18 citations · 18 across the 5 of their papers we have counts for
7 papers
ERSkill: Evolving for Skill-Guided Adaptive Memory Retrieval
Haolong Chen, Liang Zhang, Zhuo Li +2
While Large Language Model (LLM) agents increasingly rely on long-term memory for persistent interactions, the retrieval mechanisms governing this memory are rarely treated as evol…
Error-Aware Reverse Auction Mechanism for Large Language Model Routing
Haolong Chen, Zhengyuan Xin, Liang Zhang +2
Routing each query to a cost-effective large language model (LLM) is critical for balancing quality and cost, yet most routers rely on a centralized task center to predict model pe…
QoEReasoner: An Agentic Reasoning Framework for Automated and Explainable QoE Diagnosis in RANs
Qizhe Li, Haolong Chen, Shan Dai +5
Diagnosing Quality-of-Experience (QoE) degradations in operational Radio Access Networks (RANs) is a critical but notoriously complex task, traditionally requiring labor-intensive…
DK-Root: A Joint Data-and-Knowledge-Driven Framework for Root Cause Analysis of QoE Degradations in Mobile Networks
Qizhe Li, Haolong Chen, Jiansheng Li +7
Diagnosing the root causes of Quality of Experience (QoE) degradations in operational mobile networks is challenging due to complex cross-layer interactions among kernel performanc…
STM3: Mixture of Multiscale Mamba for Long-Term Spatio-Temporal Time-Series Prediction
Haolong Chen, Liang Zhang, Zhengyuan Xin +1
Recently, spatio-temporal time-series prediction has developed rapidly, yet existing deep learning methods struggle with learning complex long-term spatio-temporal dependencies eff…
First Token Probability Guided RAG for Telecom Question Answering
Tingwei Chen, Jiayi Chen, Zijian Zhao +3
Large Language Models (LLMs) have garnered significant attention for their impressive general-purpose capabilities. For applications requiring intricate domain knowledge, Retrieval…
An overview of domain-specific foundation model: key technologies, applications and challenges
Haolong Chen, Hanzhi Chen, Zijian Zhao +6
The impressive performance of ChatGPT and other foundation-model-based products in human language understanding has prompted both academia and industry to explore how these models…