New Era
The "New Era" in the provided research papers centers on the transformative impact of large language models (LLMs) and related foundation models across diverse fields. Current research focuses on adapting and evaluating these models for tasks like data analysis, multimodal understanding, and spatio-temporal forecasting, often involving novel benchmarking strategies and addressing challenges such as energy efficiency and explainability. This work is significant because it explores the potential of LLMs to improve existing methods and create entirely new approaches in various scientific domains and practical applications, ranging from healthcare to autonomous systems. The overarching goal is to understand and harness the capabilities of these powerful models while mitigating their limitations and ethical concerns.
Papers
Revisiting Zero-Shot Abstractive Summarization in the Era of Large Language Models from the Perspective of Position Bias
Anshuman Chhabra, Hadi Askari, Prasant Mohapatra
The Internet of Things in the Era of Generative AI: Vision and Challenges
Xin Wang, Zhongwei Wan, Arvin Hekmati, Mingyu Zong, Samiul Alam, Mi Zhang, Bhaskar Krishnamachari
A Survey of Text Watermarking in the Era of Large Language Models
Aiwei Liu, Leyi Pan, Yijian Lu, Jingjing Li, Xuming Hu, Xi Zhang, Lijie Wen, Irwin King, Hui Xiong, Philip S. Yu
Morphological Profiling for Drug Discovery in the Era of Deep Learning
Qiaosi Tang, Ranjala Ratnayake, Gustavo Seabra, Zhe Jiang, Ruogu Fang, Lina Cui, Yousong Ding, Tamer Kahveci, Jiang Bian, Chenglong Li, Hendrik Luesch, Yanjun Li