109 citations · 182 across the 20 of their papers we have counts for
6 papers · 1 filter
CARET: Training-Free Test-Time Scaling for Repository-Level Code Completion
Jiajie Wang, Yutong Zhao, Kebin Peng +3
Retrieval-augmented generation (RAG) dominates repository-level code completion: it retrieves cross-file context (R), then decodes one greedy completion (G). Existing work mainly f…
Ensemble-Based Uncertainty Estimation for Code Correctness Estimation
Yunxiang Wei, Tianlin Li, Yuwei Zheng +6
Large language models (LLMs) have demonstrated remarkable capabilities in generating programs from natural language descriptions, yet ensuring their correctness without an external…
CodeChemist: Test-Time Scaling for Low-Resource Code Generation via Functional Knowledge Transfer
Kaixin Wang, Tianlin Li, Xiaoyu Zhang +6
Code Large Language Models (CodeLLMs) have been widely adopted for Natural Language to Programming Language code generation, powering applications with large user bases. Their perf…
From Context to Intent: Reasoning-Guided Function-Level Code Completion
Yanzhou Li, Tianlin Li, Yiran Zhang +4
The growing capabilities of Large Language Models (LLMs) have led to their widespread adoption for function completion within code repositories. Recent studies on such tasks show p…
BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks
Yisong Xiao, Aishan Liu, Xinwei Zhang +6
Pre-trained large deep learning models are now serving as the dominant component for downstream middleware users and have revolutionized the learning paradigm, replacing the tradit…
Latent Imitator: Generating Natural Individual Discriminatory Instances for Black-Box Fairness Testing
Yisong Xiao, Aishan Liu, Tianlin Li +1
Machine learning (ML) systems have achieved remarkable performance across a wide area of applications. However, they frequently exhibit unfair behaviors in sensitive application do…