Image de couverture de livre

CODEPROMPTZIP: Code-specific Prompt Compression for Retrieval-Augmented Generation in Coding Tasks with LMs

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	He, Pengfei, Wang, Shaowei, Chen, Tse-Hsun
Format:	Preprint
Publié:	2025
Sujets:	Software Engineering
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Evaluating the Effectiveness and Efficiency of Demonstration Retrievers in RAG for Coding Tasks
par: He, Pengfei, et autres
Publié: (2024)

SLICET5: Static Program Slicing using Language Models with Copy Mechanism and Constrained Decoding
par: He, Pengfei, et autres
Publié: (2025)

A Comprehensive Framework for Evaluating API-oriented Code Generation in Large Language Models
par: Wu, Yixi, et autres
Publié: (2024)

When LLMs Lag Behind: Knowledge Conflicts from Evolving APIs in Code Generation
par: Ashik, Ahmed Nusayer, et autres
Publié: (2026)

A Survey of Code Review Benchmarks and Evaluation Practices in Pre-LLM and LLM Era
par: Khan, Taufiqul Islam, et autres
Publié: (2026)

Studying the Impact of Early Test Termination Due to Assertion Failure on Code Coverage and Spectrum-based Fault Localization
par: Uddin, Md. Ashraf, et autres
Publié: (2025)

Towards Better Graph Neural Network-based Fault Localization Through Enhanced Code Representation
par: Rafi, Md Nakhla, et autres
Publié: (2024)

ZS4C: Zero-Shot Synthesis of Compilable Code for Incomplete Code Snippets using LLMs
par: Kabir, Azmain, et autres
Publié: (2024)

Static Program Slicing Using Language Models With Dataflow-Aware Pretraining and Constrained Decoding
par: He, Pengfei, et autres
Publié: (2026)

A Multi-Agent Approach to Fault Localization via Graph-Based Retrieval and Reflexion
par: Rafi, Md Nakhla, et autres
Publié: (2024)

SWE-Refactor: A Repository-Level Benchmark for Real-World LLM-Based Code Refactoring
par: Xu, Yisen, et autres
Publié: (2026)

Evaluating Software Process Models for Multi-Agent Class-Level Code Generation
par: Shafin, Wasique Islam, et autres
Publié: (2025)

Prompt-based Code Completion via Multi-Retrieval Augmented Generation
par: Tan, Hanzhuo, et autres
Publié: (2024)

Identifying Performance-Sensitive Configurations in Software Systems through Code Analysis with LLM Agents
par: Wang, Zehao, et autres
Publié: (2024)

Improving Retrieval-Augmented Code Comment Generation by Retrieving for Generation
par: Lu, Hanzhen, et autres
Publié: (2024)

RepoGenReflex: Enhancing Repository-Level Code Completion with Verbal Reinforcement and Retrieval-Augmented Generation
par: Wang, Jicheng, et autres
Publié: (2024)

Retrieval-Augmented Code Review Comment Generation
par: Hong, Hyunsun, et autres
Publié: (2025)

What to Retrieve for Effective Retrieval-Augmented Code Generation? An Empirical Study and Beyond
par: Gu, Wenchao, et autres
Publié: (2025)

DSTC: Direct Preference Learning with Only Self-Generated Tests and Code to Improve Code LMs
par: Liu, Zhihan, et autres
Publié: (2024)

Preference-Guided Refactored Tuning for Retrieval Augmented Code Generation
par: Gao, Xinyu, et autres
Publié: (2024)

CodeRAG-Bench: Can Retrieval Augment Code Generation?
par: Wang, Zora Zhiruo, et autres
Publié: (2024)

An Empirical Study of Retrieval-Augmented Code Generation: Challenges and Opportunities
par: Yang, Zezhou, et autres
Publié: (2025)

When More Retrieval Hurts: Retrieval-Augmented Code Review Generation
par: Meng, Qianru, et autres
Publié: (2025)

Towards Structured, State-Aware, and Execution-Grounded Reasoning for Software Engineering Agents
par: Tse-Hsun, et autres
Publié: (2026)

RobuNFR: Evaluating the Robustness of Large Language Models on Non-Functional Requirements Aware Code Generation
par: Lin, Feng, et autres
Publié: (2025)

Empowering AIOps: Leveraging Large Language Models for IT Operations Management
par: Vitui, Arthur, et autres
Publié: (2025)

On Rank Aggregating Test Prioritizations
par: Mondal, Shouvick, et autres
Publié: (2024)

Exploring the Security Threats of Retriever Backdoors in Retrieval-Augmented Code Generation
par: Li, Tian, et autres
Publié: (2025)

LLMParser: An Exploratory Study on Using Large Language Models for Log Parsing
par: Ma, Zeyang, et autres
Publié: (2024)

DRAINCODE: Stealthy Energy Consumption Attacks on Retrieval-Augmented Code Generation via Context Poisoning
par: Wang, Yanlin, et autres
Publié: (2026)

ReCode: Improving LLM-based Code Repair with Fine-Grained Retrieval-Augmented Generation
par: Zhao, Yicong, et autres
Publié: (2025)

Are Benchmark Tests Strong Enough? Mutation-Guided Diagnosis and Augmentation of Regression Suites
par: Li, Chenglin, et autres
Publié: (2026)

GraphCodeAgent: Dual Graph-Guided LLM Agent for Retrieval-Augmented Repo-Level Code Generation
par: Li, Jia, et autres
Publié: (2025)

Instructive Code Retriever: Learn from Large Language Model's Feedback for Code Intelligence Tasks
par: Lu, Jiawei, et autres
Publié: (2024)

A Deep Dive into Retrieval-Augmented Generation for Code Completion: Experience on WeChat
par: Yang, Zezhou, et autres
Publié: (2025)

Exploring the Security Threats of Knowledge Base Poisoning in Retrieval-Augmented Code Generation
par: Lin, Bo, et autres
Publié: (2025)

LAURA: Enhancing Code Review Generation with Context-Enriched Retrieval-Augmented LLM
par: Zhang, Yuxin, et autres
Publié: (2025)

Prompt Alchemy: Automatic Prompt Refinement for Enhancing Code Generation
par: Ye, Sixiang, et autres
Publié: (2025)

Less is More: DocString Compression in Code Generation
par: Yang, Guang, et autres
Publié: (2024)

Enhancing Cross-Language Code Translation via Task-Specific Embedding Alignment in Retrieval-Augmented Generation
par: Bhattarai, Manish, et autres
Publié: (2024)