2 citations · 5 across the 14 of their papers we have counts for
14 papers
Rethinking On-Device LLM Reasoning: Why Analogical Mapping Outperforms Abstract Thinking for IoT DDoS Detection
William Pan, Guiran Liu, Binrong Zhu +4
The rapid expansion of IoT deployments has intensified cybersecurity threats, notably Distributed Denial of Service (DDoS) attacks, characterized by increasingly sophisticated patt…
ExpertAgent: Enhancing Personalized Education through Dynamic Planning and Retrieval-Augmented Long-Chain Reasoning
Binrong Zhu, Guiran Liu, Nina Jiang
The application of advanced generative artificial intelligence in education is often constrained by the lack of real-time adaptability, personalization, and reliability of the cont…
LLM Assisted Alpha Fairness for 6 GHz WiFi and NR_U Coexistence: An Agentic Orchestrator for Throughput, Energy, and SLA
Qun Wang, Yingzhou Lu, Guiran Liu +2
Unlicensed 6GHz is becoming a primary workhorse for high-capacity access, with Wi-Fi and 5G NR-U competing for the same channels under listen-before-talk (LBT) rules. Operating in…
Graph-Based Spectral Decomposition for Parameter Coordination in Language Model Fine-Tuning
Hanlu Zhang, Yumeng Ma, Shuo Wang +2
This paper proposes a parameter collaborative optimization algorithm for large language models, enhanced with graph spectral analysis. The goal is to improve both fine-tuning effic…
Structured Gradient Guidance for Few-Shot Adaptation in Large Language Models
Hongye Zheng, Yichen Wang, Ray Pan +3
This paper presents a gradient-informed fine-tuning method for large language models under few-shot conditions. The goal is to enhance task adaptability and training stability when…
Context-Guided Dynamic Retrieval for Improving Generation Quality in RAG Models
Jacky He, Guiran Liu, Binrong Zhu +3
This paper focuses on the dynamic optimization of the Retrieval-Augmented Generation (RAG) architecture. It proposes a state-aware dynamic knowledge retrieval mechanism to enhance…
Pre-trained Language Models and Few-shot Learning for Medical Entity Extraction
Xiaokai Wang, Guiran Liu, Binrong Zhu +3
This study proposes a medical entity extraction method based on Transformer to enhance the information extraction capability of medical literature. Considering the professionalism…
A Fine-Tuning Approach for T5 Using Knowledge Graphs to Address Complex Tasks
Xiaoxuan Liao, Binrong Zhu, Jacky He +3
With the development of deep learning technology, large language models have achieved remarkable results in many natural language processing tasks. However, these models still have…
A Hybrid Model for Few-Shot Text Classification Using Transfer and Meta-Learning
Jia Gao, Shuangquan Lyu, Guiran Liu +3
With the continuous development of natural language processing (NLP) technology, text classification tasks have been widely used in multiple application fields. However, obtaining…
Multi-Level Attention and Contrastive Learning for Enhanced Text Classification with an Optimized Transformer
Jia Gao, Guiran Liu, Binrong Zhu +3
This paper studies a text classification algorithm based on an improved Transformer to improve the performance and efficiency of the model in text classification tasks. Aiming at t…
A Review of Intelligent Device Fault Diagnosis Technologies Based on Machine Vision
Guiran Liu, Binrong Zhu
This paper provides a comprehensive review of mechanical equipment fault diagnosis methods, focusing on the advancements brought by Transformer-based models. It details the structu…
Dynamic EEG-fMRI mapping: Revealing the relationship between brain connectivity and cognitive state
Guiran Liu, Binrong Zhu
This study investigated the dynamic connectivity patterns between EEG and fMRI modalities, contributing to our understanding of brain network interactions. By employing a comprehen…
Balancing Innovation and Privacy: Data Security Strategies in Natural Language Processing Applications
Shaobo Liu, Guiran Liu, Binrong Zhu +3
This research addresses privacy protection in Natural Language Processing (NLP) by introducing a novel algorithm based on differential privacy, aimed at safeguarding user data in c…
Graph Neural Network Framework for Sentiment Analysis Using Syntactic Feature
Linxiao Wu, Yuanshuai Luo, Binrong Zhu +3
Amidst the swift evolution of social media platforms and e-commerce ecosystems, the domain of opinion mining has surged as a pivotal area of exploration within natural language pro…