Towards Scientific Discovery with Generative AI: Progress, Opportunities, and Challenges

16 December 2024

Papers citing "Towards Scientific Discovery with Generative AI: Progress, Opportunities, and Challenges"

6 / 6 papers shown

Title
Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Jiayi Geng Howard Chen Dilip Arumugam Thomas L. Griffiths 22 0 0 23 May 2025
AI-Driven Automation Can Become the Foundation of Next-Era Science of Science Research Renqi Chen Haoyang Su Shixiang Tang Zhenfei Yin Qi Wu Hui Li Ye Sun Nanqing Dong Wanli Ouyang Philip Torr AI4CE 32 0 0 17 May 2025
Benchmarking AI scientists in omics data-driven biological research Erpai Luo Jinmeng Jia Yifan Xiong Xiangyu Li Xiaobo Guo Baoqi Yu Lei Wei Xuegong Zhang ELM 30 0 0 13 May 2025
LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models Parshin Shojaee Ngoc-Hieu Nguyen Kazem Meidani A. Farimani Khoa D. Doan Chandan K. Reddy 36 1 0 14 Apr 2025
AI-Newton: A Concept-Driven Physical Law Discovery System without Prior Physical Knowledge You-Le Fang Dong-Shan Jian Xiang Li Yan Ma 42 0 0 02 Apr 2025
Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning Yibo Yan Shen Wang Jiahao Huo Jingheng Ye Zhendong Chu Xuming Hu Philip S. Yu Carla P. Gomes B. Selman Qingsong Wen LRM 132 14 0 05 Feb 2025