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Code Summarization

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Showing 51–100 of 163 papers

TitleStatusHype
An Exploratory Study on Code Attention in BERT—0
An LLM-as-Judge Metric for Bridging the Gap with Human Evaluation in SE Tasks—0
AST-MHSA : Code Summarization using Multi-Head Self-Attention—0
A Structural Transformer with Relative Positions in Trees for Code-to-Sequence Tasks—0
AST-Transformer: Encoding Abstract Syntax Trees Efficiently for Code Summarization—0
A Survey on Pretrained Language Models for Neural Code Intelligence—0
Automatic Code Summarization via ChatGPT: How Far Are We?—0
Automatic Source Code Summarization via Reinforcement Learning—0
Benchmarking Causal Study to Interpret Large Language Models for Source Code—0
Can Large Language Models Understand Intermediate Representations?—0
Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering—0
Code-Craft: Hierarchical Graph-Based Code Summarization for Enhanced Context Retrieval—0
Code Representation Learning with Prüfer Sequences—0
Code Structure Guided Transformer for Source Code Summarization—0
Code Summarization: Do Transformers Really Understand Code?—0
Pre-Training Representations of Binary Code Using Contrastive Learning—0
Commenting Higher-level Code Unit: Full Code, Reduced Code, or Hierarchical Code Summarization—0
Cross-Lingual Transfer Learning for Statistical Type Inference—0
DeepCodeProbe: Towards Understanding What Models Trained on Code Learn—0
WheaCha: A Method for Explaining the Predictions of Models of Code—0
Demystifying What Code Summarization Models Learned—0
DocGen: Generating Detailed Parameter Docstrings in Python—0
Do Current Language Models Support Code Intelligence for R Programming Language?—0
Do Machines and Humans Focus on Similar Code? Exploring Explainability of Large Language Models in Code Summarization—0
EditSum: A Retrieve-and-Edit Framework for Source Code Summarization—0
Self-Supervised Contrastive Learning for Code Retrieval and Summarization via Semantic-Preserving Transformations—0
Energy-Conscious LLM Decoding: Impact of Text Generation Strategies on GPU Energy Consumption—0
Enhancing Code LLM Training with Programmer Attention—0
Calibration of Large Language Models on Code Summarization—0
ESALE: Enhancing Code-Summary Alignment Learning for Source Code Summarization—0
ETF: An Entity Tracing Framework for Hallucination Detection in Code Summaries—0
EVALOOP: Assessing LLM Robustness in Programming from a Self-consistency Perspective—0
Evaluation of Contrastive Learning with Various Code Representations for Code Clone Detection—0
Exploiting Method Names to Improve Code Summarization: A Deliberation Multi-Task Learning Approach—0
Exploring Distributional Shifts in Large Language Models for Code Analysis—0
Greener yet Powerful: Taming Large Code Generation Models with Quantization—0
Hierarchical Repository-Level Code Summarization for Business Applications Using Local LLMs—0
Icing on the Cake: Automatic Code Summarization at Ericsson—0
Automatic Semantic Augmentation of Language Model Prompts (for Code Summarization)—0
Is ChatGPT the Ultimate Programming Assistant -- How far is it?—0
Laminar: A New Serverless Stream-based Framework with Semantic Code Search and Code Completion—0
Large Language Models are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Tasks—0
Large Language Models for Code Summarization—0
LEANCODE: Understanding Models Better for Code Simplification of Pre-trained Large Language Models—0
Learning code summarization from a small and local dataset—0
Learning Sequential and Structural Information for Source Code Summarization—0
Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow—0
HierarchyNet: Learning to Summarize Source Code with Heterogeneous Representations—0
Leveraging Code Generation to Improve Code Retrieval and Summarization via Dual Learning—0
Leveraging Deep Learning for Abstractive Code Summarization of Unofficial Documentation—0
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