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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
An Empirical Study on Capability of Large Language Models in Understanding Code Semantics
WRDScore: New Metric for Evaluation of Natural Language Generation Models
Studying Vulnerable Code Entities in R
TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree Transformation
Evaluating the Impact of Source Code Parsers on ML4SE Models
Assessing Project-Level Fine-Tuning of ML4SE Models
Syntax-Guided Program Reduction for Understanding Neural Code Intelligence Models
Extracting Label-specific Key Input Features for Neural Code Intelligence Models
Code2Snapshot: Using Code Snapshots for Learning Representations of Source Code
Memorization and Generalization in Neural Code Intelligence Models
Understanding Neural Code Intelligence Through Program Simplification
PSIMiner: A Tool for Mining Rich Abstract Syntax Trees from Code
Universal Representation for Code
InferCode: Self-Supervised Learning of Code Representations by Predicting Subtrees
Self-Supervised Contrastive Learning for Code Retrieval and Summarization via Semantic-Preserving Transformations
Towards Demystifying Dimensions of Source Code Embeddings
On the Generalizability of Neural Program Models with respect to Semantic-Preserving Program Transformations
Contrastive Code Representation Learning
Learning Semantic Program Embeddings with Graph Interval Neural Network
Evaluation of Generalizability of Neural Program Analyzers under Semantic-Preserving Transformations
Embedding Java Classes with code2vec: Improvements from Variable Obfuscation
Testing Neural Program Analyzers
Learning Blended, Precise Semantic Program Embeddings
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.