Cover Image

CodeIF-Bench: Evaluating Instruction-Following Capabilities of Large Language Models in Interactive Code Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Peiding, Zhang, Li, Liu, Fang, Shi, Lin, Li, Minxiao, Shen, Bo, Fu, An
Format:	Preprint
Published:	2025
Subjects:	Software Engineering Artificial Intelligence Programming Languages
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

CodeIF: Benchmarking the Instruction-Following Capabilities of Large Language Models for Code Generation
by: Yan, Kaiwen, et al.
Published: (2025)

EfficientEdit: Accelerating Code Editing via Edit-Oriented Speculative Decoding
by: Wang, Peiding, et al.
Published: (2025)

Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions
by: Cassano, Federico, et al.
Published: (2023)

Steerable Instruction Following Coding Data Synthesis with Actor-Parametric Schema Co-Evolution
by: Huang, Tinglin, et al.
Published: (2026)

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

CodeEditorBench: Evaluating Code Editing Capability of Large Language Models
by: Guo, Jiawei, et al.
Published: (2024)

PerfCodeBench: Benchmarking LLMs for System-Level High-Performance Code Optimization
by: Jing, Huihao, et al.
Published: (2026)

From Effectiveness to Efficiency: Uncovering Linguistic Bias in Large Language Model-based Code Generation
by: Jiang, Weipeng, et al.
Published: (2024)

CodeMind: Evaluating Large Language Models for Code Reasoning
by: Liu, Changshu, et al.
Published: (2024)

JavaBench: A Benchmark of Object-Oriented Code Generation for Evaluating Large Language Models
by: Cao, Jialun, et al.
Published: (2024)

SIMCOPILOT: Evaluating Large Language Models for Copilot-Style Code Generation
by: Jiang, Mingchao, et al.
Published: (2025)

LLMigrate: Transforming "Lazy" Large Language Models into Efficient Source Code Migrators
by: Liu, Yuchen, et al.
Published: (2025)

COBOL-Coder: Domain-Adapted Large Language Models for COBOL Code Generation and Translation
by: Dau, Anh T. V., et al.
Published: (2026)

CodePod: A Language-Agnostic Hierarchical Scoping System for Interactive Development
by: Li, Hebi, et al.
Published: (2023)

Is Functional Correctness Enough to Evaluate Code Language Models? Exploring Diversity of Generated Codes
by: Chon, Heejae, et al.
Published: (2024)

CodeFuse-Query: A Data-Centric Static Code Analysis System for Large-Scale Organizations
by: Xie, Xiaoheng, et al.
Published: (2024)

SWE-QA: Can Language Models Answer Repository-level Code Questions?
by: Peng, Weihan, et al.
Published: (2025)

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators
by: Chou, Jason, et al.
Published: (2025)

Perish or Flourish? A Holistic Evaluation of Large Language Models for Code Generation in Functional Programming
by: Lang, Nguyet-Anh H., et al.
Published: (2026)

Scalable, Validated Code Translation of Entire Projects using Large Language Models
by: Zhang, Hanliang, et al.
Published: (2024)

CodeMEM: AST-Guided Adaptive Memory for Repository-Level Iterative Code Generation
by: Wang, Peiding, et al.
Published: (2026)

EvoCodeBench: An Evolving Code Generation Benchmark with Domain-Specific Evaluations
by: Li, Jia, et al.
Published: (2024)

Evaluating the Generalization Capabilities of Large Language Models on Code Reasoning
by: Yang, Rem, et al.
Published: (2025)

AInsteinBench: Benchmarking Coding Agents on Scientific Repositories
by: Duston, Titouan, et al.
Published: (2025)

Semantic Source Code Segmentation using Small and Large Language Models
by: Dahou, Abdelhalim, et al.
Published: (2025)

AutoBench: Automatic Testbench Generation and Evaluation Using LLMs for HDL Design
by: Qiu, Ruidi, et al.
Published: (2024)

LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code
by: Jain, Naman, et al.
Published: (2024)

HumanEval-XL: A Multilingual Code Generation Benchmark for Cross-lingual Natural Language Generalization
by: Peng, Qiwei, et al.
Published: (2024)

ArtifactsBench: Bridging the Visual-Interactive Gap in LLM Code Generation Evaluation
by: Zhang, Chenchen, et al.
Published: (2025)

Python Symbolic Execution with LLM-powered Code Generation
by: Wang, Wenhan, et al.
Published: (2024)

Language Models for Code Completion: A Practical Evaluation
by: Izadi, Maliheh, et al.
Published: (2024)

Pareto Optimal Code Generation
by: Orlanski, Gabriel, et al.
Published: (2025)

NExT: Teaching Large Language Models to Reason about Code Execution
by: Ni, Ansong, et al.
Published: (2024)

Assessing GPT-4-Vision's Capabilities in UML-Based Code Generation
by: Antal, Gábor, et al.
Published: (2024)

Eliciting Instruction-tuned Code Language Models' Capabilities to Utilize Auxiliary Function for Code Generation
by: Lee, Seonghyeon, et al.
Published: (2024)

Generating Equivalent Representations of Code By A Self-Reflection Approach
by: Li, Jia, et al.
Published: (2024)

Finding Compiler Bugs through Cross-Language Code Generator and Differential Testing
by: Feng, Qiong, et al.
Published: (2025)

Large Language Models for Multilingual Code Intelligence: A Survey
by: Jiang, Chao, et al.
Published: (2026)

Executing as You Generate: Hiding Execution Latency in LLM Code Generation
by: Sun, Zhensu, et al.
Published: (2026)

A Preliminary Study of Multilingual Code Language Models for Code Generation Task Using Translated Benchmarks
by: Dandamudi, Rohit, et al.
Published: (2024)