{"total":65,"rows":[{"id":"2108.07732","title":"Program Synthesis with Large Language Models","created":"2021-08-16","cited_by_count":3637,"area":null},{"id":"2302.06527","title":"An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation","created":"2023-02-13","cited_by_count":194,"area":null},{"id":"2301.13816","title":"Execution-based Code Generation using Deep Reinforcement Learning","created":"2023-01-31","cited_by_count":99,"area":null},{"id":"2110.06773","title":"Leveraging Automated Unit Tests for Unsupervised Code Translation","created":"2021-10-13","cited_by_count":82,"area":null},{"id":"2102.07492","title":"DOBF: A Deobfuscation Pre-Training Objective for Programming Languages","created":"2021-02-15","cited_by_count":68,"area":null},{"id":"2501.08200","title":"CWEval: Outcome-driven Evaluation on Functionality and Security of LLM Code Generation","created":"2025-01-14","cited_by_count":59,"area":null},{"id":"2305.00418","title":"Using Large Language Models to Generate JUnit Tests: An Empirical Study","created":"2023-04-30","cited_by_count":53,"area":null},{"id":"2202.06689","title":"CodeFill: Multi-token Code Completion by Jointly Learning from Structure and Naming Sequences","created":"2022-02-14","cited_by_count":50,"area":null},{"id":"2402.02047","title":"Calibration and Correctness of Language Models for Code","created":"2024-02-03","cited_by_count":49,"area":null},{"id":"2202.04903","title":"Investigating Explainability of Generative AI for Code through Scenario-based Design","created":"2022-02-10","cited_by_count":47,"area":null},{"id":"2203.05132","title":"Compilable Neural Code Generation with Compiler Feedback","created":"2022-03-10","cited_by_count":47,"area":null},{"id":"2207.11680","title":"No More Fine-Tuning? An Experimental Evaluation of Prompt Tuning in Code Intelligence","created":"2022-07-24","cited_by_count":41,"area":null},{"id":"2405.19782","title":"Dataflow-Guided Retrieval Augmentation for Repository-Level Code Completion","created":"2024-05-30","cited_by_count":40,"area":null},{"id":"2206.01335","title":"Code Generation Tools (Almost) for Free? A Study of Few-Shot, Pre-Trained Language Models on Code","created":"2022-06-02","cited_by_count":39,"area":null},{"id":"2311.00889","title":"SALLM: Security Assessment of Generated Code","created":"2023-11-01","cited_by_count":39,"area":null},{"id":"2402.16197","title":"Language Models for Code Completion: A Practical Evaluation","created":"2024-02-25","cited_by_count":39,"area":null},{"id":"2206.05239","title":"StructCoder: Structure-Aware Transformer for Code Generation","created":"2022-06-10","cited_by_count":34,"area":null},{"id":"2401.03003","title":"AST-T5: Structure-Aware Pretraining for Code Generation and Understanding","created":"2024-01-05","cited_by_count":33,"area":null},{"id":"2307.02503","title":"Natural Language Generation and Understanding of Big Code for AI-Assisted Programming: A Review","created":"2023-07-04","cited_by_count":32,"area":null},{"id":"2103.09499","title":"Code Completion by Modeling Flattened Abstract Syntax Trees as Graphs","created":"2021-03-17","cited_by_count":30,"area":null},{"id":"2306.03438","title":"Large Language Models of Code Fail at Completing Code with Potential Bugs","created":"2023-06-06","cited_by_count":29,"area":null},{"id":"2105.04297","title":"How could Neural Networks understand Programs?","created":"2021-05-10","cited_by_count":26,"area":null},{"id":"2108.06645","title":"On Multi-Modal Learning of Editing Source Code","created":"2021-08-15","cited_by_count":25,"area":null},{"id":"2205.10162","title":"FedAdapter: Efficient Federated Learning for Modern NLP","created":"2022-05-20","cited_by_count":25,"area":null},{"id":"2106.10158","title":"Learning to Complete Code with Sketches","created":"2021-06-18","cited_by_count":23,"area":null},{"id":"2210.13148","title":"Transformers over Directed Acyclic Graphs","created":"2022-10-24","cited_by_count":23,"area":null},{"id":"2401.00288","title":"Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit","created":"2023-12-30","cited_by_count":22,"area":null},{"id":"2305.12050","title":"AI-assisted Code Authoring at Scale: Fine-tuning, deploying, and mixed methods evaluation","created":"2023-05-20","cited_by_count":21,"area":null},{"id":"2205.02029","title":"CODE-MVP: Learning to Represent Source Code from Multiple Views with Contrastive Pre-Training","created":"2022-05-04","cited_by_count":15,"area":null},{"id":"2212.05974","title":"Federated Few-Shot Learning for Mobile NLP","created":"2022-12-12","cited_by_count":15,"area":null},{"id":"2306.00381","title":"Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion","created":"2023-06-01","cited_by_count":14,"area":null},{"id":"2307.08220","title":"FRANC: A Lightweight Framework for High-Quality Code Generation","created":"2023-07-17","cited_by_count":14,"area":null},{"id":"2410.04490","title":"A Large-Scale Exploit Instrumentation Study of AI/ML Supply Chain Attacks in Hugging Face Models","created":"2024-10-06","cited_by_count":14,"area":null},{"id":"2101.11268","title":"Enquire One's Parent and Child Before