Sep 25, 2020 · Code recommendation systems for software engineering are designed to accelerate the development of large software projects. A classical ...
The idea behind Extended Network is to combine neural and prob- abilistic language models for code modeling and prediction. Ex- tended Network is a way to ...
A method by Li et al., (IJCAI 2018) uses deep learning methods, in detail a Recurrent Neural Network coupled with a Pointer Network. We compare these two ...
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Jul 12, 2024 · We propose a methodology named One-shot Correction to mitigate these issues in natural language to code translation models with no additional re-training.
This paper presents a novel approach, CodePrompt, which utilizes rich knowledge recalled from a pre-trained model by prompt learning and an attention mechanism
Jul 2, 2019 · Traditional machine learning can be better than a deep neural net when your constraints are extremely high, or when your objective is fuzzy. If ...
Combining theoretical modelling and machine learning approaches
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The current study explores potential synergetic effects of these two general approaches both for predictive accuracy and theoretical understanding.
Jun 19, 2018 · 1. Verify that your code is bug free. There's a saying among writers that "All writing is re-writing" -- that is, the greater part of writing is revising.
Jan 31, 2024 · Let's break down the ML vs. LLM debate and delve into their distinctions, functionalities, and when one is preferable over the other in AI ...
Nov 1, 2022 · Machine learning (ML) approaches for code ... Improving code recommendations by combining neural and classical machine learning approaches.