{"total":68,"rows":[{"id":"2406.00515","title":"A Survey on Large Language Models for Code Generation","created":"2024-06-01","cited_by_count":658,"area":null},{"id":"2108.09293","title":"Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code Contributions","created":"2021-08-20","cited_by_count":431,"area":null},{"id":"2304.00385","title":"Keep the Conversation Going: Fixing 162 out of 337 bugs for $0.42 each using ChatGPT","created":"2023-04-01","cited_by_count":125,"area":null},{"id":"2112.02125","title":"Examining Zero-Shot Vulnerability Repair with Large Language Models","created":"2021-12-03","cited_by_count":105,"area":null},{"id":"2406.01304","title":"CodeR: Issue Resolving with Multi-Agent and Task Graphs","created":"2024-06-03","cited_by_count":91,"area":null},{"id":"2309.00608","title":"Copiloting the Copilots: Fusing Large Language Models with Completion Engines for Automated Program Repair","created":"2023-09-01","cited_by_count":55,"area":null},{"id":"2305.18607","title":"How Effective Are Neural Networks for Fixing Security Vulnerabilities","created":"2023-05-29","cited_by_count":52,"area":null},{"id":"2312.15698","title":"RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair","created":"2023-12-25","cited_by_count":50,"area":null},{"id":"2112.02043","title":"Multilingual training for Software Engineering","created":"2021-12-03","cited_by_count":43,"area":null},{"id":"2305.14752","title":"A New Era in Software Security: Towards Self-Healing Software via Large Language Models and Formal Verification","created":"2023-05-24","cited_by_count":42,"area":null},{"id":"2301.13246","title":"Conversational Automated Program Repair","created":"2023-01-30","cited_by_count":41,"area":null},{"id":"2405.02213","title":"Automatic Programming: Large Language Models and Beyond","created":"2024-05-03","cited_by_count":36,"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":"2108.06645","title":"On Multi-Modal Learning of Editing Source Code","created":"2021-08-15","cited_by_count":25,"area":null},{"id":"2110.09610","title":"A Survey on Machine Learning Techniques for Source Code Analysis","created":"2021-10-18","cited_by_count":24,"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":"2304.05216","title":"Towards Efficient Fine-tuning of Pre-trained Code Models: An Experimental Study and Beyond","created":"2023-04-11","cited_by_count":20,"area":null},{"id":"2407.07472","title":"Rectifier: Code Translation with Corrector via LLMs","created":"2024-07-10","cited_by_count":20,"area":null},{"id":"2304.12015","title":"ITER: Iterative Neural Repair for Multi-Location Patches","created":"2023-04-24","cited_by_count":16,"area":null},{"id":"2503.17502","title":"Large Language Models (LLMs) for Source Code Analysis: applications, models and datasets","created":"2025-03-21","cited_by_count":16,"area":null},{"id":"2304.03816","title":"Towards Generating Functionally Correct Code Edits from Natural Language Issue Descriptions","created":"2023-04-07","cited_by_count":14,"area":null},{"id":"2402.05980","title":"Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates","created":"2024-02-08","cited_by_count":14,"area":null},{"id":"2302.01857","title":"KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair","created":"2023-02-03","cited_by_count":13,"area":null},{"id":"2404.08877","title":"Aligning the Objective of LLM-based Program Repair","created":"2024-04-13","cited_by_count":12,"area":null},{"id":"2304.01102","title":"RunBugRun -- An Executable Dataset for Automated Program Repair","created":"2023-04-03","cited_by_count":11,"area":null},{"id":"2211.14875","title":"Detect-Localize-Repair: A Unified Framework for Learning to Debug with CodeT5","created":"2022-11-27","cited_by_count":10,"area":null},{"id":"2212.11414","title":"Improving Automated Program Repair with Domain Adaptation","created":"2022-12-21","cited_by_count":10,"area":null},{"id":"2402.00699","title":"PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software","created":"2024-02-01","cited_by_count":9,"area":null},{"id":"2302.04048","title":"Automating Code-Related Tasks Through Transformers: The Impact of Pre-training","created":"2023-02-08","cited_by_count":8,"area":null},{"id":"2208.04125","title":"Is this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness","created":"2022-08-08","cited_by_count":7,"area":null},{"id":"2303.10494","title":"Revisiting the Plastic Surgery Hypothesis via Large Language Models","created":"2023-03-18","cited_by_count":7,"area":null},{"id":"2405.05455","title":"Automated Program Repair: Emerging trends pose and expose problems for benchmarks","created":"2024-05-08","cited_by_count":7,"area":null},{"id":"2309.12938","title":"Frustrated with Code Quality Issues? LLMs can Help!","created":"2023-09-22","cited_by_count":5,"area":null},{"id":"2312.04986","title":"Out of Context: How important is Local Context in Neural Program Repair?","created":"2023-12-08","cited_by_count":5,"area":null},{"id":"2402.11892","title":"Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testing","created":"2024-02-19","cited_by_count":5,"area":null},{"id":"2410.15490","title":"Dynamic Intelligence Assessment: Benchmarking LLMs on the Road to AGI with a Focus on Model Confidence","created":"2024-10-20","cited_by_count":5,"area":null},{"id":"2410.16655","title":"Memory-Efficient