---
title: "Who cites Neel Sundaresan — 207 papers of our library"
description: "207 papers of the Elamur Research library cite the works of Neel Sundaresan, found in their bibliographies; the most cited first."
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---
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# Who cites Neel Sundaresan

223 citations of their works from 207 papers of our library (of the 149,439 whose bibliographies we read) · 50 with a page here, the most cited first · [← Neel Sundaresan](https://md.research.elamur.ai/free/en/authors/neel-sundaresan/)

1. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,160 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
2. [**Evaluating Large Language Models Trained on Code arXiv:2107.03374**Mark Chen, Jerry Tworek, Heewoo Jun, et al.*2021 · 2,659 citations*](https://md.research.elamur.ai/free/en/papers/chen-2021-evaluating-large-language-models-trained/)
3. **[Competition-Level Code Generation with AlphaCode](https://md.research.elamur.ai/free/en/papers/li-2022-competition-level-code-generation-alphacode/) [Science](https://md.research.elamur.ai/free/en/venues/science/)**Yujia Li, David Choi, Junyoung Chung, et al.*2022 · 1,564 citations*
4. [**Code Llama: Open Foundation Models for Code arXiv:2308.12950**Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.*2024 · 1,430 citations*](https://md.research.elamur.ai/free/en/papers/roziere-2024-code-llama-open-foundation-models/)
5. [**Program Synthesis with Large Language Models arXiv:2108.07732**Jacob Austin, Augustus Odena, Maxwell Nye, et al.*2021 · 1,192 citations*](https://md.research.elamur.ai/free/en/papers/austin-2021-program-synthesis-large-language-models/)
6. **[Unified Pre-training for Program Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ahmad-2021-unified-pre-training-program-understanding/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, et al.*2021 · 750 citations*
7. **[Security and Privacy Challenges of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/das-2024-security-privacy-challenges-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu*2024 · 424 citations*
8. **[A Survey on Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*
9. [**Text and Code Embeddings by Contrastive Pre-Training arXiv:2201.10005**Arvind Neelakantan, Tao Xu, Raul Puri, et al.*2022 · 323 citations*](https://md.research.elamur.ai/free/en/papers/neelakantan-2022-text-code-embeddings-contrastive-pre/)
10. **[CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/le-2022-coderl-mastering-code-generation-through/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hung Le, Yue Wang, Akhilesh Deepak Gotmare, et al.*2022 · 297 citations*
11. **[Retrieval Augmented Code Generation and Summarization](https://md.research.elamur.ai/free/en/papers/parvez-2021-retrieval-augmented-code-generation-summarization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Rizwan Parvez, Wasi Ahmad, Saikat Chakraborty, et al.*2021 · 193 citations*
12. [**BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions arXiv:2406.15877**Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.*2024 · 176 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-bigcodebench-benchmarking-code-generation-diverse/)
13. **[ReACC: A Retrieval-Augmented Code Completion Framework](https://md.research.elamur.ai/free/en/papers/lu-2022-reacc-retrieval-augmented-code-completion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuai Lu, Nan Duan, Hojae Han, et al.*2022 · 125 citations*
14. **[Can Language Models Solve Graph Problems in Natural Language?](https://md.research.elamur.ai/free/en/papers/wang-2023-language-models-solve-graph-problems/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Heng Wang, Shangbin Feng, Tianxing He, et al.*2023 · 124 citations*
15. [**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/)
16. **[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*
17. [**AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation arXiv:2312.13010**Dong Huang, Jie M.Zhang, Michael Luck, et al.*2023 · 90 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-agentcoder-multi-agent-based/)
18. [**Planning with Large Language Models for Code Generation arXiv:2303.05510**Shun Zhang, Zhenfang Chen, Yikang Shen, et al.*2023 · 90 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-planning-large-language-models-code/)
