9 papers
Multilingual Safety Alignment via Self-Distillation
Ruiyang Qin, Qingzhuo Wang, Dongrui Liu +3
Large language models (LLMs) exhibit severe multilingual safety misalignment: they possess strong safeguards in high-resource languages but remain highly vulnerable to jailbreak at…
Tiny-Align: Bridging Automatic Speech Recognition and Large Language Model on the Edge
Ruiyang Qin, Dancheng Liu, Gelei Xu +7
The combination of Large Language Models (LLM) and Automatic Speech Recognition (ASR), when deployed on edge devices (called edge ASR-LLM), can serve as a powerful personalized ass…
PI-Whisper: Designing an Adaptive and Incremental Automatic Speech Recognition System for Edge Devices
Amir Nassereldine, Dancheng Liu, Chenhui Xu +3
Edge-based automatic speech recognition (ASR) technologies are increasingly prevalent in the development of intelligent and personalized assistants. However, resource-constrained A…
Empirical Guidelines for Deploying LLMs onto Resource-constrained Edge Devices
Ruiyang Qin, Dancheng Liu, Chenhui Xu +9
The scaling laws have become the de facto guidelines for designing large language models (LLMs), but they were studied under the assumption of unlimited computing resources for bot…
An Adaptive System for Wearable Devices to Detect Stress Using Physiological Signals
Gelei Xu, Ruiyang Qin, Zhi Zheng +1
Timely stress detection is crucial for protecting vulnerable groups from long-term detrimental effects by enabling early intervention. Wearable devices, by collecting real-time phy…
Open-Ended Multi-Modal Relational Reasoning for Video Question Answering
Haozheng Luo, Ruiyang Qin, Chenwei Xu +2
In this paper, we introduce a robotic agent specifically designed to analyze external environments and address participants' questions. The primary focus of this agent is to assist…