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Octopack: Instruction tuning code large language models
N Muennighoff, Q Liu, A Zebaze, Q Zheng… - … 2023 Workshop on …, 2023 - openreview.net
Finetuning large language models (LLMs) on instructions leads to vast performance
improvements on natural language tasks. We apply instruction tuning using code …
improvements on natural language tasks. We apply instruction tuning using code …
MultiPL-E: a scalable and polyglot approach to benchmarking neural code generation
Large language models have demonstrated the ability to generate both natural language
and programming language text. Although contemporary code generation models are …
and programming language text. Although contemporary code generation models are …
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 …
Generative software engineering
The rapid development of deep learning techniques, improved computational power, and
the availability of vast training data have led to significant advancements in pre-trained …
the availability of vast training data have led to significant advancements in pre-trained …
“What it wants me to say”: Bridging the abstraction gap between end-user programmers and code-generating large language models
MX Liu, A Sarkar, C Negreanu, B Zorn… - Proceedings of the …, 2023 - dl.acm.org
Code-generating large language models map natural language to code. However, only a
small portion of the infinite space of naturalistic utterances is effective at guiding code …
small portion of the infinite space of naturalistic utterances is effective at guiding code …
Multilingual large language model: A survey of resources, taxonomy and frontiers
Multilingual Large Language Models are capable of using powerful Large Language
Models to handle and respond to queries in multiple languages, which achieves remarkable …
Models to handle and respond to queries in multiple languages, which achieves remarkable …
Multi-lingual evaluation of code generation models
B Athiwaratkun, SK Gouda, Z Wang, X Li, Y Tian… - arxiv preprint arxiv …, 2022 - arxiv.org
We present new benchmarks on evaluation code generation models: MBXP and Multilingual
HumanEval, and MathQA-X. These datasets cover over 10 programming languages and are …
HumanEval, and MathQA-X. These datasets cover over 10 programming languages and are …
Unifying the perspectives of nlp and software engineering: A survey on language models for code
Z Zhang, C Chen, B Liu, C Liao, Z Gong, H Yu… - arxiv preprint arxiv …, 2023 - arxiv.org
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 …
language models, covering 70+ models, 40+ evaluation tasks, 180+ datasets, and 900 …
Execution-based evaluation for open-domain code generation
To extend the scope of coding queries to more realistic settings, we propose ODEX, the first
Open-Domain EXecution-based natural language (NL) to Python code generation dataset …
Open-Domain EXecution-based natural language (NL) to Python code generation dataset …
A survey of neural code intelligence: Paradigms, advances and beyond
Neural Code Intelligence--leveraging deep learning to understand, generate, and optimize
code--holds immense potential for transformative impacts on the whole society. Bridging the …
code--holds immense potential for transformative impacts on the whole society. Bridging the …