---
title: "Who cites JuICe: A Large Scale Distantly — 28 citing papers"
description: "28 papers of the Elamur Research library cite «JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code…"
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# Who cites «JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation»

28 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · [← back to «JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation»](https://md.research.elamur.ai/free/en/papers/agashe-2019-juice-large-scale-distantly-supervised/)

1. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
2. [**LEVER: Learning to Verify Language-to-Code Generation with Execution arXiv:2302.08468**Ansong Ni, Srini Iyer, Dragomir Radev, et al.*2023 · 126 citations*](https://md.research.elamur.ai/free/en/papers/ni-2023-lever-learning-verify-language-code/)
3. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
4. **[InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback](https://md.research.elamur.ai/free/en/papers/yang-2023-intercode-standardizing-benchmarking-interactive-coding/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**John Yang, Akshara Prabhakar, Karthik Narasimhan, et al.*2023 · 95 citations*
5. **[Execution-Based Evaluation for Open-Domain Code Generation](https://md.research.elamur.ai/free/en/papers/wang-2023-execution-based-evaluation-open-domain/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiruo Wang, Shuyan Zhou, Daniel Fried, et al.*2023 · 69 citations*
6. **[Natural Language to Code Generation in Interactive Data Science Notebooks](https://md.research.elamur.ai/free/en/papers/yin-2023-natural-language-code-generation-interactive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pengcheng Yin, Wen-Ding Li, Kefan Xiao, et al.*2023 · 63 citations*
7. **[XCodeEval: An Execution-based Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval](https://md.research.elamur.ai/free/en/papers/khan-2024-xcodeeval-execution-based-large-scale/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2024 · 51 citations*
8. [**xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval arXiv:2303.03004**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/khan-2023-xcodeeval-large-scale-multilingual-multitask/)
9. **[L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/ni-2024-l2ceval-evaluating-language-code-generation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ansong Ni, Pengcheng Yin, Yilun Zhao, et al.*2024 · 27 citations*

19 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/agashe-2019-juice-large-scale-distantly-supervised/) — JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation