{"total":97,"rows":[{"id":"2310.06770","title":"SWE-bench: Can Language Models Resolve Real-World GitHub Issues?","created":"2023-10-10","cited_by_count":3373,"area":null},{"id":"2406.00515","title":"A Survey on Large Language Models for Code Generation","created":"2024-06-01","cited_by_count":658,"area":null},{"id":"2406.15877","title":"BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions","created":"2024-06-22","cited_by_count":546,"area":null},{"id":"2308.10620","title":"Large Language Models for Software Engineering: A Systematic Literature Review","created":"2023-08-21","cited_by_count":399,"area":null},{"id":"2504.02605","title":"Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving","created":"2025-04-03","cited_by_count":171,"area":null},{"id":"2308.01861","title":"ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on Class-level Code Generation","created":"2023-08-03","cited_by_count":168,"area":null},{"id":"2307.04349","title":"RLTF: Reinforcement Learning from Unit Test Feedback","created":"2023-07-10","cited_by_count":114,"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":"2310.00658","title":"The Robots are Here: Navigating the Generative AI Revolution in Computing Education","created":"2023-10-01","cited_by_count":86,"area":null},{"id":"2310.00367","title":"AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ","created":"2023-09-30","cited_by_count":79,"area":null},{"id":"2404.10952","title":"Can Language Models Solve Olympiad Programming?","created":"2024-04-16","cited_by_count":72,"area":null},{"id":"2307.14936","title":"PanGu-Coder2: Boosting Large Language Models for Code with Ranking Feedback","created":"2023-07-27","cited_by_count":69,"area":null},{"id":"2410.03981","title":"A Survey on LLM-based Code Generation for Low-Resource and Domain-Specific Programming Languages","created":"2024-10-04","cited_by_count":66,"area":null},{"id":"2403.08937","title":"Bugs in Large Language Models Generated Code: An Empirical Study","created":"2024-03-13","cited_by_count":60,"area":null},{"id":"2407.06153","title":"What's Wrong with Your Code Generated by Large Language Models? An Extensive Study","created":"2024-07-08","cited_by_count":53,"area":null},{"id":"2308.01240","title":"Evaluating Instruction-Tuned Large Language Models on Code Comprehension and Generation","created":"2023-08-02","cited_by_count":50,"area":null},{"id":"2403.01131","title":"LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generation","created":"2024-03-02","cited_by_count":45,"area":null},{"id":"2403.18746","title":"CYCLE: Learning to Self-Refine the Code Generation","created":"2024-03-27","cited_by_count":42,"area":null},{"id":"2402.05200","title":"Are LLMs Ready for Real-World Materials Discovery?","created":"2024-02-07","cited_by_count":40,"area":null},{"id":"2402.07844","title":"Mercury: A Code Efficiency Benchmark for Code Large Language Models","created":"2024-02-12","cited_by_count":35,"area":null},{"id":"2406.07243","title":"MBBQ: A Dataset for Cross-Lingual Comparison of Stereotypes in Generative LLMs","created":"2024-06-11","cited_by_count":35,"area":null},{"id":"2408.14354","title":"SWE-bench-java: A GitHub Issue Resolving Benchmark for Java","created":"2024-08-26","cited_by_count":34,"area":null},{"id":"2404.02806","title":"The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers","created":"2024-04-03","cited_by_count":30,"area":null},{"id":"2501.12372","title":"Is Long Context All You Need? Leveraging LLM's Extended Context for NL2SQL","created":"2025-01-21","cited_by_count":30,"area":null},{"id":"2403.16443","title":"CodeS: Natural Language to Code Repository via Multi-Layer Sketch","created":"2024-03-25","cited_by_count":28,"area":null},{"id":"2308.16458","title":"BioCoder: A Benchmark for Bioinformatics