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20242026
most citedExploring Large-Scale Language Models to Evaluate EEG-Based Multimodal Data for Mental Health

28 citations · 53 across the 10 of their papers we have counts for

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5 papers · 1 filter

cs.HC2024★ 1 cited

Exploring Device-Oriented Video Encryption for Hierarchical Privacy Protection in AR Content Sharing

Yongquan Hu, Dongsheng Zheng, Kexin Nie +3

Content sharing across multiple Augmented Reality (AR) displays is becoming commonplace, enhancing team communication and collaboration through devices like smartphones and AR glas…

cs.HC2024

Adanonymizer: Interactively Navigating and Balancing the Duality of Privacy and Output Performance in Human-LLM Interaction

Shuning Zhang, Xin Yi, Haobin Xing +3

Current Large Language Models (LLMs) cannot support users to precisely balance privacy protection and output performance during individual consultations. We introduce Adanonymizer,…

cs.HC2024★ 3 cited

Towards Enhanced Context Awareness with Vision-based Multimodal Interfaces

Yongquan Hu, Wen Hu, Aaron Quigley

Vision-based Interfaces (VIs) are pivotal in advancing Human-Computer Interaction (HCI), particularly in enhancing context awareness. However, there are significant opportunities f…

cs.HC2024★ 28 cited

Exploring Large-Scale Language Models to Evaluate EEG-Based Multimodal Data for Mental Health

Yongquan Hu, Shuning Zhang, Ting Dang +4

Integrating physiological signals such as electroencephalogram (EEG), with other data such as interview audio, may offer valuable multimodal insights into psychological states or n…

cs.HC2024

MultiSurf-GPT: Facilitating Context-Aware Reasoning with Large-Scale Language Models for Multimodal Surface Sensing

Yongquan Hu, Black Sun, Pengcheng An +3

Surface sensing is widely employed in health diagnostics, manufacturing and safety monitoring. Advances in mobile sensing affords this potential for context awareness in mobile com…