Chiming Duan

Orcid: 0009-0008-4422-6323

According to our database1, Chiming Duan authored at least 13 papers between 2023 and 2025.

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Bibliography

2025
A Survey on Parallel Text Generation: From Parallel Decoding to Diffusion Language Models.
CoRR, August, 2025

ThinkFL: Self-Refining Failure Localization for Microservice Systems via Reinforcement Fine-Tuning.
CoRR, April, 2025

Enhancing Web Service Anomaly Detection via Fine-grained Multi-modal Association and Frequency Domain Analysis.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

AgentFM: Role-Aware Failure Management for Distributed Databases with LLM-Driven Multi-Agents.
Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering, 2025

CLSLog: Collaborating Large and Small Models for Log-based Anomaly Detection.
Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering, 2025

Weakly-Supervised Log-Based Anomaly Detection with Inexact Labels via Multi-Instance Learning.
Proceedings of the 47th IEEE/ACM International Conference on Software Engineering, 2025

Famos: Fault Diagnosis for Microservice Systems Through Effective Multi-Modal Data Fusion.
Proceedings of the 47th IEEE/ACM International Conference on Software Engineering, 2025

EagerLog: Active Learning Enhanced Retrieval Augmented Generation for Log-based Anomaly Detection.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

2024
SOIL: Score Conditioned Diffusion Model for Imbalanced Cloud Failure Prediction.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

LogCAE: An Approach for Log-based Anomaly Detection with Active Learning and Contrastive Learning.
Proceedings of the 35th IEEE International Symposium on Software Reliability Engineering, 2024

LLMeLog: An Approach for Anomaly Detection based on LLM-enriched Log Events.
Proceedings of the 35th IEEE International Symposium on Software Reliability Engineering, 2024

2023
AFALog: A General Augmentation Framework for Log-based Anomaly Detection with Active Learning.
Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering, 2023

AcLog: An Approach to Detecting Anomalies from System Logs with Active Learning.
Proceedings of the IEEE International Conference on Web Services, 2023


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