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20212026
most citedOn the Evaluation of Neural Code Summarization

87 citations · 395 across the 49 of their papers we have counts for

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10 papers · 1 filter

cs.SE2024

SECRET: Towards Scalable and Efficient Code Retrieval via Segmented Deep Hashing

Wenchao Gu, Ensheng Shi, Yanlin Wang +5

Code retrieval, which retrieves code snippets based on users' natural language descriptions, is widely used by developers and plays a pivotal role in real-world software developmen…

cs.SE2024

CoCoST: Automatic Complex Code Generation with Online Searching and Correctness Testing

Xinyi He, Jiaru Zou, Yun Lin +4

Large Language Models have revolutionized code generation ability by converting natural language descriptions into executable code. However, generating complex code within real-wor…

cs.SE2023

SoTaNa: The Open-Source Software Development Assistant

Ensheng Shi, Fengji Zhang, Yanlin Wang +6

Software development plays a crucial role in driving innovation and efficiency across modern societies. To meet the demands of this dynamic field, there is a growing need for an ef…

cs.SE2023★ 1 cited

Towards Efficient Fine-tuning of Pre-trained Code Models: An Experimental Study and Beyond

Ensheng Shi, Yanlin Wang, Hongyu Zhang +4

Recently, fine-tuning pre-trained code models such as CodeBERT on downstream tasks has achieved great success in many software testing and analysis tasks. While effective and preva…

cs.SE2022★ 17 cited

Revisiting Code Search in a Two-Stage Paradigm

Fan Hu, Yanlin Wang, Lun Du +4

With a good code search engine, developers can reuse existing code snippets and accelerate software development process. Current code search methods can be divided into two categor…

cs.SE2022

Tackling Long Code Search with Splitting, Encoding, and Aggregating

Fan Hu, Yanlin Wang, Lun Du +4

Code search with natural language helps us reuse existing code snippets. Thanks to the Transformer-based pretraining models, the performance of code search has been improved signif…

cs.SE2022★ 10 cited

CoCoSoDa: Effective Contrastive Learning for Code Search

Ensheng Shi, Yanlin Wang, Wenchao Gu +5

Code search aims to retrieve semantically relevant code snippets for a given natural language query. Recently, many approaches employing contrastive learning have shown promising r…

cs.SE2022

Accelerating Code Search with Deep Hashing and Code Classification

Wenchao Gu, Yanlin Wang, Lun Du +4

Code search is to search reusable code snippets from source code corpus based on natural languages queries. Deep learning-based methods of code search have shown promising results.…

cs.SE2022★ 6 cited

RACE: Retrieval-Augmented Commit Message Generation

Ensheng Shi, Yanlin Wang, Wei Tao +5

Commit messages are important for software development and maintenance. Many neural network-based approaches have been proposed and shown promising results on automatic commit mess…

cs.SE2021★ 87 cited

On the Evaluation of Neural Code Summarization

Ensheng Shi, Yanlin Wang, Lun Du +5

Source code summaries are important for program comprehension and maintenance. However, there are plenty of programs with missing, outdated, or mismatched summaries. Recently, deep…