Intelligent Assistant
Intelligent assistants are software systems designed to automate tasks and provide personalized support to users, aiming to improve efficiency and user experience across various domains. Current research focuses on enhancing these assistants using large language models (LLMs), retrieval-augmented generation (RAG), and Bayesian methods to improve memory, personalization, and contextual understanding, often incorporating multimodal interactions (e.g., voice, vision, and gesture). This research is significant because it addresses challenges in human-computer interaction, knowledge sharing, and task automation, with implications for diverse fields including manufacturing, healthcare, education, and customer service.
Papers
Factory Operators' Perspectives on Cognitive Assistants for Knowledge Sharing: Challenges, Risks, and Impact on Work
Samuel Kernan Freire, Tianhao He, Chaofan Wang, Evangelos Niforatos, Alessandro Bozzon
MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal Assistants
Zeyu Zhang, Quanyu Dai, Luyu Chen, Zeren Jiang, Rui Li, Jieming Zhu, Xu Chen, Yi Xie, Zhenhua Dong, Ji-Rong Wen