15 citations · 38 across the 13 of their papers we have counts for
13 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…
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…
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…
Robust Implementation of Retrieval-Augmented Generation on Edge-based Computing-in-Memory Architectures
Ruiyang Qin, Zheyu Yan, Dewen Zeng +8
Large Language Models (LLMs) deployed on edge devices learn through fine-tuning and updating a certain portion of their parameters. Although such learning methods can be optimized…
FL-NAS: Towards Fairness of NAS for Resource Constrained Devices via Large Language Models
Ruiyang Qin, Yuting Hu, Zheyu Yan +3
Neural Architecture Search (NAS) has become the de fecto tools in the industry in automating the design of deep neural networks for various applications, especially those driven by…
Enabling On-Device Large Language Model Personalization with Self-Supervised Data Selection and Synthesis
Ruiyang Qin, Jun Xia, Zhenge Jia +5
After a large language model (LLM) is deployed on edge devices, it is desirable for these devices to learn from user-generated conversation data to generate user-specific and perso…
When Automated Assessment Meets Automated Content Generation: Examining Text Quality in the Era of GPTs
Marialena Bevilacqua, Kezia Oketch, Ruiyang Qin +5
The use of machine learning (ML) models to assess and score textual data has become increasingly pervasive in an array of contexts including natural language processing, informatio…
Hybrid Gate-Pulse Model for Variational Quantum Algorithms
Zhiding Liang, Zhixin Song, Jinglei Cheng +8
Current quantum programs are mostly synthesized and compiled on the gate-level, where quantum circuits are composed of quantum gates. The gate-level workflow, however, introduces s…
Improving Quantum Classifier Performance in NISQ Computers by Voting Strategy from Ensemble Learning
Ruiyang Qin, Zhiding Liang, Jinglei Cheng +2
Due to the immense potential of quantum computers and the significant computing overhead required in machine learning applications, the variational quantum classifier (VQC) has rec…
IBERT: Idiom Cloze-style reading comprehension with Attention
Ruiyang Qin, Haozheng Luo, Zheheng Fan +1
Idioms are special fixed phrases usually derived from stories. They are commonly used in casual conversations and literary writings. Their meanings are usually highly non-compositi…
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…