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[PRE REVIEW]: ai3: A Framework Enabling Algorithmic Selection in Deep Neural Networks #7386

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editorialbot opened this issue Oct 21, 2024 · 25 comments
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pre-review Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning withdrawn

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editorialbot commented Oct 21, 2024

Submitting author: @4imothy (Timothy Cronin)
Repository: https://github.com/KLab-AI3/ai3
Branch with paper.md (empty if default branch):
Version: 0.1.0
Editor: @HaoZeke
Reviewers: Pending
Managing EiC: Chris Vernon

Status

status

Status badge code:

HTML: <a href="https://joss.theoj.org/papers/4a3b4bb9a124d09bb5db437d55b8d74b"><img src="https://joss.theoj.org/papers/4a3b4bb9a124d09bb5db437d55b8d74b/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/4a3b4bb9a124d09bb5db437d55b8d74b/status.svg)](https://joss.theoj.org/papers/4a3b4bb9a124d09bb5db437d55b8d74b)

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Thanks for submitting your paper to JOSS @4imothy. Currently, there isn't a JOSS editor assigned to your paper.

@4imothy if you have any suggestions for potential reviewers then please mention them here in this thread (without tagging them with an @). You can search the list of people that have already agreed to review and may be suitable for this submission.

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@editorialbot editorialbot added pre-review Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning labels Oct 21, 2024
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Hello human, I'm @editorialbot, a robot that can help you with some common editorial tasks.

For a list of things I can do to help you, just type:

@editorialbot commands

For example, to regenerate the paper pdf after making changes in the paper's md or bib files, type:

@editorialbot generate pdf

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Software report:

github.com/AlDanial/cloc v 1.90  T=0.06 s (2068.1 files/s, 157883.1 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          59            761            198           3469
C++                             24            212             24           1523
C/C++ Header                    15            149            196            761
Objective-C++                    2             50              3            380
reStructuredText                 7            115            424            218
CMake                            2             34              0            194
YAML                             4             13              0            120
Markdown                         1             15              0            115
TeX                              1              3              0             58
TOML                             1              4              0             39
DOS Batch                        1              8              1             26
Bourne Shell                     1              2              0             14
JSON                             1              0              0             12
make                             1              4              7              9
-------------------------------------------------------------------------------
SUM:                           120           1370            853           6938
-------------------------------------------------------------------------------

Commit count by author:

   189	Timothy Cronin
     5	GitHub Actions
     1	sxk1942

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Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

✅ OK DOIs

- 10.1109/CVPRW56347.2022.00346 is OK
- 10.1145/3620665.3640366 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: A Framework to Enable Algorithmic Design Choice Ex...
- No DOI given, and none found for title: TorchVision: PyTorch’s Computer Vision library

❌ MISSING DOIs

- None

❌ INVALID DOIs

- None

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Paper file info:

📄 Wordcount for paper.md is 775

✅ The paper includes a Statement of need section

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License info:

✅ License found: Apache License 2.0 (Valid open source OSI approved license)

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👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

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Five most similar historical JOSS papers:

PyDGN: a Python Library for Flexible and Reproducible Research on Deep Learning for Graphs
Submitting author: @diningphil
Handling editor: @arfon (Active)
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Similarity score: 0.6971

ADaPT-ML: A Data Programming Template for Machine Learning
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Reviewers: @aaronpeikert, @wincowgerDEV
Similarity score: 0.6955

brains-py, A framework to support research on energy-efficient unconventional hardware for machine learning
Submitting author: @ualegre
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Similarity score: 0.6846

giotto-deep: A Python Package for Topological Deep Learning
Submitting author: @matteocao
Handling editor: @osorensen (Active)
Reviewers: @EduPH, @leotrs, @ismailguzel
Similarity score: 0.6828

Moead-framework: a modular MOEA/D Python framework
Submitting author: @geoffreyp
Handling editor: @melissawm (Retired)
Reviewers: @sjvrijn, @chkoar
Similarity score: 0.6809

⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.

@crvernon
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@editorialbot invite @HaoZeke as editor

👋 @HaoZeke - can you take this one on as editor? Thanks!

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Invitation to edit this submission sent!

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HaoZeke commented Oct 23, 2024

Hi @crvernon I will be able to edit this, with the caveat being I will not be able to start soliciting reviews until the weekend / Monday morning, I will assign myself if that's OK?

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@editorialbot assign @HaoZeke as editor

Perfectly OK @HaoZeke! Thank you!

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Assigned! @HaoZeke is now the editor

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HaoZeke commented Oct 23, 2024

@editorialbot remind @HaoZeke in 3 days

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Reminder set for @HaoZeke in 3 days

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👋 @HaoZeke, please take a look at the state of the submission (this is an automated reminder).

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HaoZeke commented Nov 5, 2024

@crvernon should this go for scope review since this has already been described in an existing publication?

@4imothy could you provide more information about the differences between the proposed publication and https://dl.acm.org/doi/10.1145/3620665.3640366 ?

@4imothy
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4imothy commented Nov 7, 2024

Hi @HaoZeke,

The submission to JOSS is meant to pair with ai3 into the future as we add more features, extend compatibility to more frameworks and support more operations, like attention. The JOSS paper is more broad to maintain its generality to future versions of ai3.

Since the last publication, the framework has achieved significant performance improvements, expanded support for additional acceleration platforms, and now PyTorch DNNs using the framework's implementations remain trainable and compilable.

Please let us know if this is sufficient, or if we should resubmit after adding additional features, such as support for attention.

@crvernon
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@editorialbot remind me in two days

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Reminder set for @crvernon in two days

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👋 @crvernon, please take a look at the state of the submission (this is an automated reminder).

@crvernon
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@editorialbot remind me in 1 week

@4imothy thank you for the clarification. I do think you should resubmit after a larger feature addition that shows major advancements on any previously reviewed work. If resubmitting to JOSS in the future, please specify this review thread link for clarification.

Unless I hear back @HaoZeke , I will plan on withdrawing this submission in one week.

Thank you

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Reminder set for @crvernon in 1 week

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👋 @crvernon, please take a look at the state of the submission (this is an automated reminder).

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crvernon commented Dec 2, 2024

@editorialbot withdraw

On the grounds of the following:

@4imothy thank you for the clarification. I do think you should resubmit after a larger feature addition that shows major advancements on any previously reviewed work. If resubmitting to JOSS in the future, please specify this review thread link for clarification.

Unless I hear back @HaoZeke , I will plan on withdrawing this submission in one week.

Thank you

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Paper withdrawn.

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