Decision: Fully Exploit Hierarchical Structure for Self-Supervised Taxonomy Expansion","created":"2021-01-27","cited_by_count":13,"area":null},{"id":"2201.07420","title":"Cross-Language Binary-Source Code Matching with Intermediate Representations","created":"2022-01-19","cited_by_count":13,"area":null},{"id":"2402.04141","title":"Multi-line AI-assisted Code Authoring","created":"2024-02-06","cited_by_count":13,"area":null},{"id":"2107.00992","title":"Multimodal Representation for Neural Code Search","created":"2021-07-02","cited_by_count":11,"area":null},{"id":"2112.01184","title":"AST-Transformer: Encoding Abstract Syntax Trees Efficiently for Code Summarization","created":"2021-12-02","cited_by_count":11,"area":null},{"id":"2211.04673","title":"Syntax-Aware On-the-Fly Code Completion","created":"2022-11-09","cited_by_count":10,"area":null},{"id":"2308.03312","title":"Exploiting Code Symmetries for Learning Program Semantics","created":"2023-08-07","cited_by_count":10,"area":null},{"id":"2404.10155","title":"The Fault in our Stars: Quality Assessment of Code Generation Benchmarks","created":"2024-04-15","cited_by_count":9,"area":null},{"id":"2402.17988","title":"Constrained Decoding for Fill-in-the-Middle Code Language Models via Efficient Left and Right Quotienting of Context-Sensitive Grammars","created":"2024-02-28","cited_by_count":8,"area":null},{"id":"2302.02343","title":"LExecutor: Learning-Guided Execution","created":"2023-02-05","cited_by_count":7,"area":null},{"id":"2105.05991","title":"Improving Code Autocompletion with Transfer Learning","created":"2021-05-12","cited_by_count":6,"area":null},{"id":"2206.06460","title":"MetaTPTrans: A Meta Learning Approach for Multilingual Code Representation Learning","created":"2022-06-13","cited_by_count":6,"area":null},{"id":"2212.00192","title":"Towards Practical Few-shot Federated NLP","created":"2022-12-01","cited_by_count":5,"area":null},{"id":"2205.01293","title":"A Survey of Deep Learning Models for Structural Code Understanding","created":"2022-05-03","cited_by_count":4,"area":null},{"id":"2208.07461","title":"A Library for Representing Python Programs as Graphs for Machine Learning","created":"2022-08-15","cited_by_count":4,"area":null},{"id":"2312.09126","title":"Towards Trustworthy AI Software Development Assistance","created":"2023-12-14","cited_by_count":4,"area":null},{"id":"2504.00019","title":"ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding","created":"2025-03-27","cited_by_count":4,"area":null},{"id":"2507.03156","title":"The Impact of LLM-Assistants on Software Developer Productivity: A Systematic Review and Mapping Study","created":"2025-07-03","cited_by_count":4,"area":null},{"id":"2105.14038","title":"Learning to Extend Program Graphs to Work-in-Progress Code","created":"2021-05-28","cited_by_count":3,"area":null},{"id":"2301.10516","title":"What are the Machine Learning best practices reported by practitioners on Stack Exchange?","created":"2023-01-25","cited_by_count":3,"area":null},{"id":"2401.10716","title":"Structured Code Representations Enable Data-Efficient Adaptation of Code Language Models","created":"2024-01-19","cited_by_count":3,"area":null},{"id":"2402.05939","title":"Uncertainty Awareness of Large Language Models Under Code Distribution Shifts: A Benchmark Study","created":"2024-01-12","cited_by_count":3,"area":null},{"id":"2508.16131","title":"The Fools are Certain; the Wise are Doubtful: Exploring LLM Confidence in Code Completion","created":"2025-08-22","cited_by_count":3,"area":null},{"id":"2503.15571","title":"LLM-Aided Customizable Profiling of Code Data Based On Programming Language Concepts","created":"2025-03-19","cited_by_count":2,"area":null},{"id":"2504.09474","title":"MigGPT: Harnessing Large Language Models for Automated Migration of Out-of-Tree Linux Kernel Patches Across Versions","created":"2025-04-13","cited_by_count":2,"area":null},{"id":"2303.07826","title":"Implant Global and Local Hierarchy Information to Sequence based Code Representation Models","created":"2023-03-14","cited_by_count":1,"area":null},{"id":"2212.12584","title":"Neural Transition-based Parsing of Library Deprecations","created":"2022-12-23","cited_by_count":0,"area":null},{"id":"2305.11619","title":"Towards Code Generation from BDD Test Case Specifications: A Vision","created":"2023-05-19","cited_by_count":0,"area":null},{"id":"2312.12598","title":"A Case Study on Test Case Construction with Large Language Models: Unveiling Practical Insights and Challenges","created":"2023-12-19","cited_by_count":0,"area":null},{"id":"2411.19304","title":"Perspective of Software Engineering Researchers on Machine Learning Practices Regarding Research, Review, and Education","created":"2024-11-28","cited_by_count":0,"area":null},{"id":"2508.02455","title":"TreeRanker: Fast and Model-agnostic Ranking System for Code Suggestions in IDEs","created":"2025-08-04","cited_by_count":0,"area":null},{"id":"2512.21238","title":"Assessing the Software Security Comprehension of Large Language Models","created":"2025-12-24","cited_by_count":0,"area":null}],"next_cursor":null}