Baselines from the CodeSearchNet models for code search were trained and tuned by Luis Perez and Sudhardshan Viswanathan Data analysis and
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[PDF] report - CS230 Deep Learning - Stanford University
Baselines from the CodeSearchNet models for code search were trained and tuned by Luis Perez and Sudhardshan Viswanathan Data analysis and
[PDF] Semantic Code Search with Neural Bag-of-Words and Graph
CodeSearchNet Challenge Our Neural Bag-of-Words encoder improves the MRR by 4 38 for Python and 4 98 for Java The Graph Convolutional Network
[PDF] Semantic code search using Code2Vec: A bag-of-paths - UWSpace
Migrating CodeSearchNet [19] benchmark neural models in Tensorflow 2 0 • Implementing Code2Vec [3] into CodeSearchNet and evaluating its performance
[PDF] A Pre-Trained Model for Programming and Natural Languages
16 nov 2020 · related code from a collection of codes We con- duct experiments on the CodeSearchNet corpus (Husain et al , 2019) 4 We follow the official
[PDF] Multi-modal Neural Representations for Semantic Code Search - DiVA
These baseline models prepared by the CodeSearchNet Challenge are rather strong, therefore, we would investigate how well these baseline models perform
[PDF] Semantic Robustness of Models of Source Code - Computer
(i) code2seq's java-small dataset (c2s/java-small) (Alon et al , 2018), (ii) GitHub's CodeSearchNet Java and Python datasets (csn/java, csn/python) (Husain et al ,
[PDF] Survey of Embedding Performance for Semantic Code - Sean Kelley
In their paper introducing the CodeSearchNet challenge, the GitHub team defined their baseline neural model architecture which relies heavily on embeddings
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