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20232026
most citedUnveiling Memorization in Code Models

41 citations · 52 across the 7 of their papers we have counts for

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6 papers · 1 filter

cs.SE2026

Fail-Fast, Restart-Smart: Early Failure Prediction and Restart for SWE Agentic Tasks

Chenyu Wang, Yunbo Lyu, Junda He +4

Software engineering (SWE) agents resolve repository-level issues through long trajectories that grow increasingly expensive as context accumulates. Failed runs tend to be longer a…

cs.SE2024★ 5 cited

Industry Practitioners Perspectives on AI Model Quality: Perceptions, Challenges, and Solutions

Chenyu Wang, Zhou Yang, Yunbo Lyu +3

Artificial Intelligence (AI) is now used across nearly every industry, making AI model quality essential for building reliable and trustworthy systems. Historically, correctness ha…

cs.SE2023★ 3 cited

Gotcha! This Model Uses My Code! Evaluating Membership Leakage Risks in Code Models

Zhou Yang, Zhipeng Zhao, Chenyu Wang +4

Given large-scale source code datasets available in open-source projects and advanced large language models, recent code models have been proposed to address a series of critical s…

cs.SE2023★ 1 cited

Are We Ready to Embrace Generative AI for Software Q&A?

Bowen Xu, Thanh-Dat Nguyen, Thanh Le-Cong +8

Stack Overflow, the world's largest software Q&A (SQA) website, is facing a significant traffic drop due to the emergence of generative AI techniques. ChatGPT is banned by Stack Ov…

cs.SE2023★ 41 cited

Unveiling Memorization in Code Models

Zhou Yang, Zhipeng Zhao, Chenyu Wang +4

The availability of large-scale datasets, advanced architectures, and powerful computational resources have led to effective code models that automate diverse software engineering…

cs.SE2023★ 2 cited

What Do Users Ask in Open-Source AI Repositories? An Empirical Study of GitHub Issues

Zhou Yang, Chenyu Wang, Jieke Shi +5

Artificial Intelligence systems, which benefit from the availability of large-scale datasets and increasing computational power, have become effective solutions to various critical…