Cover Image

RAG or Fine-tuning? A Comparative Study on LCMs-based Code Completion in Industry

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Chaozheng, Yang, Zezhou, Gao, Shuzheng, Gao, Cuiyun, Peng, Ting, Huang, Hailiang, Deng, Yuetang, Lyu, Michael
Format:	Preprint
Published:	2025
Subjects:	Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Deep Dive into Retrieval-Augmented Generation for Code Completion: Experience on WeChat
by: Yang, Zezhou, et al.
Published: (2025)

Cascaded Code Editing: Large-Small Model Collaboration for Effective and Efficient Code Editing
by: Wang, Chaozheng, et al.
Published: (2026)

SEER: Enhancing Chain-of-Thought Code Generation through Self-Exploring Deep Reasoning
by: Gao, Shuzheng, et al.
Published: (2025)

Exploring Multi-Lingual Bias of Large Code Models in Code Generation
by: Wang, Chaozheng, et al.
Published: (2024)

Automated Prompt Generation for Code Intelligence: An Empirical study and Experience in WeChat
by: Ji, Kexing, et al.
Published: (2025)

A Systematic Evaluation of Large Code Models in API Suggestion: When, Which, and How
by: Wang, Chaozheng, et al.
Published: (2024)

Search-Based LLMs for Code Optimization
by: Gao, Shuzheng, et al.
Published: (2024)

SR-Eval: Evaluating LLMs on Code Generation under Stepwise Requirement Refinement
by: Zhan, Zexun, et al.
Published: (2025)

Smaller but Better: Self-Paced Knowledge Distillation for Lightweight yet Effective LCMs
by: Chen, Yujia, et al.
Published: (2024)

JSidentify-V2: Leveraging Dynamic Memory Fingerprinting for Mini-Game Plagiarism Detection
by: Li, Zhihao, et al.
Published: (2025)

What Makes Good In-context Demonstrations for Code Intelligence Tasks with LLMs?
by: Gao, Shuzheng, et al.
Published: (2023)

The Prompt Alchemist: Automated LLM-Tailored Prompt Optimization for Test Case Generation
by: Gao, Shuzheng, et al.
Published: (2025)

Deep Learning Based Code Generation Methods: Literature Review
by: Yang, Zezhou, et al.
Published: (2023)

Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models
by: Gao, Shuzheng, et al.
Published: (2024)

JSProtect: A Scalable Obfuscation Framework for Mini-Games in WeChat
by: Li, Zhihao, et al.
Published: (2025)

Empirical Study of Code Large Language Models for Binary Security Patch Detection
by: Li, Qingyuan, et al.
Published: (2025)

An Empirical Study of Knowledge Distillation for Code Understanding Tasks
by: Wang, Ruiqi, et al.
Published: (2025)

ComplexCodeEval: A Benchmark for Evaluating Large Code Models on More Complex Code
by: Feng, Jia, et al.
Published: (2024)

Bridge and Hint: Extending Pre-trained Language Models for Long-Range Code
by: Chen, Yujia, et al.
Published: (2024)

SCALE: Constructing Structured Natural Language Comment Trees for Software Vulnerability Detection
by: Wen, Xin-Cheng, et al.
Published: (2024)

An Empirical Study of Retrieval-Augmented Code Generation: Challenges and Opportunities
by: Yang, Zezhou, et al.
Published: (2025)

SPVR: syntax-to-prompt vulnerability repair based on large language models
by: Wang, Ruoke, et al.
Published: (2024)

Integrating Rules and Semantics for LLM-Based C-to-Rust Translation
by: Luo, Feng, et al.
Published: (2025)

A Roadmap on Modern Code Review: Challenges and Opportunities
by: Yang, Zezhou, et al.
Published: (2024)

A Closer Look into Transformer-Based Code Intelligence Through Code Transformation: Challenges and Opportunities
by: Li, Yaoxian, et al.
Published: (2022)

TREAT: A Code LLMs Trustworthiness / Reliability Evaluation and Testing Framework
by: Gao, Shuzheng, et al.
Published: (2025)

Less is More? An Empirical Study on Configuration Issues in Python PyPI Ecosystem
by: Peng, Yun, et al.
Published: (2023)

SPENCER: Self-Adaptive Model Distillation for Efficient Code Retrieval
by: Gu, Wenchao, et al.
Published: (2025)

Benchmarking LLMs for Fine-Grained Code Review with Enriched Context in Practice
by: Hu, Ruida, et al.
Published: (2025)

On the Effectiveness of Context Compression for Repository-Level Tasks: An Empirical Investigation
by: Feng, Jia, et al.
Published: (2026)

BDiff: Block-aware and Accurate Text-based Code Differencing
by: Lu, Yao, et al.
Published: (2025)

GrepRAG: An Empirical Study and Optimization of Grep-Like Retrieval for Code Completion
by: Wang, Baoyi, et al.
Published: (2026)

RepoMasterEval: Evaluating Code Completion via Real-World Repositories
by: Wu, Qinyun, et al.
Published: (2024)

CodeCrash: Exposing LLM Fragility to Misleading Natural Language in Code Reasoning
by: Lam, Man Ho, et al.
Published: (2025)

CodeVisionary: An Agent-based Framework for Evaluating Large Language Models in Code Generation
by: Wang, Xinchen, et al.
Published: (2025)

Dependency-Guided Repository-Level C-to-Rust Translation with Reinforcement Alignment
by: Feng, Jia, et al.
Published: (2026)

When Shared Worlds Break: Demystifying Defects in Multi-User Extended Reality Software Systems
by: Li, Shuqing, et al.
Published: (2025)

A Real-World Benchmark for Evaluating Fine-Grained Issue Solving Capabilities of Large Language Models
by: Hu, Ruida, et al.
Published: (2024)

Towards Mitigating API Hallucination in Code Generated by LLMs with Hierarchical Dependency Aware
by: Chen, Yujia, et al.
Published: (2025)

Position Paper: Programming Language Techniques for Bridging LLM Code Generation Semantic Gaps
by: Du, Yalong, et al.
Published: (2025)