8 citations · 16 across the 18 of their papers we have counts for
7 papers · 1 filter
A Systematic Evaluation of Large Code Models in API Suggestion: When, Which, and How
Chaozheng Wang, Shuzheng Gao, Cuiyun Gao +4
API suggestion is a critical task in modern software development, assisting programmers by predicting and recommending third-party APIs based on the current context. Recent advance…
ComplexCodeEval: A Benchmark for Evaluating Large Code Models on More Complex Code
Jia Feng, Jiachen Liu, Cuiyun Gao +4
In recent years, the application of large language models (LLMs) to code-related tasks has gained significant attention. However, existing evaluation benchmarks often focus on limi…
Search-Based LLMs for Code Optimization
Shuzheng Gao, Cuiyun Gao, Wenchao Gu +1
The code written by developers usually suffers from efficiency problems and contain various performance bugs. These inefficiencies necessitate the research of automated refactoring…
RepoMasterEval: Evaluating Code Completion via Real-World Repositories
Qinyun Wu, Chao Peng, Pengfei Gao +9
With the growing reliance on automated code completion tools in software development, the need for comprehensive evaluation benchmarks has become critical. Existing benchmarks focu…
SPVR: syntax-to-prompt vulnerability repair based on large language models
Ruoke Wang, Zongjie Li, Cuiyun Gao +3
Purpose: In the field of vulnerability repair, previous research has leveraged pretrained models and LLM-based prompt engineering, among which LLM-based approaches show better gene…
Exploring Multi-Lingual Bias of Large Code Models in Code Generation
Chaozheng Wang, Zongjie Li, Cuiyun Gao +6
Code generation aims to synthesize code and fulfill functional requirements based on natural language (NL) specifications, which can greatly improve development efficiency. In the…
XMoE: Sparse Models with Fine-grained and Adaptive Expert Selection
Yuanhang Yang, Shiyi Qi, Wenchao Gu +3
Sparse models, including sparse Mixture-of-Experts (MoE) models, have emerged as an effective approach for scaling Transformer models. However, they often suffer from computational…