9 citations · 14 across the 16 of their papers we have counts for
9 papers · 1 filter
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…