6 papers
SodaMem: Evidence-Grounded Temporal Graph Memory for LLM Agents
Fengrong Wan, Chengcan Wu, Ningtao Lyu
Large language model (LLM) agents that assist users over weeks of conversation must remember what is currently true, not merely what was once said. Flat RAG diaries and Markdown lo…
Improving Pattern Recognition of Scheduling Anomalies through Structure-Aware and Semantically-Enhanced Graphs
Ning Lyu, Junjie Jiang, Lu Chang +3
This paper proposes a structure-aware driven scheduling graph modeling method to improve the accuracy and representation capability of anomaly identification in scheduling behavior…
Advancing Text Classification with Large Language Models and Neural Attention Mechanisms
Ning Lyu, Yuxi Wang, Feng Chen +1
This study proposes a text classification algorithm based on large language models, aiming to address the limitations of traditional methods in capturing long-range dependencies, u…
Knowledge-Augmented Large Language Model Agents for Explainable Financial Decision-Making
Qingyuan Zhang, Yuxi Wang, Cancan Hua +2
This study investigates an explainable reasoning method for financial decision-making based on knowledge-enhanced large language model agents. To address the limitations of traditi…
Graph Neural AI with Temporal Dynamics for Comprehensive Anomaly Detection in Microservices
Qingyuan Zhang, Ning Lyu, Le Liu +3
This study addresses the problem of anomaly detection and root cause tracing in microservice architectures and proposes a unified framework that combines graph neural networks with…
Multi-Objective Adaptive Rate Limiting in Microservices Using Deep Reinforcement Learning
Ning Lyu, Yuxi Wang, Ziyu Cheng +2
As cloud computing and microservice architectures become increasingly prevalent, API rate limiting has emerged as a critical mechanism for ensuring system stability and service qua…