28 citations · 28 across the 28 of their papers we have counts for
7 papers · 1 filter
Position: Human-Robot Interaction in Embodied Intelligence Demands a Shift From Static Privacy Controls to Dynamic Learning
Shuning Zhang, Hong Jia, Simin Li +4
The reasoning capabilities of embodied agents introduce a critical, under-explored inferential privacy challenge, where the risk of an agent generate sensitive conclusions from amb…
HealthSLM-Bench: Benchmarking Small Language Models for Mobile and Wearable Healthcare Monitoring
Xin Wang, Ting Dang, Xinyu Zhang +3
Mobile and wearable healthcare monitoring play a vital role in facilitating timely interventions, managing chronic health conditions, and ultimately improving individuals' quality…
From Patient Burdens to User Agency: Designing for Real-Time Protection Support in Online Health Consultations
Shuning Zhang, Ying Ma, Yongquan `Owen' Hu +4
Online medical consultation platforms, while convenient, are undermined by significant privacy risks that erode user trust. We first conducted in-depth semi-structured interviews w…
E-BATS: Efficient Backpropagation-Free Test-Time Adaptation for Speech Foundation Models
Jiaheng Dong, Hong Jia, Soumyajit Chatterjee +3
Speech Foundation Models encounter significant performance degradation when deployed in real-world scenarios involving acoustic domain shifts, such as background noise and speaker…
FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models
Yan Gao, Massimo Roberto Scamarcia, Javier Fernandez-Marques +18
Large Language Models (LLMs) have achieved state-of-the-art results across diverse domains, yet their development remains reliant on vast amounts of publicly available data, raisin…
Token-Level Logits Matter: A Closer Look at Speech Foundation Models for Ambiguous Emotion Recognition
Jule Valendo Halim, Siyi Wang, Hong Jia +1
Emotional intelligence in conversational AI is crucial across domains like human-computer interaction. While numerous models have been developed, they often overlook the complexity…
Scaling Auditory Cognition via Test-Time Compute in Audio Language Models
Ting Dang, Yan Gao, Hong Jia
Large language models (LLMs) have shown exceptional versatility in natural language processing, prompting recent efforts to extend their multimodal capabilities to speech processin…