AI Researcher
AI researchers are developing autonomous systems capable of conducting scientific research, encompassing hypothesis generation, experimentation, and result analysis. Current research focuses on creating robust and reproducible AI agents using large language models and other deep learning architectures, often evaluated through benchmarks designed to assess their ability to solve real-world scientific problems across various domains. This work aims to improve the efficiency and effectiveness of scientific discovery, potentially accelerating breakthroughs in fields like medicine, materials science, and mathematics, while also addressing ethical considerations and biases inherent in AI systems.
Papers
StarWhisper Telescope: Agent-Based Observation Assistant System to Approach AI Astrophysicist
Cunshi Wang, Xinjie Hu, Yu Zhang, Xunhao Chen, Pengliang Du, Yiming Mao, Rui Wang, Yuyang Li, Ying Wu, Hang Yang, Yansong Li, Beichuan Wang, Haiyang Mu, Zheng Wang, Jianfeng Tian, Liang Ge, Yongna Mao, Shengming Li, Xiaomeng Lu, Jinhang Zou, Yang Huang, Ningchen Sun, Jie Zheng, Min He, Yu Bai, Junjie Jin, Hong Wu, Chaohui Shang, Jifeng Liu
DSAI: Unbiased and Interpretable Latent Feature Extraction for Data-Centric AI
Hyowon Cho, Soonwon Ka, Daechul Park, Jaewook Kang, Minjoon Seo, Bokyung Son