faced in these areas, as well as potential future directions for research. Finally, we also offer a comprehensive overview of existing benchmarks and tools across various domains that support the integration of AI into the research process. We hope this paper serves as an introduction for beginners and fosters future research."
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<abstract>Research is a fundamental process driving the advancement of human civilization, yet it demands substantial time and effort from researchers. In recent years, the rapid development of artificial intelligence (AI) technologies has inspired researchers to explore how AI can accelerate and enhance research. To monitor relevant advancements, this paper presents a systematic review of the progress in this domain. Specifically, we organize the relevant studies into three main categories: hypothesis formulation, hypothesis validation, and manuscript publication. Hypothesis formulation involves knowledge synthesis and hypothesis generation. Hypothesis validation includes the verification of scientific claims, theorem proving, and experiment validation. Manuscript publication encompasses manuscript writing and the peer review process. Furthermore, we identify and discuss the current challenges faced in these areas, as well as potential future directions for research. Finally, we also offer a comprehensive overview of existing benchmarks and tools across various domains that support the integration of AI into the research process. We hope this paper serves as an introduction for beginners and fosters future research.</abstract>
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%0 Conference Proceedings
%T From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systems
%A Zhou, Zekun
%A Feng, Xiaocheng
%A Huang, Lei
%A Feng, Xiachong
%A Song, Ziyun
%A Chen, Ruihan
%A Zhao, Liang
%A Ma, Weitao
%A Gu, Yuxuan
%A Wang, Baoxin
%A Wu, Dayong
%A Hu, Guoping
%A Liu, Ting
%A Qin, Bing
%Y Christodoulopoulos, Christos
%Y Chakraborty, Tanmoy
%Y Rose, Carolyn
%Y Peng, Violet
%S Findings of the Association for Computational Linguistics: EMNLP 2025
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-335-7
%F zhou-etal-2025-hypothesis
%X Research is a fundamental process driving the advancement of human civilization, yet it demands substantial time and effort from researchers. In recent years, the rapid development of artificial intelligence (AI) technologies has inspired researchers to explore how AI can accelerate and enhance research. To monitor relevant advancements, this paper presents a systematic review of the progress in this domain. Specifically, we organize the relevant studies into three main categories: hypothesis formulation, hypothesis validation, and manuscript publication. Hypothesis formulation involves knowledge synthesis and hypothesis generation. Hypothesis validation includes the verification of scientific claims, theorem proving, and experiment validation. Manuscript publication encompasses manuscript writing and the peer review process. Furthermore, we identify and discuss the current challenges faced in these areas, as well as potential future directions for research. Finally, we also offer a comprehensive overview of existing benchmarks and tools across various domains that support the integration of AI into the research process. We hope this paper serves as an introduction for beginners and fosters future research.
%U https://aclanthology.org/2025.findings-emnlp.631/
%P 11773-11803
Markdown (Informal)
[From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systems](https://aclanthology.org/2025.findings-emnlp.631/) (Zhou et al., Findings 2025)
ACL
- Zekun Zhou, Xiaocheng Feng, Lei Huang, Xiachong Feng, Ziyun Song, Ruihan Chen, Liang Zhao, Weitao Ma, Yuxuan Gu, Baoxin Wang, Dayong Wu, Guoping Hu, Ting Liu, and Bing Qin. 2025. From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systems. In Findings of the Association for Computational Linguistics: EMNLP 2025, pages 11773–11803, Suzhou, China. Association for Computational Linguistics.