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
ERAS: Evaluating the Robustness of Chinese NLP Models to Morphological Garden Path Errors
Qinchan Li, Sophie Hao
On the Risk of Evidence Pollution for Malicious Social Text Detection in the Era of LLMs
Herun Wan, Minnan Luo, Zhixiong Su, Guang Dai, Xiang Zhao
A linguistic analysis of undesirable outcomes in the era of generative AI
Daniele Gambetta, Gizem Gezici, Fosca Giannotti, Dino Pedreschi, Alistair Knott, Luca Pappalardo
MC-Bench: A Benchmark for Multi-Context Visual Grounding in the Era of MLLMs
Yunqiu Xu, Linchao Zhu, Yi Yang
Parametric Graph Representations in the Era of Foundation Models: A Survey and Position
Dongqi Fu, Liri Fang, Zihao Li, Hanghang Tong, Vetle I. Torvik, Jingrui He