Large Language Models for Program Repair with Semantic-Guided Patch Generation","created":"2024-10-22","cited_by_count":5,"area":null},{"id":"2107.13296","title":"Predicting Patch Correctness Based on the Similarity of Failing Test Cases","created":"2021-07-28","cited_by_count":4,"area":null},{"id":"2403.08375","title":"Translating between SQL Dialects for Cloud Migration","created":"2024-03-13","cited_by_count":4,"area":null},{"id":"2404.04839","title":"AI for DevSecOps: A Landscape and Future Opportunities","created":"2024-04-07","cited_by_count":4,"area":null},{"id":"2404.06201","title":"Open-Source AI-based SE Tools: Opportunities and Challenges of Collaborative Software Learning","created":"2024-04-09","cited_by_count":4,"area":null},{"id":"2409.10959","title":"Leveraging Reviewer Experience in Code Review Comment Generation","created":"2024-09-17","cited_by_count":4,"area":null},{"id":"2412.03905","title":"Integrating Various Software Artifacts for Better LLM-based Bug Localization and Program Repair","created":"2024-12-05","cited_by_count":4,"area":null},{"id":"2202.04847","title":"A Survey on Artificial Intelligence for Source Code: A Dialogue Systems Perspective","created":"2022-02-10","cited_by_count":3,"area":null},{"id":"2401.07994","title":"Assessing the Latent Automated Program Repair Capabilities of Large Language Models using Round-Trip Translation","created":"2024-01-15","cited_by_count":3,"area":null},{"id":"2409.08904","title":"AnyBipe: An End-to-End Framework for Training and Deploying Bipedal Robots Guided by Large Language Models","created":"2024-09-13","cited_by_count":3,"area":null},{"id":"2507.19909","title":"The Impact of Fine-tuning Large Language Models on Automated Program Repair","created":"2025-07-26","cited_by_count":3,"area":null},{"id":"2512.24635","title":"DynaFix: Iterative Automated Program Repair Driven by Execution-Level Dynamic Information","created":"2025-12-31","cited_by_count":3,"area":null},{"id":"2306.06620","title":"ARIST: An Effective API Argument Recommendation Approach","created":"2023-06-11","cited_by_count":2,"area":null},{"id":"2401.14617","title":"A Systematic Literature Review on Explainability for Machine/Deep Learning-based Software Engineering Research","created":"2024-01-26","cited_by_count":2,"area":null},{"id":"2506.10401","title":"HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration","created":"2025-06-12","cited_by_count":2,"area":null},{"id":"2205.13342","title":"Leveraging Causal Inference for Explainable Automatic Program Repair","created":"2022-05-26","cited_by_count":1,"area":null},{"id":"2307.02443","title":"An Exploratory Literature Study on Sharing and Energy Use of Language Models for Source Code","created":"2023-07-05","cited_by_count":1,"area":null},{"id":"2308.08943","title":"Towards Automatically Addressing Self-Admitted Technical Debt: How Far Are We?","created":"2023-08-17","cited_by_count":1,"area":null},{"id":"2402.16790","title":"Beyond Self-learned Attention: Mitigating Attention Bias in Transformer-based Models Using Attention Guidance","created":"2024-02-26","cited_by_count":1,"area":null},{"id":"2408.08619","title":"PatUntrack: Automated Generating Patch Examples for Issue Reports without Tracked Insecure Code","created":"2024-08-16","cited_by_count":1,"area":null},{"id":"2506.13182","title":"From Empirical Evaluation to Context-Aware Enhancement: Repairing Regression Errors with LLMs","created":"2025-06-16","cited_by_count":1,"area":null},{"id":"2207.10739","title":"BigIssue: A Realistic Bug Localization Benchmark","created":"2022-07-21","cited_by_count":0,"area":null},{"id":"2212.12584","title":"Neural Transition-based Parsing of Library Deprecations","created":"2022-12-23","cited_by_count":0,"area":null},{"id":"2404.01754","title":"Peer-aided Repairer: Empowering Large Language Models to Repair Advanced Student Assignments","created":"2024-04-02","cited_by_count":0,"area":null},{"id":"2412.13467","title":"Transducer Tuning: Efficient Model Adaptation for Software Tasks Using Code Property Graphs","created":"2024-12-18","cited_by_count":0,"area":null},{"id":"2502.13459","title":"Poisoned Source Code Detection in Code Models","created":"2025-02-19","cited_by_count":0,"area":null},{"id":"2507.19271","title":"Fine-Tuning Multilingual Language Models for Code Review: An Empirical Study on Industrial C# Projects","created":"2025-07-25","cited_by_count":0,"area":null},{"id":"2601.23059","title":"On the Impact of Code Comments for Automated Bug-Fixing: An Empirical Study","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2604.12994","title":"LogicEval: A Systematic Framework for Evaluating Automated Repair Techniques for Logical Vulnerabilities in Real-World Software","created":"2026-04-14","cited_by_count":0,"area":null},{"id":"2605.17450","title":"ContraFix: Skill-Enhanced Contrastive Runtime Analysis for Vulnerability Repair","created":"2026-05-17","cited_by_count":0,"area":null},{"id":"2609.20130","title":"AdaRepair-Mem: Adaptive Experience Orchestration for Repository-Level Program Repair","created":"2026-09-17","cited_by_count":0,"area":null},{"id":"2610.20245","title":"P2Patch: Exploit-Guided Vulnerability Repair","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}