Image de couverture de livre

Heterogeneous Directed Hypergraph Neural Network over abstract syntax tree (AST) for Code Classification

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Yang, Guang, Jin, Tiancheng, Dou, Liang
Format:	Preprint
Publié:	2023
Sujets:	Software Engineering Artificial Intelligence Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

HGAdapter: Hypergraph-based Adapters in Language Models for Code Summarization and Clone Detection
par: Yang, Guang, et autres
Publié: (2025)

AST-PAC: AST-guided Membership Inference for Code
par: Koohestani, Roham, et autres
Publié: (2026)

AI-Driven Code Refactoring: Using Graph Neural Networks to Enhance Software Maintainability
par: Bandarupalli, Gopichand
Publié: (2025)

AST-Enhanced or AST-Overloaded? The Surprising Impact of Hybrid Graph Representations on Code Clone Detection
par: Zhang, Zixian, et autres
Publié: (2025)

Functional Overlap Reranking for Neural Code Generation
par: To, Hung Quoc, et autres
Publié: (2023)

CSA-Trans: Code Structure Aware Transformer for AST
par: Oh, Saeyoon, et autres
Publié: (2024)

GREPO: A Benchmark for Graph Neural Networks on Repository-Level Bug Localization
par: Wang, Juntong, et autres
Publié: (2026)

CodeFuse-13B: A Pretrained Multi-lingual Code Large Language Model
par: Di, Peng, et autres
Publié: (2023)

NeuFair: Neural Network Fairness Repair with Dropout
par: Dasu, Vishnu Asutosh, et autres
Publié: (2024)

Monitizer: Automating Design and Evaluation of Neural Network Monitors
par: Azeem, Muqsit, et autres
Publié: (2024)

Protocode: Prototype-Driven Interpretability for Code Generation in LLMs
par: Bodla, Krishna Vamshi, et autres
Publié: (2025)

Learning to Parallelize with OpenMP by Augmented Heterogeneous AST Representation
par: Chen, Le, et autres
Publié: (2023)

CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X
par: Zheng, Qinkai, et autres
Publié: (2023)

Graph Neural Networks based Log Anomaly Detection and Explanation
par: Li, Zhong, et autres
Publié: (2023)

SoundnessBench: A Soundness Benchmark for Neural Network Verifiers
par: Zhou, Xingjian, et autres
Publié: (2024)

Analysing the Behaviour of Tree-Based Neural Networks in Regression Tasks
par: Samoaa, Peter, et autres
Publié: (2024)

RBT4DNN: Requirements-based Testing of Neural Networks
par: Mozumder, Nusrat Jahan, et autres
Publié: (2025)

Talking with Verifiers: Automatic Specification Generation for Neural Network Verification
par: Elboher, Yizhak Y., et autres
Publié: (2026)

Your Code Agent Can Grow Alongside You with Structured Memory
par: Deng, Yi-Xuan, et autres
Publié: (2026)

Beyond Output Correctness: Benchmarking and Evaluating Large Language Model Reasoning in Coding Tasks
par: Li, Yuangang, et autres
Publié: (2026)

Unlock the Correlation between Supervised Fine-Tuning and Reinforcement Learning in Training Code Large Language Models
par: Chen, Jie, et autres
Publié: (2024)

Debugging and Runtime Analysis of Neural Networks with VLMs (A Case Study)
par: Hu, Boyue Caroline, et autres
Publié: (2025)

Toward a Theory of Causation for Interpreting Neural Code Models
par: Palacio, David N., et autres
Publié: (2023)

VeriScale: Adversarial Test-Suite Scaling for Verifiable Code Generation
par: Bai, Yifan, et autres
Publié: (2026)

Automated Cloud Infrastructure-as-Code Reconciliation with AI Agents
par: Yang, Zhenning, et autres
Publié: (2025)

First Three Years of the International Verification of Neural Networks Competition (VNN-COMP)
par: Brix, Christopher, et autres
Publié: (2023)

SimCert: Probabilistic Certification for Behavioral Similarity in Deep Neural Network Compression
par: Li, Jingyang, et autres
Publié: (2026)

CodeTaste: Can LLMs Generate Human-Level Code Refactorings?
par: Thillen, Alex, et autres
Publié: (2026)

miniCodeProps: a Minimal Benchmark for Proving Code Properties
par: Lohn, Evan, et autres
Publié: (2024)

Relative Positioning Based Code Chunking Method For Rich Context Retrieval In Repository Level Code Completion Task With Code Language Model
par: Rahman, Imranur, et autres
Publié: (2025)

Detecting and Correcting Hallucinations in LLM-Generated Code via Deterministic AST Analysis
par: Khati, Dipin, et autres
Publié: (2026)

ZnTrack -- Data as Code
par: Zills, Fabian, et autres
Publié: (2024)

Call Me Maybe: Enhancing JavaScript Call Graph Construction using Graph Neural Networks
par: Bhuiyan, Masudul Hasan Masud, et autres
Publié: (2025)

On LLMs' Internal Representation of Code Correctness
par: Ribeiro, Francisco, et autres
Publié: (2025)

Optimizing AI-Assisted Code Generation
par: Torka, Simon, et autres
Publié: (2024)

Operational Robustness of LLMs on Code Generation
par: Paul, Debalina Ghosh, et autres
Publié: (2026)

Can Coding Agents Be General Agents?
par: Ivanov, Maksim, et autres
Publié: (2026)

Co-Located Tests, Better AI Code: How Test Syntax Structure Affects Foundation Model Code Generation
par: Jacopin, Éric
Publié: (2026)

I Know Which LLM Wrote Your Code Last Summer: LLM generated Code Stylometry for Authorship Attribution
par: Bisztray, Tamas, et autres
Publié: (2025)

Clover: Closed-Loop Verifiable Code Generation
par: Sun, Chuyue, et autres
Publié: (2023)