19. [**MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation arXiv:2208.08227**Federico Cassano, John Gouwar, Daniel Nguyen, et al.*2022 · 88 citations*](https://md.research.elamur.ai/free/en/papers/cassano-2022-multipl-e-scalable-extensible-approach/)
20. [**Multi-lingual Evaluation of Code Generation Models arXiv:2210.14868**Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, et al.*2022 · 86 citations*](https://md.research.elamur.ai/free/en/papers/athiwaratkun-2022-multi-lingual-evaluation-code-generation/)
21. [**RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning arXiv:2410.02089**Jonas Gehring, Kunhao Zheng, Jade Copet, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/gehring-2024-rlef-grounding-code-llms-execution/)
22. [**PanGu-Coder: Program Synthesis with Function-Level Language Modeling arXiv:2207.11280**Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, et al.*2022 · 49 citations*](https://md.research.elamur.ai/free/en/papers/christopoulou-2022-pangu-coder-program-synthesis/)
23. **[CoCoMIC: Code Completion by Jointly Modeling In-file and Cross-file Context](https://md.research.elamur.ai/free/en/papers/ding-2024-cocomic-code-completion-jointly-modeling/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yangruibo Ding, Zijian Wang, Wasi Ahmad, et al.*2024 · 45 citations*
24. [**Leveraging Automated Unit Tests for Unsupervised Code Translation arXiv:2110.06773**Baptiste Roziere, Jie M. Zhang, Francois Charton, et al.*2022 · 40 citations*](https://md.research.elamur.ai/free/en/papers/roziere-2022-leveraging-automated-unit-tests-unsupervised/)
25. **[Fault-Aware Neural Code Rankers](https://md.research.elamur.ai/free/en/papers/inala-2022-fault-aware-neural-code-rankers/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jeevana Priya Inala, Chenglong Wang, Mei Yang, et al.*2022 · 39 citations*
26. **[Code Execution with Pre-trained Language Models](https://md.research.elamur.ai/free/en/papers/liu-2023-code-execution-pre-trained-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenxiao Liu, Shuai Lu, Weizhu Chen, et al.*2023 · 38 citations*
27. [**ERNIE-Code: Beyond English-Centric Cross-lingual Pretraining for Programming Languages arXiv:2212.06742**Yekun Chai, Shuohuan Wang, Chao Pang, et al.*2022 · 32 citations*](https://md.research.elamur.ai/free/en/papers/chai-2022-ernie-code-english-centric/)
28. [**Measuring The Impact Of Programming Language Distribution arXiv:2302.01973**Gabriel Orlanski, Kefan Xiao, Xavier Garcia, et al.*2023 · 22 citations*](https://md.research.elamur.ai/free/en/papers/orlanski-2023-measuring-impact-programming-language-distribution/)
29. [**CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction arXiv:2502.07316**Junlong Li, Daya Guo, Dejian Yang, et al.*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-codei-o-condensing-reasoning/)
30. [**CodeS: Natural Language to Code Repository via Multi-Layer Sketch arXiv:2403.16443**Daoguang Zan, Ailun Yu, Wei Liu, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zan-2024-codes-natural-language-code-repository/)
31. **[EquiBench: Benchmarking Large Language Models' Reasoning about Program Semantics via Equivalence Checking](https://md.research.elamur.ai/free/en/papers/wei-2025-equibench-benchmarking-large-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Anjiang Wei, Jiannan Cao, Ran Li, et al.*2025 · 8 citations*
32. **[MulVul: Retrieval-augmented Multi-Agent Code Vulnerability Detection via Cross-Model Prompt Evolution](https://md.research.elamur.ai/free/en/papers/wu-2026-mulvul-retrieval-augmented-multi-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihan Wu, Jie Xu, Yun Peng, et al.*2026 · 5 citations*
33. **[Scaling Laws for Code: Every Programming Language Matters](https://md.research.elamur.ai/free/en/papers/yang-2026-scaling-laws-code-every-programming/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jian Yang, Shuyue Guo, Linzheng Chai, et al.*2026 · 2 citations*
34. **[XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding Assistants](https://md.research.elamur.ai/free/en/papers/storek-2026-xoxo-stealthy-cross-origin-context/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Adam Štorek, Mukur Gupta, Noopur Bhatt, et al.*2026 · 2 citations*
35. **[ExecVerify: White-Box RL with Verifiable Stepwise Rewards for Code Execution Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2026-execverify-white-box-rl-verifiable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingxiao Tang, He Ye, Zhaoyang Chu, et al.*2026 · 1 citation*
