https://github.com/amazon-science/function-call-argument-completion
https://github.com/amazon-science/function-call-argument-completion
Science Score: 13.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (4.5%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: amazon-science
- License: apache-2.0
- Language: Python
- Default Branch: main
- Size: 99.6 KB
Statistics
- Stars: 8
- Watchers: 4
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion
This is the experiment code for our AAAI 2023 paper "Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion".
Data
Please refer to https://registry.opendata.aws/pyenvs-and-callargs/ for downloading PYENVS and CALLARGS.
Code
Please check the sub-folder for more details:
generate folder contains the codes for generating PYENVS and CALLARGS.
training folder contains the codes for the experiments on CALLARGS.
Citation
You are more than welcome to cite our paper:
@article{pei2023better,
title={Better context makes better code language models: A case study on function call argument completion},
author={Pei, Hengzhi and Zhao, Jinman and Lausen, Leonard and Zha, Sheng and Karypis, George},
journal={arXiv preprint arXiv:2306.00381},
year={2023}
}
Owner
- Name: Amazon Science
- Login: amazon-science
- Kind: organization
- Website: https://amazon.science
- Twitter: AmazonScience
- Repositories: 80
- Profile: https://github.com/amazon-science
GitHub Events
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Last Year
- Watch event: 1
Issues and Pull Requests
Last synced: over 1 year ago
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- Total issue authors: 0
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- Average comments per issue: 0
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Past Year
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