Best Practice
Best practices in various scientific fields are currently a major focus, aiming to optimize methodologies and improve the reliability, efficiency, and ethical implications of research. Research emphasizes improving model architectures and algorithms across diverse applications, including large language models, Bayesian optimization, and graph neural networks, with a strong emphasis on addressing issues like bias, interpretability, and efficient resource utilization. These efforts are crucial for advancing scientific understanding and ensuring the responsible development and deployment of technologies across numerous domains, from healthcare and finance to materials science and robotics.
Papers
Searching for Best Practices in Retrieval-Augmented Generation
Xiaohua Wang, Zhenghua Wang, Xuan Gao, Feiran Zhang, Yixin Wu, Zhibo Xu, Tianyuan Shi, Zhengyuan Wang, Shizheng Li, Qi Qian, Ruicheng Yin, Changze Lv, Xiaoqing Zheng, Xuanjing Huang
From Introspection to Best Practices: Principled Analysis of Demonstrations in Multimodal In-Context Learning
Nan Xu, Fei Wang, Sheng Zhang, Hoifung Poon, Muhao Chen