activity
20242026
most citedIndustry Practitioners Perspectives on AI Model Quality: Perceptions, Challenges, and Solutions

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

collaborators

5 papers

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.AI2026

Solvita: Enhancing Large Language Models for Competitive Programming via Agentic Evolution

Han Li, Jinyu Tian, Rili Feng +10

Large language models (LLMs) still struggle with the rigorous reasoning demands of hard competitive programming. While recent multi-agent frameworks attempt to bridge this reliabil…

cs.SE20265 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.CR2025

Backdoors in Code Summarizers: How Bad Is It?

Chenyu Wang, Zhou Yang, Yaniv Harel +1

Code LLMs are increasingly employed in software development. However, studies have shown that they are vulnerable to backdoor attacks: when a trigger (a specific input pattern) app…

cs.SE2024

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…