Code Generation with Large Language Models","created":"2023-08-31","cited_by_count":25,"area":null},{"id":"2502.01715","title":"Process-Supervised Reinforcement Learning for Code Generation","created":"2025-02-03","cited_by_count":22,"area":null},{"id":"2407.02099","title":"Helpful assistant or fruitful facilitator? Investigating how personas affect language model behavior","created":"2024-07-02","cited_by_count":21,"area":null},{"id":"2408.13204","title":"DOMAINEVAL: An Auto-Constructed Benchmark for Multi-Domain Code Generation","created":"2024-08-23","cited_by_count":21,"area":null},{"id":"2401.09074","title":"Code Simulation Challenges for Large Language Models","created":"2024-01-17","cited_by_count":15,"area":null},{"id":"2407.00456","title":"Beyond Functional Correctness: Investigating Coding Style Inconsistencies in Large Language Models","created":"2024-06-29","cited_by_count":15,"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":"2308.12415","title":"Benchmarking Causal Study to Interpret Large Language Models for Source Code","created":"2023-08-23","cited_by_count":14,"area":null},{"id":"2407.02211","title":"PromptIntern: Saving Inference Costs by Internalizing Recurrent Prompt during Large Language Model Fine-tuning","created":"2024-07-02","cited_by_count":13,"area":null},{"id":"2502.15343","title":"Tokenization is Sensitive to Language Variation","created":"2025-02-21","cited_by_count":13,"area":null},{"id":"2311.07599","title":"Testing LLMs on Code Generation with Varying Levels of Prompt Specificity","created":"2023-11-10","cited_by_count":12,"area":null},{"id":"2402.14558","title":"LLMs with Industrial Lens: Deciphering the Challenges and Prospects -- A Survey","created":"2024-02-22","cited_by_count":12,"area":null},{"id":"2308.07505","title":"Data Race Detection Using Large Language Models","created":"2023-08-15","cited_by_count":11,"area":null},{"id":"2505.11604","title":"Talk to Your Slides: High-Efficiency Slide Editing via Language-Driven Structured Data Manipulation","created":"2025-05-16","cited_by_count":11,"area":null},{"id":"2508.18190","title":"ST-Raptor: LLM-Powered Semi-Structured Table Question Answering","created":"2025-08-25","cited_by_count":11,"area":null},{"id":"2406.12902","title":"JavaBench: A Benchmark of Object-Oriented Code Generation for Evaluating Large Language Models","created":"2024-06-10","cited_by_count":10,"area":null},{"id":"2509.09969","title":"Large Language Models Meet Legal Artificial Intelligence: A Survey","created":"2025-09-12","cited_by_count":10,"area":null},{"id":"2403.15230","title":"An Exploratory Investigation into Code License Infringements in Large Language Model Training Datasets","created":"2024-03-22","cited_by_count":9,"area":null},{"id":"2409.08692","title":"B4: Towards Optimal Assessment of Plausible Code Solutions with Plausible Tests","created":"2024-09-13","cited_by_count":9,"area":null},{"id":"2501.05396","title":"FairCoder: Probing LLM Bias in High-Stakes Decision Making via Coding Tasks","created":"2025-01-09","cited_by_count":9,"area":null},{"id":"2410.04617","title":"Evaluation of Code LLMs on Geospatial Code Generation","created":"2024-10-06","cited_by_count":8,"area":null},{"id":"2503.12440","title":"HKCanto-Eval: A Benchmark for Evaluating Cantonese Language Understanding and Cultural Comprehension in LLMs","created":"2025-03-16","cited_by_count":8,"area":null},{"id":"2504.20964","title":"OSVBench: Benchmarking LLMs on Specification Generation Tasks for Operating System Verification","created":"2025-04-29","cited_by_count":8,"area":null},{"id":"2308.16824","title":"Can Programming Languages Boost Each Other via Instruction Tuning?","created":"2023-08-31","cited_by_count":7,"area":null},{"id":"2401.07870","title":"JumpCoder: Go Beyond