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Code Generation

23 papers with code ยท Computer Code

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IntelliCode Compose: Code Generation Using Transformer

16 May 2020

In software development through integrated development environments (IDEs), code completion is one of the most widely used features.

CODE GENERATION

Semantic Scaffolds for Pseudocode-to-Code Generation

12 May 2020

We propose a method for program generation based on semantic scaffolds, lightweight structures representing the high-level semantic and syntactic composition of a program.

CODE GENERATION

Taming the Expressiveness and Programmability of Graph Analytical Queries

20 Apr 2020

Graph database has enjoyed a boom in the last decade, and graph queries accordingly gain a lot of attentions from both the academia and industry.

CODE GENERATION

Leveraging Code Generation to Improve Code Retrieval and Summarization via Dual Learning

24 Feb 2020

Since both tasks aim to model the association between natural language and programming language, recent studies have combined these two tasks to improve their performance.

CODE GENERATION CODE SUMMARIZATION MULTI-TASK LEARNING

LIMITS: Lightweight Machine Learning for IoT Systems with Resource Limitations

28 Jan 2020

Exploiting big data knowledge on small devices will pave the way for building truly cognitive Internet of Things (IoT) systems.

CODE GENERATION

An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices

20 Jan 2020

Weight pruning has been widely acknowledged as a straightforward and effective method to eliminate redundancy in Deep Neural Networks (DNN), thereby achieving acceleration on various platforms.

CODE GENERATION

Structural Language Models for Any-Code Generation

ICLR 2020

We introduce a new approach to AnyGen that leverages the strict syntax of programming languages to model a code snippet as tree structural language modeling (SLM).

CODE GENERATION LANGUAGE MODELLING

PatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning

1 Jan 2020

Weight pruning of DNNs is proposed, but existing schemes represent two extremes in the design space: non-structured pruning is fine-grained, accurate, but not hardware friendly; structured pruning is coarse-grained, hardware-efficient, but with higher accuracy loss.

CODE GENERATION MODEL COMPRESSION

GANCoder: An Automatic Natural Language-to-Programming Language Translation Approach based on GAN

2 Dec 2019

We propose GANCoder, an automatic programming approach based on Generative Adversarial Networks (GAN), which can generate the same functional and logical programming language codes conditioned on the given natural language utterances.

CODE GENERATION