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Recent advances in machine learning and AI, including Generative AI and LLMs, are disrupting technological innovation, product development, and society as a whole. AI's contribution to technology can come from multiple approaches that…

The powerful reasoning capabilities of Large Language Models (LLMs) in mathematics and coding, combined with their ability to automate complex tasks through agentic frameworks, present unprecedented opportunities for accelerating scientific…

人工智能 · 计算机科学 2025-05-27 Jiabin Tang , Lianghao Xia , Zhonghang Li , Chao Huang

Analogies have been central to creative problem-solving throughout the history of science and technology. As the number of scientific papers continues to increase exponentially, there is a growing opportunity for finding diverse solutions…

人机交互 · 计算机科学 2022-06-01 Hyeonsu B. Kang , Xin Qian , Tom Hope , Dafna Shahaf , Joel Chan , Aniket Kittur

As AI promises to accelerate scientific discovery, it remains unclear whether fully AI-driven research is possible and whether it can adhere to key scientific values, such as transparency, traceability and verifiability. Mimicking human…

其他定量生物学 · 定量生物学 2024-04-30 Tal Ifargan , Lukas Hafner , Maor Kern , Ori Alcalay , Roy Kishony

Scientific discovery increasingly entails long-horizon exploration of complex hypothesis spaces, yet most existing approaches emphasize final performance while offering limited insight into how scientific exploration unfolds over time,…

The cognitive sciences aim to understand intelligence by formalizing underlying operations as computational models. Traditionally, this follows a cycle of discovery where researchers develop paradigms, collect data, and test predefined…

人工智能 · 计算机科学 2026-03-24 Akshay K. Jagadish , Milena Rmus , Kristin Witte , Marvin Mathony , Marcel Binz , Eric Schulz

Recent advances in large language models (LLMs) have opened new avenues for accelerating scientific research. While models are increasingly capable of assisting with routine tasks, their ability to contribute to novel, expert-level…

Novel research ideas play a critical role in advancing scientific inquiries. Recent advancements in Large Language Models (LLMs) have demonstrated their potential to generate novel research ideas by leveraging large-scale scientific…

人工智能 · 计算机科学 2025-11-05 Keyu Zhao , Weiquan Lin , Qirui Zheng , Fengli Xu , Yong Li

The exponential growth of academic publications poses challenges for the research process, such as literature review and procedural planning. Large Language Models (LLMs) have emerged as powerful AI tools, especially when combined with…

应用物理 · 物理学 2025-02-13 Joaquin Ramirez-Medina , Mohammadmehdi Ataei , Alidad Amirfazli

Scientific discovery has long been constrained by human limitations in expertise, physical capability, and sleep cycles. The recent rise of AI scientists and automated laboratories has accelerated both the cognitive and operational aspects…

Artificial intelligence is undergoing a profound transition from a computational instrument to an autonomous originator of scientific knowledge. This emerging paradigm, the AI scientist, is architected to emulate the complete scientific…

人工智能 · 计算机科学 2026-01-21 Guiyao Tie , Pan Zhou , Lichao Sun

Autonomous scientific discovery with large language model (LLM)-based agents has recently made substantial progress, demonstrating the ability to automate end-to-end research workflows. However, existing systems largely rely on…

计算工程、金融与科学 · 计算机科学 2026-01-29 Tengyue Xu , Zhuoyang Qian , Gaoge Liu , Li Ling , Zhentao Zhang , Biao Wu , Shuo Zhang , Ke Lu , Wei Shi , Ziqi Wang , Zheng Feng , Yan Luo , Shu Xu , Yongjin Chen , Zhibo Feng , Zhuo Chen , Bruce Yuan , Harry Wang , Kris Chen

The rapid advancement of large language models (LLMs) has opened new possibilities for automating the proposal of innovative scientific ideas. This process involves two key phases: literature retrieval and idea generation. However, existing…

计算与语言 · 计算机科学 2025-02-18 Wenxiao Wang , Lihui Gu , Liye Zhang , Yunxiang Luo , Yi Dai , Chen Shen , Liang Xie , Binbin Lin , Xiaofei He , Jieping Ye

Automating scientific discovery requires more than generating papers from ideas. Real research is iterative: hypotheses are challenged from multiple perspectives, experiments fail and inform the next attempt, and lessons accumulate across…

Large language models (LLMs) have rapidly evolved from text generators into powerful problem solvers. Yet, many open tasks demand critical thinking, multi-source, and verifiable outputs, which are beyond single-shot prompting or standard…

Collaboration is the defining mode of modern science, yet its core mechanism -- feedback -- remains hard to observe, difficult to scale, and unequally distributed. Here we test whether large language models (LLMs) can contribute to this…

物理与社会 · 物理学 2026-05-26 Binglu Wang , Weixin Liang , Jiahui Xue , Yuhui Zhang , Hancheng Cao , Dashun Wang , Yian Yin

AI-assisted research is crossing a threshold: fully automated systems can now generate research papers for as little as $15, while long-horizon agents can execute experiments, draft manuscripts, and simulate critique with minimal human…

Large Language Models (LLMs) are catalyzing a paradigm shift in scientific discovery, evolving from task-specific automation tools into increasingly autonomous agents and fundamentally redefining research processes and human-AI…

计算与语言 · 计算机科学 2025-09-18 Tianshi Zheng , Zheye Deng , Hong Ting Tsang , Weiqi Wang , Jiaxin Bai , Zihao Wang , Yangqiu Song

Artificial intelligence (AI) is reshaping how research is conceived, conducted, and communicated across fields from chemistry to biomedicine. This commentary examines how AI is transforming the research workflow. AI systems now help…

人工智能 · 计算机科学 2025-11-14 Maksim E. Eren , Dorianis M. Perez

The quest for fully autonomous vehicles (AVs) capable of navigating complex real-world scenarios with human-like understanding and responsiveness. In this paper, we introduce Dolphins, a novel vision-language model architected to imbibe…

计算机视觉与模式识别 · 计算机科学 2023-12-04 Yingzi Ma , Yulong Cao , Jiachen Sun , Marco Pavone , Chaowei Xiao
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