most citedLarge Language Models for Constructing and Optimizing Machine Learning Workflows: A Survey

3 citations · 3 across the 5 of their papers we have counts for

collaborators

6 papers

cs.SE2025

LLM-SrcLog: Towards Proactive and Unified Log Template Extraction via Large Language Models

Jiaqi Sun, Wei Li, Heng Zhang +4

Log parsing transforms raw logs into structured templates containing constants and variables. It underpins anomaly detection, failure diagnosis, and other AIOps tasks. Current pars…

cs.DC2025

GFS: A Preemption-aware Scheduling Framework for GPU Clusters with Predictive Spot Instance Management

Jiaang Duan, Shenglin Xu, Shiyou Qian +15

The surge in large language models (LLMs) has fundamentally reshaped the landscape of GPU usage patterns, creating an urgent need for more efficient management strategies. While cl…

cs.PF2025

Atys: An Efficient Profiling Framework for Identifying Hotspot Functions in Large-scale Cloud Microservices

Jiaqi Sun, Dingyu Yang, Shiyou Qian +2

To handle the high volume of requests, large-scale services are comprised of thousands of instances deployed in clouds. These services utilize diverse programming languages and are…

cs.CL2025

LKD-KGC: Domain-Specific KG Construction via LLM-driven Knowledge Dependency Parsing

Jiaqi Sun, Shiyou Qian, Zhangchi Han +5

Knowledge Graphs (KGs) structure real-world entities and their relationships into triples, enhancing machine reasoning for various tasks. While domain-specific KGs offer substantia…

cs.LG20243 cited

Large Language Models for Constructing and Optimizing Machine Learning Workflows: A Survey

Yang Gu, Hengyu You, Jian Cao +3

Building effective machine learning (ML) workflows to address complex tasks is a primary focus of the Automatic ML (AutoML) community and a critical step toward achieving artificia…

cs.SE2024

LogLLM: Log-based Anomaly Detection Using Large Language Models

Wei Guan, Jian Cao, Shiyou Qian +2

Software systems often record important runtime information in logs to help with troubleshooting. Log-based anomaly detection has become a key research area that aims to identify s…