Autoregressive Coder via Online Modification","created":"2024-01-15","cited_by_count":7,"area":null},{"id":"2405.03998","title":"Sketch Then Generate: Providing Incremental User Feedback and Guiding LLM Code Generation through Language-Oriented Code Sketches","created":"2024-05-07","cited_by_count":7,"area":null},{"id":"2407.03611","title":"An Empirical Study on Capability of Large Language Models in Understanding Code Semantics","created":"2024-07-04","cited_by_count":7,"area":null},{"id":"2410.07002","title":"CursorCore: Assist Programming through Aligning Anything","created":"2024-10-09","cited_by_count":7,"area":null},{"id":"2501.15000","title":"MDEval: Evaluating and Enhancing Markdown Awareness in Large Language Models","created":"2025-01-25","cited_by_count":7,"area":null},{"id":"2502.03568","title":"Code Simulation as a Proxy for High-order Tasks in Large Language Models","created":"2025-02-05","cited_by_count":7,"area":null},{"id":"2601.19697","title":"AlignCoder: Aligning Retrieval with Target Intent for Repository-Level Code Completion","created":"2026-01-27","cited_by_count":7,"area":null},{"id":"2312.15614","title":"A Comprehensive Evaluation of Parameter-Efficient Fine-Tuning on Software Engineering Tasks","created":"2023-12-25","cited_by_count":5,"area":null},{"id":"2402.03130","title":"User Centric Evaluation of Code Generation Tools","created":"2024-02-05","cited_by_count":5,"area":null},{"id":"2402.09615","title":"API Pack: A Massive Multi-Programming Language Dataset for API Call Generation","created":"2024-02-14","cited_by_count":5,"area":null},{"id":"2402.10436","title":"I Am Not Them: Fluid Identities and Persistent Out-group Bias in Large Language Models","created":"2024-02-16","cited_by_count":5,"area":null},{"id":"2409.07489","title":"RAGent: Retrieval-based Access Control Policy Generation","created":"2024-09-08","cited_by_count":5,"area":null},{"id":"2505.23851","title":"ASyMOB: Algebraic Symbolic Mathematical Operations Benchmark","created":"2025-05-28","cited_by_count":5,"area":null},{"id":"2507.22080","title":"CodeEvo: Interaction-Driven Synthesis of Code-centric Data through Hybrid and Iterative Feedback","created":"2025-07-25","cited_by_count":5,"area":null},{"id":"2309.13218","title":"Language Models for Business Optimisation with a Real World Case Study in Production Scheduling","created":"2023-09-22","cited_by_count":4,"area":null},{"id":"2403.01570","title":"Small Models are LLM Knowledge Triggers on Medical Tabular Prediction","created":"2024-03-03","cited_by_count":4,"area":null},{"id":"2502.08298","title":"Improving Existing Optimization Algorithms with LLMs","created":"2025-02-12","cited_by_count":4,"area":null},{"id":"2311.01490","title":"The Behavior of Large Language Models When Prompted to Generate Code Explanations","created":"2023-11-02","cited_by_count":3,"area":null},{"id":"2404.02512","title":"Towards Large Language Model driven Reference-less Translation Evaluation for English and Indian Languages","created":"2024-04-03","cited_by_count":3,"area":null},{"id":"2404.02540","title":"CSEPrompts: A Benchmark of Introductory Computer Science Prompts","created":"2024-04-03","cited_by_count":3,"area":null},{"id":"2405.01556","title":"Semantically Aligned Question and Code Generation for Automated Insight Generation","created":"2024-03-21","cited_by_count":3,"area":null},{"id":"2405.04955","title":"Improving Long Text Understanding with Knowledge Distilled from Summarization Model","created":"2024-05-08","cited_by_count":3,"area":null},{"id":"2502.11466","title":"GiFT: Gibbs Fine-Tuning for Code Generation","created":"2025-02-17","cited_by_count":3,"area":null},{"id":"2503.10542","title":"Language Models, Graph Searching, and Supervision Adulteration: When More Supervision is Less and How