Imagen de Portada

What Makes Good In-context Demonstrations for Code Intelligence Tasks with LLMs?

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Gao, Shuzheng, Wen, Xin-Cheng, Gao, Cuiyun, Wang, Wenxuan, Zhang, Hongyu, Lyu, Michael R.
Formato:	Preprint
Publicado:	2023
Materias:	Software Engineering
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

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

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

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

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

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

RAG or Fine-tuning? A Comparative Study on LCMs-based Code Completion in Industry
por: Wang, Chaozheng, et al.
Publicado: (2025)

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

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

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

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

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

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

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

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

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

Schedule-and-Calibrate: Utility-Guided Multi-Task Reinforcement Learning for Code LLMs
por: Chen, Yujia, et al.
Publicado: (2026)

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

What Makes a Good TODO Comment?
por: Wang, Haoye, et al.
Publicado: (2025)

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

Weakly Supervised Vulnerability Localization via Multiple Instance Learning
por: Gu, Wenchao, et al.
Publicado: (2025)

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

Boosting Vulnerability Detection of LLMs via Curriculum Preference Optimization with Synthetic Reasoning Data
por: Wen, Xin-Cheng, et al.
Publicado: (2025)

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

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

MLLM-Based UI2Code Automation Guided by UI Layout Information
por: Wu, Fan, et al.
Publicado: (2025)

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

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

Repository-Level Graph Representation Learning for Enhanced Security Patch Detection
por: Wen, Xin-Cheng, et al.
Publicado: (2024)

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

Uncovering Weaknesses in Neural Code Generation
por: Lian, Xiaoli, et al.
Publicado: (2024)

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

Stronger, Cheaper and Demonstration-Free Log Parsing with LLMs
por: Xiao, Yi, et al.
Publicado: (2024)

Game Rewards Vulnerabilities: Software Vulnerability Detection with Zero-Sum Game and Prototype Learning
por: Wen, Xin-Cheng, et al.
Publicado: (2024)

The Current Challenges of Software Engineering in the Era of Large Language Models
por: Gao, Cuiyun, et al.
Publicado: (2024)

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

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

Vul-R2: A Reasoning LLM for Automated Vulnerability Repair
por: Wen, Xin-Cheng, et al.
Publicado: (2025)

EvalSVA: Multi-Agent Evaluators for Next-Gen Software Vulnerability Assessment
por: Wen, Xin-Cheng, et al.
Publicado: (2024)

Benchmarking Multimodal LLMs on Code Generation for Complex Interactive Webpages
por: Wu, Fan, et al.
Publicado: (2026)