mlsanityData to 7 Oct 2026

AutoCoder: Enhancing Code Large Language Model with textscAIEV-Instruct

arXiv 2405.14906 ↗First posted 23 May 2024cs.SE cs.AIcited by 8

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Abstract (arXiv)

We introduce AutoCoder, the first Large Language Model to surpass GPT-4 Turbo (April 2024) and GPT-4o in pass@1 on the Human Eval benchmark test (90.9% vs. 90.2%). In addition, AutoCoder offers a more versatile code interpreter compared to GPT-4 Turbo and GPT-4o. It's code interpreter can install external packages instead of limiting to built-in packages. AutoCoder's training data is a multi-turn dialogue dataset created by a system combining agent interaction and external code execution verification, a method we term textbftextscAIEV-Instruct (Instruction Tuning with Agent-Interaction and Execution-Verified). Compared to previous large-scale code dataset generation methods, textscAIEV-Instruct reduces dependence on proprietary large models and provides execution-validated code dataset. The code and the demo video is available in urlhttps://github.com/bin123apple/AutoCoder.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 20 of its 29 references that are in the map. First posted on arXiv 23 May 2024.

Builds on

20 of 29 references.

References · 20

  1. 2022Training language models to follow instructions with human feedbackcited by 15,712
  2. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  3. 2021Program Synthesis with Large Language Modelscited by 3,509
  4. 2022Training Compute-Optimal Large Language Modelscited by 2,927
  5. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,674
  6. 2023Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generationcited by 1,332
  7. 2020Making Pre-trained Language Models Better Few-shot Learnerscited by 1,255
  8. 2023A Survey on Evaluation of Large Language Modelscited by 1,227
  9. 2024DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligencecited by 1,154
  10. 2023WizardCoder: Empowering Code Large Language Models with Evol-Instructcited by 728
  11. 2022DS-1000: A Natural and Reliable Benchmark for Data Science Code Generationcited by 442
  12. 2024InternLM2 Technical Reportcited by 391
8 more
  1. 2024OpenCodeInterpreter: Integrating Code Generation with Execution and Refinementcited by 242
  2. 2022MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generationcited by 132
  3. 2023InferFix: End-to-End Program Repair with LLMscited by 113
  4. 2023How Novices Use LLM-Based Code Generators to Solve CS1 Coding Tasks in a Self-Paced Learning Environmentcited by 55
  5. 2023Large Language Model-Aware In-Context Learning for Code Generationcited by 42
  6. 2021In-IDE Code Generation from Natural Language: Promise and Challengescited by 41
  7. 2023A Comparative Study of Code Generation using ChatGPT 3.5 across 10 Programming Languagescited by 11
  8. 2024DevEval: Evaluating Code Generation in Practical Software Projectscited by 9

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Cited by year

Citing papers per year: 2024: 4; 2025: 4.

8 papers.

  1. 2025Large Language Model Agent: A Survey on Methodology, Applications and Challengescited by 194
  2. 2024Large Language Model-Based Agents for Software Engineering: A Surveycited by 173
  3. 2024CraftRTL: High-quality Synthetic Data Generation for Verilog Code Models with Correct-by-Construction Non-Textual Representations and Targeted Code Repaircited by 41
  4. 2024API-guided Dataset Synthesis to Finetune Large Code Modelscited by 11
  5. 2025How Many Code and Test Cases Are Enough? Evaluating Test Cases Generation from a Binary-Matrix Perspectivecited by 4
  6. 2025Designing LLM-based Multi-Agent Systems for Software Engineering Tasks: Quality Attributes, Design Patterns and Rationalecited by 3
  7. 2025Exploring Large Language Models for Translating Romanian Computational Problems into Englishcited by 2
  8. 2024Evaluating the Performance of Large Language Models in Competitive Programming: A Multi-Year, Multi-Grade Analysiscited by 0