{"total":62,"rows":[{"id":"2109.00859","title":"CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation","created":"2021-09-02","cited_by_count":906,"area":null},{"id":"2206.06488","title":"Multimodal Learning with Transformers: A Survey","created":"2022-06-13","cited_by_count":400,"area":null},{"id":"2202.13169","title":"A Systematic Evaluation of Large Language Models of Code","created":"2022-02-26","cited_by_count":363,"area":null},{"id":"2106.05234","title":"Do Transformers Really Perform Bad for Graph Representation?","created":"2021-06-09","cited_by_count":320,"area":null},{"id":"2108.04556","title":"SynCoBERT: Syntax-Guided Multi-Modal Contrastive Pre-Training for Code Representation","created":"2021-08-10","cited_by_count":63,"area":null},{"id":"2206.08474","title":"XLCoST: A Benchmark Dataset for Cross-lingual Code Intelligence","created":"2022-06-16","cited_by_count":56,"area":null},{"id":"2302.00049","title":"Transformers Meet Directed Graphs","created":"2023-01-31","cited_by_count":40,"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":"2308.14731","title":"Distilled GPT for Source Code Summarization","created":"2023-08-28","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":"2103.11599","title":"Project-Level Encoding for Neural Source Code Summarization of Subroutines","created":"2021-03-22","cited_by_count":24,"area":null},{"id":"2201.10608","title":"DOM-LM: Learning Generalizable Representations for HTML Documents","created":"2022-01-25","cited_by_count":24,"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":"2205.11739","title":"Deep Learning Meets Software Engineering: A Survey on Pre-Trained Models of Source Code","created":"2022-05-24","cited_by_count":21,"area":null},{"id":"2110.03868","title":"Towards Learning (Dis)-Similarity of Source Code from Program Contrasts","created":"2021-10-08","cited_by_count":17,"area":null},{"id":"2204.10049","title":"On Distribution Shift in Learning-based Bug Detectors","created":"2022-04-21","cited_by_count":15,"area":null},{"id":"2203.09707","title":"M2TS: Multi-Scale Multi-Modal Approach Based on Transformer for Source Code Summarization","created":"2022-03-18","cited_by_count":14,"area":null},{"id":"2305.05779","title":"Learning to Parallelize with OpenMP by Augmented Heterogeneous AST Representation","created":"2023-05-09","cited_by_count":14,"area":null},{"id":"2307.13018","title":"The potential of LLMs for coding with low-resource and domain-specific programming languages","created":"2023-07-24","cited_by_count":11,"area":null},{"id":"2504.08734","title":"Towards an Understanding of Context Utilization in Code Intelligence","created":"2025-04-11","cited_by_count":10,"area":null},{"id":"2112.08273","title":"Programming Knowledge Tracing: A Comprehensive Dataset and A New Model","created":"2021-12-11","cited_by_count":9,"area":null},{"id":"2305.09773","title":"Towards Modeling Human Attention from Eye Movements for Neural Source Code Summarization","created":"2023-05-16","cited_by_count":8,"area":null},{"id":"2302.03908","title":"Syntax and Domain Aware Model for Unsupervised Program Translation","created":"2023-02-08","cited_by_count":7,"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":"2208.08643","title":"Learning Program Representations with a Tree-Structured Transformer","created":"2022-08-18","cited_by_count":6,"area":null},{"id":"2210.04633","title":"CAT-probing: A Metric-based Approach to Interpret How Pre-trained Models for Programming Language Attend Code Structure","created":"2022-10-07","cited_by_count":6,"area":null},{"id":"2109.01942","title":"On the ability of monolingual models to learn language-agnostic representations","created":"2021-09-04","cited_by_count":5,"area":null},{"id":"2206.04730","title":"A Neural Network Architecture for Program Understanding Inspired by Human Behaviors","created":"2022-05-10","cited_by_count":5,"area":null},{"id":"2210.07228","title":"Language Model Decoding as Likelihood-Utility Alignment","created":"2022-10-13","cited_by_count":5,"area":null},{"id":"2308.07429","title":"Semantic Similarity Loss for Neural Source Code Summarization","created":"2023-08-14","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":"2206.14175","title":"InvAASTCluster: On Applying Invariant-Based Program Clustering to Introductory Programming Assignments","created":"2022-06-28","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":"2105.14038","title":"Learning to Extend Program Graphs to Work-in-Progress Code","created":"2021-05-28","cited_by_count":3,"area":null},{"id":"2111.04473","title":"Senatus -- A Fast and Accurate Code-to-Code Recommendation Engine","created":"2021-11-05","cited_by_count":3,"area":null},{"id":"2205.10674","title":"NS3: Neuro-Symbolic Semantic Code Search","created":"2022-05-21","cited_by_count":3,"area":null},{"id":"2206.08726","title":"Evaluation of Contrastive Learning with Various Code Representations for Code Clone Detection","created":"2022-06-17","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":"2305.13504","title":"Neural Machine Translation for Code Generation","created":"2023-05-22","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":"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":"2404.07471","title":"Structure-aware Fine-tuning for Code Pre-trained Models","created":"2024-04-11","cited_by_count":3,"area":null},{"id":"2206.03333","title":"Assessing Project-Level Fine-Tuning of ML4SE Models","created":"2022-06-07","cited_by_count":2,"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":"2304.13350","title":"Neuro-symbolic Zero-Shot Code Cloning with Cross-Language Intermediate Representation","created":"2023-04-26","cited_by_count":2,"area":null},{"id":"2307.11709","title":"Statement-based Memory for Neural Source Code Summarization","created":"2023-07-21","cited_by_count":2,"area":null},{"id":"2501.12617","title":"Deep Learning-Based Identification of Inconsistent Method Names: How Far Are We?","created":"2025-01-22","cited_by_count":2,"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":"2112.00663","title":"Graph Conditioned Sparse-Attention for Improved Source Code Understanding","created":"2021-12-01","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":"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":"2303.09062","title":"Knowledge Transfer for Pseudo-code Generation from Low Resource Programming Language","created":"2023-03-16","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":"2205.08585","title":"CV4Code: Sourcecode Understanding via Visual Code Representations","created":"2022-05-11","cited_by_count":0,"area":null},{"id":"2208.03922","title":"CSSAM:Code Search via Attention Matching of Code Semantics and Structures","created":"2022-08-08","cited_by_count":0,"area":null},{"id":"2303.03540","title":"Judging Adam: Studying the Performance of Optimization Methods on ML4SE Tasks","created":"2023-03-06","cited_by_count":0,"area":null},{"id":"2307.13014","title":"Graph Neural Networks For Mapping Variables Between Programs -- Extended Version","created":"2023-07-24","cited_by_count":0,"area":null},{"id":"2312.05531","title":"KEN: Kernel Extensions using Natural Language","created":"2023-12-09","cited_by_count":0,"area":null},{"id":"2505.19392","title":"Simple and Effective Baselines for Code Summarisation Evaluation","created":"2025-05-26","cited_by_count":0,"area":null}],"next_cursor":null}