Type-IV Code Clone Detection via Layer-Wise Non-Contrastive Representation Learning

arXiv:2609.17338 · cs.SE, cs.LG · Submitted 2026-09-15 · Read on arXiv

cs.SE, cs.LG

Submitted: 2026-09-15

Updated: 2026-09-15

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Embeddings — 33× in this paper · explained in 2 episodes
• Representation Learning — 33× in this paper · explained in 2 episodes
• Consistency — 31× in this paper · explained in 3 episodes
• Transformer — 25× in this paper · explained in 2 episodes
• Contrastive Learning — 19× in this paper · explained in 5 episodes
• AUC — 17× in this paper · explained in 2 episodes
• Regularization — 12× in this paper · explained in 3 episodes
• Ablation — 9× in this paper · explained in 1 episode
• Cosine Similarity — 9× in this paper · explained in 3 episodes
• F1 Score — 6× in this paper · explained in 3 episodes
• Ablation study — 5× in this paper · explained in 1 episode
• Benchmark — 5× in this paper · explained in 2 episodes
• Generalization — 4× in this paper · explained in 13 episodes
• International Conference on Automated Software Engineering — 4× in this paper
• Alignment — 3× in this paper · explained in 1 episode
• Generalizability — 3× in this paper · explained in 6 episodes
• Transfer Learning — 3× in this paper · explained in 10 episodes
• Abstract Syntax Tree — 2× in this paper
• Accuracy — 2× in this paper · explained in 1 episode
• Aggregation — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• Continual Learning — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generalized Estimating Equations — 2× in this paper
• International Conference on Software Engineering — 2× in this paper
• International Workshop on Software Clones — 2× in this paper
• Redundancy — 2× in this paper · explained in 2 episodes
• Semantic Similarity — 2× in this paper · explained in 2 episodes
• Transferability — 2× in this paper · explained in 4 episodes
• Vector Representations — 2× in this paper · explained in 2 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Area Under the Curve — 1× in this paper
• Area Under the Curve (AUC) — 1× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Ensemble Learning — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Program Dependence Graphs — 1× in this paper
• Robustness — 1× in this paper · explained in 5 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes

Sources

• A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment
• CodeBERT: A Pre-Trained Model for Programming and Natural Languages
• VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning
• A Literature Study of Embeddings on Source Code
• Path-Based Function Embedding and its Application to Specification Mining
• How the Misuse of a Dataset Harmed Semantic Clone Detection
• LLMs' Reshaping of People, Processes, Products, and Society in Software Development: A Comprehensive Exploration with Early Adopters

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