:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Xue, Zhantong, Ma, Pingchuan, Wang, Zhaoyu, Zhou, Yuguang, Zhang, Xiaoqin, Wang, Shuai, Rahmel, Juergen
Formato:	Preprint
Publicado:	2025
Materias:	Software Engineering
Acceso en línea:	https://arxiv.org/abs/2509.11708
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

ZK-Value: A Practical Zero-Knowledge System for Verifiable Data Valuation
por: Wang, Zhaoyu, et al.
Publicado: (2026)

RepoMark: A Data-Usage Auditing Framework for Code Large Language Models
por: Qu, Wenjie, et al.
Publicado: (2025)

A Survey on Evaluating Large Language Models in Code Generation Tasks
por: Chen, Liguo, et al.
Publicado: (2024)

SkillReducer: Optimizing LLM Agent Skills for Token Efficiency
por: Gao, Yudong, et al.
Publicado: (2026)

Self-planning Code Generation with Large Language Models
por: Jiang, Xue, et al.
Publicado: (2023)

Towards Understanding the Characteristics of Code Generation Errors Made by Large Language Models
por: Wang, Zhijie, et al.
Publicado: (2024)

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

Digging Into the Internal: Causality-Based Analysis of LLM Function Calling
por: Ji, Zhenlan, et al.
Publicado: (2025)

How Multi-Modal LLMs Reshape Visual Deep Learning Testing? A Comprehensive Study Through the Lens of Image Mutation
por: Wang, Liwen, et al.
Publicado: (2024)

Large Language Model Unlearning for Source Code
por: Jiang, Xue, et al.
Publicado: (2025)

On the Evaluation of Large Language Models in Unit Test Generation
por: Yang, Lin, et al.
Publicado: (2024)

CrossPL: Evaluating Large Language Models on Cross Programming Language Code Generation
por: Xiong, Zhanhang, et al.
Publicado: (2025)

SpecEval: Evaluating Code Comprehension in Large Language Models via Program Specifications
por: Ma, Lezhi, et al.
Publicado: (2024)

ClassEval-T: Evaluating Large Language Models in Class-Level Code Translation
por: Xue, Pengyu, et al.
Publicado: (2024)

Optimizing Large Language Model Hyperparameters for Code Generation
por: Arora, Chetan, et al.
Publicado: (2024)

CFCEval: Evaluating Security Aspects in Code Generated by Large Language Models
por: Cheng, Cheng, et al.
Publicado: (2025)

Failure-Aware Enhancements for Large Language Model (LLM) Code Generation: An Empirical Study on Decision Framework
por: Shen, Jianru, et al.
Publicado: (2026)

Task Abstention for Large Language Models in Code Generation
por: Zhou, Yanke, et al.
Publicado: (2026)

Strengthening Programming Comprehension in Large Language Models through Code Generation
por: Ren, Xiaoning, et al.
Publicado: (2025)

Knowledge-Aware Code Generation with Large Language Models
por: Huang, Tao, et al.
Publicado: (2024)

QuanBench: Benchmarking Quantum Code Generation with Large Language Models
por: Guo, Xiaoyu, et al.
Publicado: (2025)

Hotfixing Large Language Models for Code
por: Yang, Zhou, et al.
Publicado: (2024)

Flow2Code: Evaluating Large Language Models for Flowchart-based Code Generation Capability
por: He, Mengliang, et al.
Publicado: (2025)

Evaluating the Impact of Post-Training Quantization on Large Language Models for Code Generation
por: Giagnorio, Alessandro, et al.
Publicado: (2025)

Large Language Models as Test Case Generators: Performance Evaluation and Enhancement
por: Li, Kefan, et al.
Publicado: (2024)

A Hybrid Approach for EMF Code Generation:Code Templates Meet Large Language Models
por: He, Xiao, et al.
Publicado: (2025)

Confidentiality-Preserving Verifiable Business Processes through Zero-Knowledge Proofs
por: Kiesel, Jannis, et al.
Publicado: (2025)

On the Effectiveness of Large Language Models in Domain-Specific Code Generation
por: Gu, Xiaodong, et al.
Publicado: (2023)

Is Your AI-Generated Code Really Safe? Evaluating Large Language Models on Secure Code Generation with CodeSecEval
por: Wang, Jiexin, et al.
Publicado: (2024)

Ecosystem of Large Language Models for Code
por: Yang, Zhou, et al.
Publicado: (2024)

Chain-of-Thought in Neural Code Generation: From and For Lightweight Language Models
por: Yang, Guang, et al.
Publicado: (2023)

A Preliminary Study on the Robustness of Code Generation by Large Language Models
por: Li, Zike, et al.
Publicado: (2025)

Advancing Code Coverage: Incorporating Program Analysis with Large Language Models
por: Yang, Chen, et al.
Publicado: (2024)

ROCODE: Integrating Backtracking Mechanism and Program Analysis in Large Language Models for Code Generation
por: Jiang, Xue, et al.
Publicado: (2024)

Cross-Task Benchmarking and Evaluation of General-Purpose and Code-Specific Large Language Models
por: Das, Gunjan, et al.
Publicado: (2025)

Greening Large Language Models of Code
por: Shi, Jieke, et al.
Publicado: (2023)

Evaluating Generated Commit Messages with Large Language Models
por: Zeng, Qunhong, et al.
Publicado: (2025)

Synergistic Enhancement of Requirement-to-Code Traceability: A Framework Combining Large Language Model based Data Augmentation and an Advanced Encoder
por: Zhang, Jianzhang, et al.
Publicado: (2025)

CodeScore: Evaluating Code Generation by Learning Code Execution
por: Dong, Yihong, et al.
Publicado: (2023)

Automated Proof Generation for Rust Code via Self-Evolution
por: Chen, Tianyu, et al.
Publicado: (2024)