{"total":62,"rows":[{"id":"2102.04664","title":"CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation","created":"2021-02-09","cited_by_count":744,"area":null},{"id":"2108.11601","title":"Retrieval Augmented Code Generation and Summarization","created":"2021-08-26","cited_by_count":149,"area":"rag"},{"id":"2106.11455","title":"KaggleDBQA: Realistic Evaluation of Text-to-SQL Parsers","created":"2021-06-22","cited_by_count":106,"area":null},{"id":"2006.05405","title":"Retrieval-Augmented Generation for Code Summarization via Hybrid GNN","created":"2020-06-09","cited_by_count":89,"area":"rag"},{"id":"2304.11938","title":"Is ChatGPT the Ultimate Programming Assistant -- How far is it?","created":"2023-04-24","cited_by_count":76,"area":null},{"id":"2304.06815","title":"Automatic Semantic Augmentation of Language Model Prompts (for Code Summarization)","created":"2023-04-13","cited_by_count":72,"area":null},{"id":"2208.03133","title":"Out of the BLEU: how should we assess quality of the Code Generation models?","created":"2022-08-05","cited_by_count":65,"area":null},{"id":"2107.07112","title":"On the Evaluation of Neural Code Summarization","created":"2021-07-15","cited_by_count":48,"area":null},{"id":"2203.05132","title":"Compilable Neural Code Generation with Compiler Feedback","created":"2022-03-10","cited_by_count":47,"area":null},{"id":"2112.02043","title":"Multilingual training for Software Engineering","created":"2021-12-03","cited_by_count":43,"area":null},{"id":"2107.01431","title":"Neural-Symbolic Solver for Math Word Problems with Auxiliary Tasks","created":"2021-07-03","cited_by_count":38,"area":null},{"id":"2302.10166","title":"Learning Deep Semantics for Test Completion","created":"2023-02-20","cited_by_count":31,"area":null},{"id":"2104.09340","title":"Code Structure Guided Transformer for Source Code Summarization","created":"2021-04-19","cited_by_count":30,"area":null},{"id":"2109.08365","title":"CodeQA: A Question Answering Dataset for Source Code Comprehension","created":"2021-09-17","cited_by_count":30,"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":"2406.16386","title":"Automatically Generating UI Code from Screenshot: A Divide-and-Conquer-Based Approach","created":"2024-06-24","cited_by_count":24,"area":null},{"id":"2105.14220","title":"CoDesc: A Large Code-Description Parallel Dataset","created":"2021-05-29","cited_by_count":23,"area":null},{"id":"2402.08699","title":"Unsupervised Evaluation of Code LLMs with Round-Trip Correctness","created":"2024-02-13","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":"2103.07845","title":"Improving Code Summarization with Block-wise Abstract Syntax Tree Splitting","created":"2021-03-14","cited_by_count":19,"area":null},{"id":"2206.07245","title":"An Extractive-and-Abstractive Framework for Source Code Summarization","created":"2022-06-15","cited_by_count":18,"area":null},{"id":"2306.14583","title":"Exploring the Robustness of Large Language Models for Solving Programming Problems","created":"2023-06-26","cited_by_count":16,"area":null},{"id":"2405.07530","title":"Prompt-based Code Completion via Multi-Retrieval Augmented Generation","created":"2024-05-13","cited_by_count":16,"area":"rag"},{"id":"2310.06680","title":"Benchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach","created":"2023-10-10","cited_by_count":15,"area":null},{"id":"2202.06521","title":"Source Code Summarization with Structural Relative Position Guided Transformer","created":"2022-02-14","cited_by_count":14,"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":"2103.10668","title":"API2Com: On the Improvement of Automatically Generated Code Comments Using API Documentations","created":"2021-03-19","cited_by_count":10,"area":null},{"id":"2105.14796","title":"Improving Tree-Structured Decoder Training for Code Generation via Mutual Learning","created":"2021-05-31","cited_by_count":10,"area":null},{"id":"2106.00261","title":"Exploring Dynamic Selection of Branch Expansion Orders for Code Generation","created":"2021-06-01","cited_by_count":10,"area":null},{"id":"2205.15479","title":"HierarchyNet: Learning to Summarize Source Code with Heterogeneous Representations","created":"2022-05-31","cited_by_count":9,"area":null},{"id":"2409.02074","title":"RACONTEUR: A Knowledgeable, Insightful, and Portable LLM-Powered Shell Command