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Code Summarization

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Showing 76–100 of 163 papers

TitleStatusHype
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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