Copertina

OpenCodeInstruct: A Large-scale Instruction Tuning Dataset for Code LLMs

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ahmad, Wasi Uddin, Ficek, Aleksander, Samadi, Mehrzad, Huang, Jocelyn, Noroozi, Vahid, Majumdar, Somshubra, Ginsburg, Boris
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Software Engineering Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Genetic Instruct: Scaling up Synthetic Generation of Coding Instructions for Large Language Models
di: Majumdar, Somshubra, et al.
Pubblicazione: (2024)

From Output to Evaluation: Does Raw Instruction-Tuned Code LLMs Output Suffice for Fill-in-the-Middle Code Generation?
di: Ahmad, Wasi Uddin, et al.
Pubblicazione: (2025)

Scoring Verifiers: Evaluating Synthetic Verification for Code and Reasoning
di: Ficek, Aleksander, et al.
Pubblicazione: (2025)

OpenCodeReasoning-II: A Simple Test Time Scaling Approach via Self-Critique
di: Ahmad, Wasi Uddin, et al.
Pubblicazione: (2025)

OpenCodeReasoning: Advancing Data Distillation for Competitive Coding
di: Ahmad, Wasi Uddin, et al.
Pubblicazione: (2025)

Scaling Test-Time Compute to Achieve IOI Gold Medal with Open-Weight Models
di: Samadi, Mehrzad, et al.
Pubblicazione: (2025)

From SWE-ZERO to SWE-HERO: Execution-free to Execution-based Fine-tuning for Software Engineering Agents
di: Ludwig, Nikolai, et al.
Pubblicazione: (2026)

Secure-Instruct: An Automated Pipeline for Synthesizing Instruction-Tuning Datasets Using LLMs for Secure Code Generation
di: Li, Junjie, et al.
Pubblicazione: (2025)

InstructCoder: Instruction Tuning Large Language Models for Code Editing
di: Li, Kaixin, et al.
Pubblicazione: (2023)

Instruction Data Generation and Unsupervised Adaptation for Speech Language Models
di: Noroozi, Vahid, et al.
Pubblicazione: (2024)

InverseCoder: Self-improving Instruction-Tuned Code LLMs with Inverse-Instruct
di: Wu, Yutong, et al.
Pubblicazione: (2024)

Stateful Conformer with Cache-based Inference for Streaming Automatic Speech Recognition
di: Noroozi, Vahid, et al.
Pubblicazione: (2023)

Repoformer: Selective Retrieval for Repository-Level Code Completion
di: Wu, Di, et al.
Pubblicazione: (2024)

Learning Generative Selection for Best-of-N
di: Toshniwal, Shubham, et al.
Pubblicazione: (2026)

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code
di: Hossen, Md Imran, et al.
Pubblicazione: (2024)

ASMA-Tune: Unlocking LLMs' Assembly Code Comprehension via Structural-Semantic Instruction Tuning
di: Wang, Xinyi, et al.
Pubblicazione: (2025)

LibEvolutionEval: A Benchmark and Study for Version-Specific Code Generation
di: Kuhar, Sachit, et al.
Pubblicazione: (2024)

SWE-Bench+: Enhanced Coding Benchmark for LLMs
di: Aleithan, Reem, et al.
Pubblicazione: (2024)

ICE-Score: Instructing Large Language Models to Evaluate Code
di: Zhuo, Terry Yue
Pubblicazione: (2023)

The Impact of Large Language Models (LLMs) on Code Review Process
di: Collante, Antonio, et al.
Pubblicazione: (2025)

Turbulence: Systematically and Automatically Testing Instruction-Tuned Large Language Models for Code
di: Honarvar, Shahin, et al.
Pubblicazione: (2023)

AutoCoder: Enhancing Code Large Language Model with \textsc{AIEV-Instruct}
di: Lei, Bin, et al.
Pubblicazione: (2024)

How Do Your Code LLMs Perform? Empowering Code Instruction Tuning with High-Quality Data
di: Wang, Yejie, et al.
Pubblicazione: (2024)

Astraios: Parameter-Efficient Instruction Tuning Code Large Language Models
di: Zhuo, Terry Yue, et al.
Pubblicazione: (2024)

Evaluating Large Language Models for Code Review
di: Cihan, Umut, et al.
Pubblicazione: (2025)

Instruction Tuning for Secure Code Generation
di: He, Jingxuan, et al.
Pubblicazione: (2024)

Magicoder: Empowering Code Generation with OSS-Instruct
di: Wei, Yuxiang, et al.
Pubblicazione: (2023)

Prompt Engineering or Fine-Tuning: An Empirical Assessment of LLMs for Code
di: Shin, Jiho, et al.
Pubblicazione: (2023)

CodeLSI: Leveraging Foundation Models for Automated Code Generation with Low-Rank Optimization and Domain-Specific Instruction Tuning
di: Le, Huy, et al.
Pubblicazione: (2025)

Wild SBOMs: a Large-scale Dataset of Software Bills of Materials from Public Code
di: Soeiro, Luıs, et al.
Pubblicazione: (2025)

An Empirical Study on the Effects of System Prompts in Instruction-Tuned Models for Code Generation
di: Cheng, Zaiyu, et al.
Pubblicazione: (2026)

Edit, But Verify: An Empirical Audit of Instructed Code-Editing Benchmarks
di: Ebrahimi, Amir M., et al.
Pubblicazione: (2026)

LLM Assisted Coding with Metamorphic Specification Mutation Agent
di: Akhond, Mostafijur Rahman, et al.
Pubblicazione: (2025)

Is Vibe Coding the Future? An Empirical Assessment of LLM Generated Codes for Construction Safety
di: Uddin, S M Jamil
Pubblicazione: (2026)

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

SynthCoder: A Synthetical Strategy to Tune LLMs for Code Completion
di: Yu, Dongjun, et al.
Pubblicazione: (2025)

AgentPack: A Dataset of Code Changes, Co-Authored by Agents and Humans
di: Zi, Yangtian, et al.
Pubblicazione: (2025)

WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning
di: Yu, Zhaojian, et al.
Pubblicazione: (2023)

TIT: A Tree-Structured Instruction Tuning Approach for LLM-Based Code Translation
di: Jiang, He, et al.
Pubblicazione: (2025)

Trained Without My Consent: Detecting Code Inclusion In Language Models Trained on Code
di: Majdinasab, Vahid, et al.
Pubblicazione: (2024)