Explainer","created":"2024-09-03","cited_by_count":9,"area":null},{"id":"2604.15597","title":"LLMs Corrupt Your Documents When You Delegate","created":"2026-04-17","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":"2407.01646","title":"ESALE: Enhancing Code-Summary Alignment Learning for Source Code Summarization","created":"2024-07-01","cited_by_count":8,"area":null},{"id":"2211.00818","title":"CodePAD: Sequence-based Code Generation with Pushdown Automaton","created":"2022-11-02","cited_by_count":7,"area":null},{"id":"2305.11074","title":"Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization","created":"2023-05-18","cited_by_count":6,"area":"rag"},{"id":"2401.05940","title":"Mutation-based Consistency Testing for Evaluating the Code Understanding Capability of LLMs","created":"2024-01-11","cited_by_count":6,"area":null},{"id":"2103.03457","title":"IOT: Instance-wise Layer Reordering for Transformer Structures","created":"2021-03-05","cited_by_count":5,"area":null},{"id":"2103.11448","title":"Exploiting Method Names to Improve Code Summarization: A Deliberation Multi-Task Learning Approach","created":"2021-03-21","cited_by_count":5,"area":null},{"id":"2103.15361","title":"Embedding API Dependency Graph for Neural Code Generation","created":"2021-03-29","cited_by_count":5,"area":null},{"id":"2109.13073","title":"Improving Stack Overflow question title generation with copying enhanced CodeBERT model and bi-modal information","created":"2021-09-27","cited_by_count":5,"area":null},{"id":"2204.12916","title":"GypSum: Learning Hybrid Representations for Code Summarization","created":"2022-04-26","cited_by_count":5,"area":null},{"id":"2305.14459","title":"Advancing Precise Outline-Conditioned Text Generation with Task Duality and Explicit Outline Control","created":"2023-05-23","cited_by_count":5,"area":null},{"id":"2310.14211","title":"LUNA: A Model-Based Universal Analysis Framework for Large Language Models","created":"2023-10-22","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":"2111.08874","title":"GN-Transformer: Fusing Sequence and Graph Representation for Improved Code Summarization","created":"2021-11-17","cited_by_count":3,"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":"2212.05773","title":"A Survey on Natural Language Processing for Programming","created":"2022-12-12","cited_by_count":3,"area":null},{"id":"2309.02326","title":"Revisiting File Context for Source Code Summarization","created":"2023-09-05","cited_by_count":3,"area":null},{"id":"2404.05767","title":"CSA-Trans: Code Structure Aware Transformer for AST","created":"2024-04-07","cited_by_count":3,"area":null},{"id":"2409.02139","title":"The Role of Transformer Models in Advancing Blockchain Technology: A Systematic Survey","created":"2024-09-02","cited_by_count":3,"area":null},{"id":"2303.01645","title":"APIContext2Com: Code Comment Generation by Incorporating Pre-Defined API Documentation","created":"2023-03-03","cited_by_count":2,"area":null},{"id":"2112.00663","title":"Graph Conditioned Sparse-Attention for Improved Source Code Understanding","created":"2021-12-01","cited_by_count":1,"area":null},{"id":"2204.04686","title":"DISK: Domain-constrained Instance Sketch for Math Word Problem Generation","created":"2022-04-10","cited_by_count":1,"area":null},{"id":"2204.09654","title":"LAMNER: Code Comment Generation Using Character Language Model and Named Entity Recognition","created":"2022-04-05","cited_by_count":1,"area":null},{"id":"2206.08713","title":"Evaluating the Impact of Source Code Parsers on ML4SE Models","created":"2022-06-17","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":"2407.08890","title":"DeepCodeProbe: Towards Understanding What Models Trained on Code Learn","created":"2024-07-11","cited_by_count":1,"area":null},{"id":"2505.09062","title":"Variational Prefix Tuning for Diverse and Accurate Code Summarization Using Pre-trained Language Models","created":"2025-05-14","cited_by_count":1,"area":null},{"id":"2201.08310","title":"Meta Learning for Code Summarization","created":"2022-01-20","cited_by_count":0,"area":null},{"id":"2208.09998","title":"Antecedent Predictions Are More Important Than You Think: An Effective Method for Tree-Based Code Generation","created":"2022-08-22","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}],"next_cursor":null}