Conversation

Fahim Farook

16 papers posted out of 55 total in the cs.CV category on arXiv.org and that concludes the reading of the papers for another week!

See y'all next week 🙂

#AI #CV #NewPapers #DeepLearning #MachineLearning
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@f Impressive! Do you keep notes or compile some sort of indexing or ranking of the papers you read? Is Mastodon your ? ;-)

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@f just realized your Toot stream is like a mini paperswithcode.com page.

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@hobs Don’t know if you want all the details (and this kind of evolved over time) but I originally created a system which would get the RSS feed for the cs.CV category on arXiv and use ML to summarize it for me.

But I didn’t like the summaries since they didn’t really tell me much 😛 So, I modified the system to download the PDF papers and to give me an overview of the papers each day. From that, I went to adding a form to the paper view so that I can post a summary and a page screen grab to Mastodon.

The posting system kind of fell by the wayside (I post manually now) due to various issues, but I also added a system which tracks the papers I skip and the ones I post about so that I can track things. That’s where it stands since I now post daily about new papers in the cs.CV category since some people seem to find that useful 🙂
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@hobs Yep, most of my posts tend to be either boost, or papers for the day that I found interesting 🙂 I do warn people about this in my profile page but most people just see one or two papers I’ve posted about and assume that they were my papers …
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@f very very cool. Seems like it a great way to gamify your brain training and keep up with the latest cs.cv trends

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@f one last question. Is any time f the software for you arxiv reading list tooter open source? I would love to use it for myself and maybe contribute and recruit learners in my NLP and CS circle.

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@hobs The original code that did the summarization is on GitHub:

https://github.com/FahimF/summarizer/

I don’t believe I updated the repo with the later code which added the Mastodon posting and stats and stuff to it though since that didn’t gel with the original #MachineLearning approach 🙂 But if you are interested, I can send you the latest source as a ZIP file?

Or I guess I should set up a separate repo if you are interested in contributing to the code. I’ve kind of hit all my targets for features (except for a stats screen and the ability to view old papers … but too busy with Mastodon clients at the moment to get that done). Let me know …
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@f Thank you! I'll dig into the summarizer and start there and once I've got my head around in it, maybe ask for the zip for the tooter.

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