1 citations · 1 across the 6 of their papers we have counts for
8 papers
Trace Sampling 2.0: Code Knowledge Enhanced Span-level Sampling for Distributed Tracing
Yulun Wu, Guangba Yu, Zhihan Jiang +2
Distributed tracing is an essential diagnostic tool in microservice systems, but the sheer volume of traces places a significant burden on backend storage. A common approach to mit…
Next Edit Prediction: Learning to Predict Code Edits from Context and Interaction History
Ruofan Lu, Yintong Huo, Meng Zhang +2
The rapid advancement of large language models (LLMs) has led to the widespread adoption of AI-powered coding assistants integrated into a development environment. On one hand, low…
Exploring Autonomous Agents: A Closer Look at Why They Fail When Completing Tasks
Ruofan Lu, Yichen Li, Yintong Huo
Autonomous agent systems powered by Large Language Models (LLMs) have demonstrated promising capabilities in automating complex tasks. However, current evaluations largely rely on…
CCISolver: End-to-End Detection and Repair of Method-Level Code-Comment Inconsistency
Renyi Zhong, Yintong Huo, Wenwei Gu +6
Comments within code serve as a crucial foundation for software documentation, facilitating developers to communicate and understand the code effectively. However, code-comment inc…
Larger Is Not Always Better: Exploring Small Open-source Language Models in Logging Statement Generation
Renyi Zhong, Yichen Li, Guangba Yu +4
Developers use logging statements to create logs that document system behavior and aid in software maintenance. As such, high-quality logging is essential for effective maintenance…
LLMPrism: Black-box Performance Diagnosis for Production LLM Training Platforms
Zhihan Jiang, Rui Ren, Guangba Yu +8
Large Language Models (LLMs) have brought about revolutionary changes in diverse fields, rendering LLM training of utmost importance for modern enterprises. To meet this demand, mu…