mlsanityData to 7 Oct 2026

RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation

arXiv 2303.12570 ↗First posted 22 Mar 2023cs.CL cs.AI cs.PLcited by 357

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Cited by 81 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

The task of repository-level code completion is to continue writing the unfinished code based on a broader context of the repository. While for automated code completion tools, it is difficult to utilize the useful information scattered in different files. We propose RepoCoder, a simple, generic, and effective framework to address the challenge. It streamlines the repository-level code completion process by incorporating a similarity-based retriever and a pre-trained code language model in an iterative retrieval-generation pipeline. RepoCoder makes effective utilization of repository-level information for code completion and has the ability to generate code at various levels of granularity. Moreover, we propose a new benchmark RepoEval, which consists of the latest and high-quality real-world repositories covering line, API invocation, and function body completion scenarios. Experimental results indicate that RepoCoder significantly improves the In-File completion baseline by over 10% in all settings and consistently outperforms the vanilla retrieval-augmented code completion approach. Furthermore, we validate the effectiveness of RepoCoder through comprehensive analysis, providing valuable insights for future research. Our source code and benchmark are publicly available: https://github.com/microsoft/CodeT/tree/main/RepoCoder

Key facts. Cited by 357 papers in the map (data through 7 Oct 2026). Builds on 31 of its 46 references that are in the map. First posted on arXiv 22 Mar 2023.

Builds on

31 of 46 references.

References · 31

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  4. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  5. 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 2,126
  6. 2022Competition-Level Code Generation with AlphaCodecited by 1,427
  7. 2022LaMDA: Language Models for Dialog Applicationscited by 1,218
  8. 2022Atlas: Few-shot Learning with Retrieval Augmented Language Modelscited by 940
  9. 2021Measuring Coding Challenge Competence With APPScited by 879
  10. 2022CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesiscited by 876
  11. 2023REPLUG: Retrieval-Augmented Black-Box Language Modelscited by 786
  12. 2021CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generationcited by 732
19 more
  1. 2023In-Context Retrieval-Augmented Language Modelscited by 694
  2. 2022CodeT: Code Generation with Generated Testscited by 369
  3. 2022UniXcoder: Unified Cross-Modal Pre-training for Code Representationcited by 355
  4. 2020IntelliCode Compose: Code Generation Using Transformercited by 225
  5. 2020Generation-Augmented Retrieval for Open-domain Question Answeringcited by 186
  6. 2021Retrieval Augmented Code Generation and Summarizationcited by 148
  7. 2023Query2doc: Query Expansion with Large Language Modelscited by 146
  8. 2022ReACC: A Retrieval-Augmented Code Completion Frameworkcited by 117
  9. 2022Repository-Level Prompt Generation for Large Language Models of Codecited by 106
  10. 2022CoCoMIC: Code Completion By Jointly Modeling In-file and Cross-file Contextcited by 64
  11. 2019Pythia: AI-assisted Code Completion Systemcited by 54
  12. 2022When Language Model Meets Private Librarycited by 54
  13. 2020Fast and Memory-Efficient Neural Code Completioncited by 38
  14. 2022Standing on the Shoulders of Giant Frozen Language Modelscited by 33
  15. 2021RetGen: A Joint framework for Retrieval and Grounded Text Generation Modelingcited by 22
  16. 2022Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsingcited by 15
  17. 2021Long-Range Modeling of Source Code Files with eWASH: Extended Window Access by Syntax Hierarchycited by 14
  18. 2022Learning to Recommend Method Names with Global Contextcited by 6
  19. 2022Generation-Augmented Query Expansion For Code Retrievalcited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 21; 2024: 100; 2025: 113; 2026: 123.

357 papers.

