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Recommending Root-Cause and Mitigation Steps for Cloud Incidents Using Large Language Models

2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), 2023, p.1737-1749

2023

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ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection

Proceedings of the VLDB Endowment, 2023-11, Vol.17 (3), p.359-372

2023

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An Intelligent Framework for Timely, Accurate, and Comprehensive Cloud Incident Detection

Operating systems review, 2022-06, Vol.56 (1), p.1-7

2022

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Xpert: Empowering Incident Management with Query Recommendations via Large Language Models

2024 IEEE/ACM 46th International Conference on Software Engineering (ICSE), 2024, p.1-13

2024

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UniLog: Automatic Logging via LLM and In-Context Learning

2024 IEEE/ACM 46th International Conference on Software Engineering (ICSE), 2024, p.1-12

2024

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CONAN: Diagnosing Batch Failures for Cloud Systems

2023 IEEE/ACM 45th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP), 2023, p.138-149

2023

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How Different are the Cloud Workloads? Characterizing Large-Scale Private and Public Cloud Workloads

2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2023, p.522-530

2023

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CODEC: Cost-Effective Duration Prediction System for Deadline Scheduling in the Cloud

2023 IEEE 34th International Symposium on Software Reliability Engineering (ISSRE), 2023, p.298-308

2023

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TraceArk: Towards Actionable Performance Anomaly Alerting for Online Service Systems

2023 IEEE/ACM 45th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP), 2023, p.258-269

2023

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Incident-Aware Duplicate Ticket Aggregation for Cloud Systems

2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), 2023, p.2299-2311

2023

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UniParser: A Unified Log Parser for Heterogeneous Log Data

Proceedings of the ACM Web Conference 2022, 2022, p.1893-1901

2022

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X-Lifecycle Learning for Cloud Incident Management using LLMs

Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024, p.417-428

2024

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Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4

Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024, p.266-277

2024

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Exploring LLM-Based Agents for Root Cause Analysis

Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024, p.208-219

2024

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LM-PACE: Confidence Estimation by Large Language Models for Effective Root Causing of Cloud Incidents

Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024, p.388-398

2024

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Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach

2024 IEEE/ACM 46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP), 2024, p.381-391

2024

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Dependency Aware Incident Linking in Large Cloud Systems

Companion Proceedings of the ACM Web Conference 2024, 2024, p.141-150

2024

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STEAM: Observability-Preserving Trace Sampling

Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023, p.1750-1761

2023

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Robust Positive-Unlabeled Learning via Noise Negative Sample Self-correction

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023, p.3663-3673

2023

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Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach

Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022, p.2169-2179

2022

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Pre-trained KPI Anomaly Detection Model Through Disentangled Transformer

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024, p.6190-6201

2024

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Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective

Proceedings of the ACM Web Conference 2024, 2024, p.3096-3105

2024

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Assess and Summarize: Improve Outage Understanding with Large Language Models

Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023, p.1657-1668

2023

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MonitorAssistant: Simplifying Cloud Service Monitoring via Large Language Models

Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024, p.38-49

2024

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Automatic Root Cause Analysis via Large Language Models for Cloud Incidents

Proceedings of the Nineteenth European Conference on Computer Systems, 2024, p.674-688

2024

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Recommending Root-Cause and Mitigation Steps for Cloud Incidents Using Large Language Models

ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection

An Intelligent Framework for Timely, Accurate, and Comprehensive Cloud Incident Detection

Xpert: Empowering Incident Management with Query Recommendations via Large Language Models

UniLog: Automatic Logging via LLM and In-Context Learning

CONAN: Diagnosing Batch Failures for Cloud Systems

How Different are the Cloud Workloads? Characterizing Large-Scale Private and Public Cloud Workloads

CODEC: Cost-Effective Duration Prediction System for Deadline Scheduling in the Cloud

TraceArk: Towards Actionable Performance Anomaly Alerting for Online Service Systems

Incident-Aware Duplicate Ticket Aggregation for Cloud Systems

UniParser: A Unified Log Parser for Heterogeneous Log Data

X-Lifecycle Learning for Cloud Incident Management using LLMs

Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4

Exploring LLM-Based Agents for Root Cause Analysis

LM-PACE: Confidence Estimation by Large Language Models for Effective Root Causing of Cloud Incidents

Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach

Dependency Aware Incident Linking in Large Cloud Systems

STEAM: Observability-Preserving Trace Sampling

Robust Positive-Unlabeled Learning via Noise Negative Sample Self-correction

Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach

Pre-trained KPI Anomaly Detection Model Through Disentangled Transformer

Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective

Assess and Summarize: Improve Outage Understanding with Large Language Models

MonitorAssistant: Simplifying Cloud Service Monitoring via Large Language Models

Automatic Root Cause Analysis via Large Language Models for Cloud Incidents

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