to Make More More","created":"2025-03-13","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":"2510.17132","title":"Do LLMs Recognize Your Latent Preferences? A Benchmark for Latent Information Discovery in Personalized Interaction","created":"2025-10-20","cited_by_count":3,"area":null},{"id":"2403.08425","title":"Specification Overfitting in Artificial Intelligence","created":"2024-03-13","cited_by_count":2,"area":null},{"id":"2409.11041","title":"Towards No-Code Programming of Cobots: Experiments with Code Synthesis by Large Code Models for Conversational Programming","created":"2024-09-17","cited_by_count":2,"area":null},{"id":"2411.00865","title":"Demo-Craft: Using In-Context Learning to Improve Code Generation in Large Language Models","created":"2024-10-30","cited_by_count":2,"area":null},{"id":"2502.18499","title":"Mechanistic Understanding of Language Models in Syntactic Code Completion","created":"2025-02-20","cited_by_count":2,"area":null},{"id":"2504.18729","title":"Multimodal graph representation learning for website generation based on visual sketch","created":"2025-04-25","cited_by_count":2,"area":null},{"id":"2504.21043","title":"CodeBC: A More Secure Large Language Model for Smart Contract Code Generation in Blockchain","created":"2025-04-28","cited_by_count":2,"area":null},{"id":"2505.19887","title":"Deconstructing Obfuscation: A four-dimensional framework for evaluating Large Language Models assembly code deobfuscation capabilities","created":"2025-05-26","cited_by_count":2,"area":null},{"id":"2512.19758","title":"Attention Distance: A Novel Metric for Directed Fuzzing with Large Language Models","created":"2025-12-19","cited_by_count":2,"area":null},{"id":"2309.12732","title":"OpenAi's GPT4 as coding assistant","created":"2023-09-22","cited_by_count":1,"area":null},{"id":"2411.07398","title":"Beyond Keywords: A Context-based Hybrid Approach to Mining Ethical Concern-related App Reviews","created":"2024-11-11","cited_by_count":1,"area":null},{"id":"2603.22018","title":"Do Papers Tell the Whole Story? A Benchmark and Framework for Uncovering Hidden Implementation Gaps in Bioinformatics","created":"2026-03-23","cited_by_count":1,"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":"2412.15441","title":"Insights into resource utilization of code small language models serving with runtime engines and execution providers","created":"2024-12-19","cited_by_count":0,"area":null},{"id":"2412.17395","title":"WarriorCoder: Learning from Expert Battles to Augment Code Large Language Models","created":"2024-12-23","cited_by_count":0,"area":null},{"id":"2505.12900","title":"AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models","created":"2025-05-19","cited_by_count":0,"area":null},{"id":"2505.24324","title":"SwiftEval: Developing a Language-Specific Benchmark for LLM-generated Code Evaluation","created":"2025-05-30","cited_by_count":0,"area":null},{"id":"2508.09832","title":"Exploring the Potential of Large Language Models in Fine-Grained Review Comment Classification","created":"2025-08-13","cited_by_count":0,"area":null},{"id":"2510.09037","title":"Repairing Regex Vulnerabilities via Localization-Guided Instructions","created":"2025-10-10","cited_by_count":0,"area":null},{"id":"2510.13163","title":"A Matter of Representation: Towards Graph-Based Abstract Code Generation","created":"2025-10-15","cited_by_count":0,"area":null},{"id":"2601.07430","title":"KALE: Enhancing Knowledge Manipulation in Large Language Models via Knowledge-aware Learning","created":"2026-01-12","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":"2610.20538","title":"PrismaCoder: Pushing the Boundaries of Open Multimodal Code Intelligence through Decomposed Rubric Synthesis","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}