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  1. 2023Qwen Technical Reportcited by 3,273
  2. 2024LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Codecited by 1,906
  3. 2024Qwen2.5-Coder Technical Reportcited by 1,151
  4. 2024A Survey on Large Language Models for Code Generationcited by 646
  5. 2023A Comprehensive Overview of Large Language Modelscited by 639
  6. 2023Active Retrieval Augmented Generationcited by 506
  7. 2023LeanDojo: Theorem Proving with Retrieval-Augmented Language Modelscited by 414
  8. 2024Agentless: Demystifying LLM-based Software Engineering Agentscited by 400
  9. 2025Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attentioncited by 391
  10. 2024Retrieval-Augmented Generation for AI-Generated Content: A Surveycited by 352
  11. 2023RepoBench: Benchmarking Repository-Level Code Auto-Completion Systemscited by 346
  12. 2023Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergycited by 343
38 more
  1. 2024CRUXEval: A Benchmark for Code Reasoning, Understanding and Executioncited by 294
  2. 2024Agent-as-a-Judge: Evaluate Agents with Agentscited by 223
  3. 2024SWE-bench Multimodal: Do AI Systems Generalize to Visual Software Domains?cited by 196
  4. 2023CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completioncited by 181
  5. 2023OctoPack: Instruction Tuning Code Large Language Modelscited by 178
  6. 2025Multi-SWE-bench: A Multilingual Benchmark for Issue Resolvingcited by 165
  7. 2024OpenCoder: The Open Cookbook for Top-Tier Code Large Language Modelscited by 127
  8. 2024Beyond Functional Correctness: Exploring Hallucinations in LLM-Generated Codecited by 106
  9. 2024LLM Hallucinations in Practical Code Generation: Phenomena, Mechanism, and Mitigationcited by 92
  10. 2025Agent KB: Leveraging Cross-Domain Experience for Agentic Problem Solvingcited by 90
  11. 2024CodeRAG-Bench: Can Retrieval Augment Code Generation?cited by 89
  12. 2024RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graphcited by 88
  13. 2024Formal Mathematical Reasoning: A New Frontier in AIcited by 80
  14. 2024EvoCodeBench: An Evolving Code Generation Benchmark Aligned with Real-World Code Repositoriescited by 71
  15. 2024DevEval: A Manually-Annotated Code Generation Benchmark Aligned with Real-World Code Repositoriescited by 71
  16. 2023PanGu-Coder2: Boosting Large Language Models for Code with Ranking Feedbackcited by 69
  17. 2024Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAGcited by 67
  18. 2025Paper2Code: Automating Code Generation from Scientific Papers in Machine Learningcited by 67
  19. 2025WebGen-Bench: Evaluating LLMs on Generating Interactive and Functional Websites from Scratchcited by 66
  20. 2023ML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Codecited by 63
  21. 2023Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Codecited by 62
  22. 2024EffiBench: Benchmarking the Efficiency of Automatically Generated Codecited by 62
  23. 2024CodexGraph: Bridging Large Language Models and Code Repositories via Code Graph Databasescited by 62
  24. 2025Evaluating Step-by-step Reasoning Traces: A Surveycited by 62
  25. 2024Agents in Software Engineering: Survey, Landscape, and Visioncited by 60
  26. 2024CoIR: A Comprehensive Benchmark for Code Information Retrieval Modelscited by 59
  27. 2024Exploring and Unleashing the Power of Large Language Models in Automated Code Translationcited by 57
  28. 2025FEA-Bench: A Benchmark for Evaluating Repository-Level Code Generation for Feature Implementationcited by 57
  29. 2025OpenCodeInstruct: A Large-scale Instruction Tuning Dataset for Code LLMscited by 57
  30. 2024Repoformer: Selective Retrieval for Repository-Level Code Completioncited by 55
  31. 2023Bias Testing and Mitigation in LLM-based Code Generationcited by 53
  32. 2024SUPER: Evaluating Agents on Setting Up and Executing Tasks from Research Repositoriescited by 52
  33. 2024Commit0: Library Generation from Scratchcited by 50
  34. 2024Can LLM Graph Reasoning Generalize beyond Pattern Memorization?cited by 46
  35. 2025Seed-Coder: Let the Code Model Curate Data for Itselfcited by 46
  36. 2024Iterative Refinement of Project-Level Code Context for Precise Code Generation with Compiler Feedbackcited by 45
  37. 2024You Name It, I Run It: An LLM Agent to Execute Tests of Arbitrary Projectscited by 45
  38. 2023RepoFusion: Training Code Models to Understand Your Repositorycited by 40

50 most cited of 357 All 357 (JSON)

Similar, not cited

Close in wording, no citation either way

  1. 2025SaraCoder: Orchestrating Semantic and Structural Cues for Resource-Optimized Repository-Level Code Completion
  2. 2026Do Not Treat Code as Natural Language: Implications for Repository-Level Code Generation and Beyond
  3. 2026Better Call Grep: Evaluating and Improving Grep-Like Lexical Retrieval for Repository-Level Code Completion
  4. 2024STALL+: Boosting LLM-based Repository-level Code Completion with Static Analysis
  5. 2024RLCoder: Reinforcement Learning for Repository-Level Code Completion
  6. 2024A Lightweight Framework for Adaptive Retrieval In Code Completion With Critique Model
  7. 2025Completion by Comprehension: Guiding Code Generation with Multi-Granularity Understanding
  8. 2025GRACE: Graph-Guided Repository-Aware Code Completion through Hierarchical Code Fusion