36. **[UIT-AMMC at SemEval-2026 Task 13: Exploiting Structural Formatting Signatures for Robust AI-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/pham-2026-uit-ammc-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Cuong Pham, Minh Nguyen, Minh Le, et al.*2026 · 1 citation*
37. [**Should Code Models Learn Pedagogically? A Preliminary Evaluation of Curriculum Learning for Real-World Software Engineering Tasks arXiv:2502.03806**Kyi Shin Khant, Hong Yi Lin, Patanamon Thongtanunam*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/khant-2025-should-code-models-learn-pedagogically/)
38. **[Research Progress of Pre-trained Model in Software Engineering (预训练模型在软件工程领域应用研究进展)](https://md.research.elamur.ai/free/en/papers/gong-2024-pre-trained-model/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Lina Gong (宫丽娜), Yiren Zhou (周易人), Yu Qiao (乔羽), et al.*2024 · 1 citation*
39. **[Deep Learning Based Code Generation Methods: Literature Review (基于深度学习的代码生成方法研究进展)](https://md.research.elamur.ai/free/en/papers/yang-2023-deep-learning-code/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Zezhou Yang (杨泽洲), Sirong Chen (陈思榕), Cuiyun Gao (高翠芸), et al.*2023 · 1 citation*
40. **[Bootstrapping Code Translation with Weighted Multilanguage Exploration](https://md.research.elamur.ai/free/en/papers/wu-2026-bootstrapping-code-translation-weighted-multilanguage/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhan Wu, Huan Zhang, Wei Cheng, et al.*2026*
41. **[FMISUYotkovaKastreva at SemEval-2026 Task 13: Lightweight Detection of LLM-Generated Code via Stylometric Signals](https://md.research.elamur.ai/free/en/papers/yotkova-2026-fmisuyotkovakastreva-semeval-2026-task-13/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Elitsa Yotkova, Violeta Kastreva, Dimitar Dimitrov, et al.*2026*
42. **[From Logical to Computational Sparsity: Structure-Aware Block-Sparse Attention for Long-Code Completion](https://md.research.elamur.ai/free/en/papers/wang-2026-logical-computational-sparsity-structure-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanli Wang, Yanlin Wang, Bowen Zhang, et al.*2026*
43. **[HyperparameterOmens at SemEval-2026 Task 13: Various approaches to detecting machine- generated code](https://md.research.elamur.ai/free/en/papers/sukhotin-2026-hyperparameteromens-semeval-2026-task-13/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Dmitry Sukhotin, How Yu*2026*
44. **[MIUN BiasPatrol at SemEval-2026 Task 13: Why TF-IDF can Beat Transformers for OOD Code Detection](https://md.research.elamur.ai/free/en/papers/sahlen-2026-miun-biaspatrol-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Loviza Sahlen, Thomas Springfeldt, Mehwish Fatima, et al.*2026*
45. **[Pixel Phantoms at SemEval-2026 Task 13: Exploring Classical and Neural Approaches for AI-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/s-2026-pixel-phantoms-semeval-2026-task-2026-semeval-1-256/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Jithu Morrison S, Janani Hariharakrishnan, Angel Deborah S, et al.*2026*
46. **[Team Yuvan at SemEval-2026 Task 13: Task-Adaptive Ensemble Strategies for AI-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/ramesh-2026-team-yuvan-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Yuvan Ramesh, Tongtong Wu*2026*
47. **[UniGeM: Unifying Data Selection and Mixing via Geometric Exploration and Mining](https://md.research.elamur.ai/free/en/papers/wang-2026-unigem-unifying-data-selection-mixing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Changhao Wang, Yunfeiyu, Xinhao Yao, et al.*2026*
48. **[YNU-HPCC at SemEval-2026 Task 13: Robust Machine-Generated Code Detection under Distribution Shifts](https://md.research.elamur.ai/free/en/papers/xing-2026-ynu-hpcc-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Lixian Xing, Jin Wang, Xuejie Zhang*2026*
49. **[Survey on Application of Retrieval-augmented Generation in Software Engineering (检索增强生成在软件工程中的应用综述)](https://md.research.elamur.ai/free/en/papers/zhang-2025-application-retrieval-augmented/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Quanjun Zhang (张犬俊), Yang Xie (谢杨), Chunrong Fang (房春荣), et al.*2025*
50. **[Survey on Code Generation with LLM-based Agents (基于大语言模型智能体的代码生成综述)](https://md.research.elamur.ai/free/en/papers/dong-2025-code-generation-llm/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yihong Dong (董益宏), Xue Jiang (姜雪), Jiaru Qian (钱家如), et al.*2025*

157 more citing papers of our library have no page here yet.

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