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Natural Language Processing Models That Automate Programming Will Transform Chemistry Research and Teaching
Natural language processing models have emerged that can generate usable software and automate a number of programming tasks with high fidelity.
Statistical Mechanics Chemical Physics
Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming
AI code generators like OpenAI Codex have the potential to assist novice programmers by generating code from natural language descriptions, however, over-reliance might negatively impact learning and retention.
Human-Computer Interaction
Primer: Searching for Efficient Transformers for Language Modeling
For example, at a 500M parameter size, Primer improves the original T5 architecture on C4 auto-regressive language modeling, reducing the training cost by 4X.
Ranked #1 on
Language Modelling
on C4
ChatDev: Communicative Agents for Software Development
Numerous studies used deep learning to improve specific phases in a waterfall model, such as design, coding, and testing.
Applications of Deep Neural Networks with Keras
Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output.
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
We present GluonCV and GluonNLP, the deep learning toolkits for computer vision and natural language processing based on Apache MXNet (incubating).
Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
In this work we systematically review the recent advancements in software engineering with language models, covering 70+ models, 40+ evaluation tasks, 180+ datasets, and 900 related works.
Unsupervised Translation of Programming Languages
We train our model on source code from open source GitHub projects, and show that it can translate functions between C++, Java, and Python with high accuracy.
Non-linear Pattern Matching with Backtracking for Non-free Data Types
Although many studies on pattern matching and implementations for practical programming languages have been proposed so far, we observe that none of these studies satisfy all the criteria of practical pattern matching, which are as follows: i) efficiency of the backtracking algorithm for non-linear patterns, ii) extensibility of matching process, and iii) polymorphism in patterns.
Programming Languages
