SOTAVerified

Source Code Summarization

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–25 of 58 papers

TitleStatusHype
Variational Prefix Tuning for Diverse and Accurate Code Summarization Using Pre-trained Language ModelsCode0
Source Code Summarization in the Era of Large Language ModelsCode1
ESALE: Enhancing Code-Summary Alignment Learning for Source Code Summarization—0
On Training a Neural Network to Explain Binaries—0
A Prompt Learning Framework for Source Code SummarizationCode1
Revisiting File Context for Source Code SummarizationCode0
Distilled GPT for Source Code SummarizationCode0
EditSum: A Retrieve-and-Edit Framework for Source Code Summarization—0
Semantic Similarity Loss for Neural Source Code SummarizationCode0
Statement-based Memory for Neural Source Code SummarizationCode0
Tram: A Token-level Retrieval-augmented Mechanism for Source Code SummarizationCode0
Towards Modeling Human Attention from Eye Movements for Neural Source Code Summarization—0
An Extractive-and-Abstractive Framework for Source Code SummarizationCode0
Modeling Hierarchical Syntax Structure with Triplet Position for Source Code Summarization—0
M2TS: Multi-Scale Multi-Modal Approach Based on Transformer for Source Code SummarizationCode1
Source Code Summarization with Structural Relative Position Guided TransformerCode1
Compositionality-Aware Graph2Seq LearningCode0
Meta Learning for Code Summarization—0
Assemble Foundation Models for Automatic Code SummarizationCode1
Leveraging Unsupervised Learning to Summarize APIs Discussed in Stack OverflowCode0
Meta Learning for Code Summarization—0
Modeling Hierarchical Syntax Structure with Triplet Position for Source Code SummarizationCode0
Retrieval-based Layer-wise Adaptive Transformer for Source Code Summarization—0
GraphSearchNet: Enhancing GNNs via Capturing Global Dependencies for Semantic Code SearchCode1
Learning Sequential and Structural Information for Source Code Summarization—0
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All datasetsDeepCom-JavaParallelCorpus-PythonCoDescCodeSearchNetCodeSearchNet - PythonJava scriptsSummarizing Source Code using a Neural Attention Model - C#Summarizing Source Code using a Neural Attention Model - PythonSummarizing Source Code using a Neural Attention Model - SQL

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AdaMo-noiseBLEU-445.35—Unverified
2AdaMo-basicBLEU-445.3—Unverified
#ModelMetricClaimedVerifiedStatus
1AdaMo-noiseBLEU-434.05—Unverified
2AdaMo-basicBLEU-433.85—Unverified
#ModelMetricClaimedVerifiedStatus
1TransformerBLEU-445.89—Unverified
#ModelMetricClaimedVerifiedStatus
1ContraCodeF117.24—Unverified
#ModelMetricClaimedVerifiedStatus
1AdaMo-basicBLEU-416.46—Unverified
#ModelMetricClaimedVerifiedStatus
1AdaMo-basicBLEU-437.64—Unverified
#ModelMetricClaimedVerifiedStatus
1CodeTrans-MT-LargeSmoothed BLEU-423.57—Unverified
#ModelMetricClaimedVerifiedStatus
1CodeTrans-MT-BaseSmoothed BLEU-413.37—Unverified
#ModelMetricClaimedVerifiedStatus
1CodeTrans-MT-TF-LargeSmoothed BLEU-419.98—Unverified