mlsanityData to 7 Oct 2026

AVATAR: A Parallel Corpus for Java-Python Program Translation

arXiv 2108.11590 ↗First posted 26 Aug 2021cs.SE cs.CLcited by 59

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Abstract (arXiv)

Program translation refers to migrating source code from one programming language to another. It has tremendous practical value in software development, as porting software across languages is time-consuming and costly. Automating program translation is of paramount importance in software migration, and recently researchers explored unsupervised approaches due to the unavailability of parallel corpora. However, the availability of pre-trained language models for programming languages enables supervised fine-tuning with a small number of labeled examples. Therefore, we present AVATAR, a collection of 9,515 programming problems and their solutions written in two popular languages, Java and Python. AVATAR is collected from competitive programming sites, online platforms, and open-source repositories. Furthermore, AVATAR includes unit tests for 250 examples to facilitate functional correctness evaluation. We benchmark several pre-trained language models fine-tuned on AVATAR. Experiment results show that the models lack in generating functionally accurate code.

Key facts. Cited by 59 papers in the map (data through 7 Oct 2026). Builds on 15 of its 31 references that are in the map. First posted on arXiv 26 Aug 2021.

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15 of 31 references.

References · 15

  1. 2017Attention Is All You Needcited by 59,932
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3 more
  1. 2020A Transformer-based Approach for Source Code Summarizationcited by 129
  2. 2018Tree-to-tree Neural Networks for Program Translationcited by 93
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 6; 2023: 9; 2024: 19; 2025: 18; 2026: 5.

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  1. 2024CRUXEval: A Benchmark for Code Reasoning, Understanding and Executioncited by 294
  2. 2022Multi-lingual Evaluation of Code Generation Modelscited by 158
  3. 2024Granite Code Models: A Family of Open Foundation Models for Code Intelligencecited by 116
  4. 2024EffiBench: Benchmarking the Efficiency of Automatically Generated Codecited by 62
  5. 2024SelfCodeAlign: Self-Alignment for Code Generationcited by 61
  6. 2025OpenCodeInstruct: A Large-scale Instruction Tuning Dataset for Code LLMscited by 57
  7. 2023CodeTransOcean: A Comprehensive Multilingual Benchmark for Code Translationcited by 55
  8. 2022XLCoST: A Benchmark Dataset for Cross-lingual Code Intelligencecited by 54
  9. 2022NatGen: Generative pre-training by "Naturalizing" source codecited by 53
  10. 2023Bias Testing and Mitigation in LLM-based Code Generationcited by 53
  11. 2023xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrievalcited by 46
  12. 2024TDD-Bench Verified: Can LLMs Generate Tests for Issues Before They Get Resolved?cited by 32
38 more
  1. 2024CRUXEval-X: A Benchmark for Multilingual Code Reasoning, Understanding and Executioncited by 31
  2. 2024CodeMind: Evaluating Large Language Models for Code Reasoningcited by 30
  3. 2023SLaDe: A Portable Small Language Model Decompiler for Optimized Assemblycited by 28
  4. 2024EffiLearner: Enhancing Efficiency of Generated Code via Self-Optimizationcited by 28
  5. 2024AlphaTrans: A Neuro-Symbolic Compositional Approach for Repository-Level Code Translation and Validationcited by 28
  6. 2022Probing Pretrained Models of Source Codecited by 26
  7. 2024MHPP: Exploring the Capabilities and Limitations of Language Models Beyond Basic Code Generationcited by 25
  8. 2025EffiBench-X: A Multi-Language Benchmark for Measuring Efficiency of LLM-Generated Codecited by 24
  9. 2023Deep Learning for Code Intelligence: Survey, Benchmark and Toolkitcited by 22
  10. 2024CodeEditorBench: Evaluating Code Editing Capability of Large Language Modelscited by 22
  11. 2023CoTran: An LLM-based Code Translator using Reinforcement Learning with Feedback from Compiler and Symbolic Executioncited by 21
  12. 2024RepoTransBench: A Real-World Multilingual Benchmark for Repository-Level Code Translationcited by 21
  13. 2024Rectifier: Code Translation with Corrector via LLMscited by 20
  14. 2024Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generationcited by 19
  15. 2022FixEval: Execution-based Evaluation of Program Fixes for Programming Problemscited by 17
  16. 2024EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuningcited by 15
  17. 2025A Comprehensive Survey on Benchmarks and Solutions in Software Engineering of LLM-Empowered Agentic Systemcited by 15
  18. 2024VersiCode: Towards Version-controllable Code Generationcited by 14
  19. 2026Seeing is Coding: On the Effectiveness of Vision Language Models in Code Understandingcited by 13
  20. 2022Summarize and Generate to Back-translate: Unsupervised Translation of Programming Languagescited by 12
  21. 2025Enhancing LLM Performance Through Debate: An Empirical Study on Multi-Agent Debate for Coding Taskscited by 11
  22. 2023CodeBPE: Investigating Subtokenization Options for Large Language Model Pretraining on Source Codecited by 9
  23. 2023Data Augmentation for Code Translation with Comparable Corpora and Multiple Referencescited by 9
  24. 2024TransAgent: Enhancing LLM-Based Code Translation via Fine-Grained Execution Alignmentcited by 7
  25. 2024SABER: Model-agnostic Backdoor Attack on Chain-of-Thought in Neural Code Generationcited by 7
  26. 2025A Tool for In-depth Analysis of Code Execution Reasoning of Large Language Modelscited by 6
  27. 2025Large Language Models are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Taskscited by 6
  28. 2025Function-to-Style Guidance of LLMs for Code Translationcited by 4
  29. 2024Structured Code Representations Enable Data-Efficient Adaptation of Code Language Modelscited by 3
  30. 2025Skeleton-Guided-Translation: A Benchmarking Framework for Code Repository Translation with Fine-Grained Quality Evaluationcited by 3
  31. 2025Benchmarking AI Models in Software Engineering: A Review, Search Tool, and Unified Approach for Elevating Benchmark Qualitycited by 3
  32. 2025Post-Incorporating Code Structural Knowledge into Pretrained Models via ICL for Code Translationcited by 3
  33. 2025On The Role of Pretrained Language Models in General-Purpose Text Embeddings: A Surveycited by 3
  34. 2025Evaluating Code Reasoning Abilities of Large Language Models Under Real-World Settingscited by 3
  35. 2025TokDrift: When LLM Speaks in Subwords but Code Speaks in Grammarcited by 2
  36. 2021Using Document Similarity Methods to create Parallel Datasets for Code Translationcited by 1
  37. 2023SUT: Active Defects Probing for Transcompiler Modelscited by 1
  38. 2025Collaboration is all you need: LLM Assisted Safe Code Translationcited by 1

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