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Source Code Summarization
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Code Summarization is a task that tries to comprehend code and automatically generate descriptions directly from the source code.
Source: Improving Automatic Source Code Summarization via Deep Reinforcement Learning
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Do Current Language Models Support Code Intelligence for R Programming Language?
Source Code Summarization in the Era of Large Language Models
An Empirical Study on Capability of Large Language Models in Understanding Code Semantics
ESALE: Enhancing Code-Summary Alignment Learning for Source Code Summarization
WRDScore: New Metric for Evaluation of Natural Language Generation Models
On Training a Neural Network to Explain Binaries
Studying Vulnerable Code Entities in R
A Prompt Learning Framework for Source Code Summarization
TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree Transformation
Revisiting File Context for Source Code Summarization
Distilled GPT for Source Code Summarization
EditSum: A Retrieve-and-Edit Framework for Source Code Summarization
Semantic Similarity Loss for Neural Source Code Summarization
Statement-based Memory for Neural Source Code Summarization
Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization
Towards Modeling Human Attention from Eye Movements for Neural Source Code Summarization
Evaluating the Impact of Source Code Parsers on ML4SE Models
An Extractive-and-Abstractive Framework for Source Code Summarization
Assessing Project-Level Fine-Tuning of ML4SE Models
Syntax-Guided Program Reduction for Understanding Neural Code Intelligence Models
M2TS: Multi-Scale Multi-Modal Approach Based on Transformer for Source Code Summarization
Extracting Label-specific Key Input Features for Neural Code Intelligence Models
Source Code Summarization with Structural Relative Position Guided Transformer
Compositionality-Aware Graph2Seq Learning
Meta Learning for Code Summarization
Assemble Foundation Models for Automatic Code Summarization
Leveraging Unsupervised Learning to Summarize APIs Discussed in Stack Overflow
GraphSearchNet: Enhancing GNNs via Capturing Global Dependencies for Semantic Code Search
Code2Snapshot: Using Code Snapshots for Learning Representations of Source Code
On the Evaluation of Neural Code Summarization
Memorization and Generalization in Neural Code Intelligence Models
Code to Comment Translation: A Comparative Study on Model Effectiveness & Errors
Understanding Neural Code Intelligence Through Program Simplification
CoDesc: A Large Code-Description Parallel Dataset
Code Structure Guided Transformer for Source Code Summarization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.