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Natural language generation and understanding of big code for AI-assisted programming: A review
This paper provides a comprehensive review of the literature concerning the utilization of
Natural Language Processing (NLP) techniques, with a particular focus on transformer …
Natural Language Processing (NLP) techniques, with a particular focus on transformer …
Applications of artificial intelligence in engineering and manufacturing: a systematic review
Engineering and manufacturing processes and systems designs involve many challenges,
such as dynamism, chaotic behaviours, and complexity. Of late, the arrival of big data, high …
such as dynamism, chaotic behaviours, and complexity. Of late, the arrival of big data, high …
The programmer's assistant: Conversational interaction with a large language model for software development
Large language models (LLMs) have recently been applied in software engineering to
perform tasks such as translating code between programming languages, generating code …
perform tasks such as translating code between programming languages, generating code …
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Language models demonstrate both quantitative improvement and new qualitative
capabilities with increasing scale. Despite their potentially transformative impact, these new …
capabilities with increasing scale. Despite their potentially transformative impact, these new …
Palm: Scaling language modeling with pathways
Large language models have been shown to achieve remarkable performance across a
variety of natural language tasks using few-shot learning, which drastically reduces the …
variety of natural language tasks using few-shot learning, which drastically reduces the …
Retrieval-based prompt selection for code-related few-shot learning
Large language models trained on massive code corpora can generalize to new tasks
without the need for task-specific fine-tuning. In few-shot learning, these models take as …
without the need for task-specific fine-tuning. In few-shot learning, these models take as …
An empirical evaluation of GitHub copilot's code suggestions
GitHub and OpenAI recently launched Copilot, an" AI pair programmer" that utilizes the
power of Natural Language Processing, Static Analysis, Code Synthesis, and Artificial …
power of Natural Language Processing, Static Analysis, Code Synthesis, and Artificial …
Large language models meet nl2code: A survey
The task of generating code from a natural language description, or NL2Code, is considered
a pressing and significant challenge in code intelligence. Thanks to the rapid development …
a pressing and significant challenge in code intelligence. Thanks to the rapid development …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Program synthesis with large language models
This paper explores the limits of the current generation of large language models for
program synthesis in general purpose programming languages. We evaluate a collection of …
program synthesis in general purpose programming languages. We evaluate a collection of …