🧑‍🔬 Who cites Alexey Svyatkovskiy

246 citations of their works from 223 papers of our library (of the 149,439 whose bibliographies we read) · 40 with a page here, the most cited first · ← Alexey Svyatkovskiy

1. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
2. Evaluating Large Language Models Trained on CodearXiv:2107.03374Mark Chen, Jerry Tworek, Heewoo Jun, et al.2021 · 2,659 citations
3. Competition-Level Code Generation with AlphaCodeScienceYujia Li, David Choi, Junyoung Chung, et al.2022 · 1,564 citations
4. Code Llama: Open Foundation Models for CodearXiv:2308.12950Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.2024 · 1,430 citations
5. Program Synthesis with Large Language ModelsarXiv:2108.07732Jacob Austin, Augustus Odena, Maxwell Nye, et al.2021 · 1,192 citations
6. Unified Pre-training for Program Understanding and GenerationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, et al.2021 · 750 citations
7. Qwen2.5-Coder Technical ReportarXiv:2409.12186Binyuan Hui, Jian Yang, Zeyu Cui, et al.2024 · 559 citations
8. Security and Privacy Challenges of Large Language Models: A SurveyACM Computing SurveysBadhan Chandra Das, M. Hadi Amini, Yanzhao Wu2024 · 424 citations
9. A Survey on Large Language Models for Code GenerationarXiv:2406.00515Juyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
10. Text and Code Embeddings by Contrastive Pre-TrainingarXiv:2201.10005Arvind Neelakantan, Tao Xu, Raul Puri, et al.2022 · 323 citations
11. Retrieval-Augmented Generation for AI-Generated Content: A SurveyarXiv:2402.19473Penghao Zhao, Hailin Zhang, Qinhan Yu, et al.2024 · 301 citations
12. CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement LearningConference on Neural Information Processing Systems (NeurIPS)Hung Le, Yue Wang, Akhilesh Deepak Gotmare, et al.2022 · 297 citations
13. LeanDojo: Theorem Proving with Retrieval-Augmented Language ModelsConference on Neural Information Processing Systems (NeurIPS)Kaiyu Yang, Aidan M. Swope, Alex Gu, et al.2023 · 253 citations
14. Retrieval Augmented Code Generation and SummarizationFindings of the Association for Computational LinguisticsMd Rizwan Parvez, Wasi Ahmad, Saikat Chakraborty, et al.2021 · 193 citations
15. ToolQA: A Dataset for LLM Question Answering with External ToolsConference on Neural Information Processing Systems (NeurIPS)Yuchen Zhuang, Yue Yu, Kuan Wang, et al.2023 · 182 citations
16. BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex InstructionsarXiv:2406.15877Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.2024 · 176 citations
17. ReACC: A Retrieval-Augmented Code Completion FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL)Shuai Lu, Nan Duan, Hojae Han, et al.2022 · 125 citations
18. InterCode: Standardizing and Benchmarking Interactive Coding with Execution FeedbackConference on Neural Information Processing Systems (NeurIPS)John Yang, Akshara Prabhakar, Karthik Narasimhan, et al.2023 · 95 citations
19. RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement LearningarXiv:2410.02089Jonas Gehring, Kunhao Zheng, Jade Copet, et al.2024 · 51 citations
20. PanGu-Coder: Program Synthesis with Function-Level Language ModelingarXiv:2207.11280Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, et al.2022 · 49 citations
21. RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon GenerationarXiv:2403.05313Zihao Wang, Anji Liu, Haowei Lin, et al.2024 · 46 citations
22. CoCoMIC: Code Completion by Jointly Modeling In-file and Cross-file ContextLanguage Resources and Evaluation Conference (LREC)Yangruibo Ding, Zijian Wang, Wasi Ahmad, et al.2024 · 45 citations
23. ERNIE-Code: Beyond English-Centric Cross-lingual Pretraining for Programming LanguagesarXiv:2212.06742Yekun Chai, Shuohuan Wang, Chao Pang, et al.2022 · 32 citations
24. RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented InstructionsConference on Empirical Methods in Natural Language Processing (EMNLP)Wanlong Liu, Junying Chen, Ke Ji, et al.2025 · 19 citations
25. CodeS: Natural Language to Code Repository via Multi-Layer SketcharXiv:2403.16443Daoguang Zan, Ailun Yu, Wei Liu, et al.2024 · 9 citations
26. MulVul: Retrieval-augmented Multi-Agent Code Vulnerability Detection via Cross-Model Prompt EvolutionAnnual Meeting of the Association for Computational Linguistics (ACL)Zihan Wu, Jie Xu, Yun Peng, et al.2026 · 5 citations
27. Scaling Laws for Code: Every Programming Language MattersFindings of the Association for Computational LinguisticsJian Yang, Shuyue Guo, Linzheng Chai, et al.2026 · 2 citations
28. XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding AssistantsAnnual Meeting of the Association for Computational Linguistics (ACL)Adam Štorek, Mukur Gupta, Noopur Bhatt, et al.2026 · 2 citations
29. UIT-AMMC at SemEval-2026 Task 13: Exploiting Structural Formatting Signatures for Robust AI-Generated Code DetectionInternational Workshop on Semantic Evaluation (SemEval)Cuong Pham, Minh Nguyen, Minh Le, et al.2026 · 1 citation
30. 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)Journal of SoftwareLina Gong (宫丽娜), Yiren Zhou (周易人), Yu Qiao (乔羽), et al.2024 · 1 citation
31. 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)Journal of SoftwareZezhou Yang (杨泽洲), Sirong Chen (陈思榕), Cuiyun Gao (高翠芸), et al.2023 · 1 citation
32. ArkRepoBench: A Repository-Level Code Completion Benchmark for HarmonyOS DevelopmentFindings of the Association for Computational LinguisticsYanlin Wang, Bowen Zhang, Yanli Wang, et al.2026
33. From Logical to Computational Sparsity: Structure-Aware Block-Sparse Attention for Long-Code CompletionAnnual Meeting of the Association for Computational Linguistics (ACL)Yanli Wang, Yanlin Wang, Bowen Zhang, et al.2026
34. HyperparameterOmens at SemEval-2026 Task 13: Various approaches to detecting machine- generated codeInternational Workshop on Semantic Evaluation (SemEval)Dmitry Sukhotin, How Yu2026
35. MIUN BiasPatrol at SemEval-2026 Task 13: Why TF-IDF can Beat Transformers for OOD Code DetectionInternational Workshop on Semantic Evaluation (SemEval)Loviza Sahlen, Thomas Springfeldt, Mehwish Fatima, et al.2026
36. Pixel Phantoms at SemEval-2026 Task 13: Exploring Classical and Neural Approaches for AI-Generated Code DetectionInternational Workshop on Semantic Evaluation (SemEval)Jithu Morrison S, Janani Hariharakrishnan, Angel Deborah S, et al.2026
37. Team Yuvan at SemEval-2026 Task 13: Task-Adaptive Ensemble Strategies for AI-Generated Code DetectionInternational Workshop on Semantic Evaluation (SemEval)Yuvan Ramesh, Tongtong Wu2026
38. UniGeM: Unifying Data Selection and Mixing via Geometric Exploration and MiningFindings of the Association for Computational LinguisticsChanghao Wang, Yunfeiyu, Xinhao Yao, et al.2026
39. 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)Journal of SoftwareQuanjun Zhang (张犬俊), Yang Xie (谢杨), Chunrong Fang (房春荣), et al.2025
40. 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)Journal of SoftwareYihong Dong (董益宏), Xue Jiang (姜雪), Jiaru Qian (钱家如), et al.2025

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