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Matt Gardner proslijedio/la je Tweet
Just a reminder to everyone -- AKBC abstract deadline is only 2 days away! Please submit your papers to this new and exciting conference! (cc
@HannaHajishirzi@sameer_@andrewmccallum@nlpmattg@astent@zgives)https://twitter.com/akbc_conf/status/1217844126730915841 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Gardner proslijedio/la je Tweet
We've released our code here: https://nitishgupta.github.io/nmn-drop Hope it helps your research. Demo coming soon!https://twitter.com/nitish_gup/status/1214555731808014336 …
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Matt Gardner proslijedio/la je Tweet
Thanks for having us and the interesting discussion! We were honored to be guests on arguably the best ML/NLP podcast out there!https://twitter.com/nlpmattg/status/1224434226168090627 …
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#nlphighlights 104:@SanhEstPasMoi and@Thom_Wolf talk to us about model distillation, when you try to approximate a large model's decision boundary with a smaller model. After talking about the general area, we dive into DistilBERT.https://soundcloud.com/nlp-highlights/104-model-distillation-with-victor-sanh-and-thomas-wolf …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Gardner proslijedio/la je Tweet
Check out BREAK - a new NLU benchmark for testing the ability of models to break down a question into the required steps for computing its answer. https://allenai.github.io/Break/ A work by Tomer Wolfson, accepted to TACL 2020.
@JonathanBerant@yoavgo@ankgup2@nlpmattgHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Gardner proslijedio/la je Tweet
New TACL paper involving a lot of hard work from my twitter-less student Tomer, along with great collab. at AI2 and TAU. Paper/website at https://arxiv.org/abs/2001.11770v1 … https://allenai.github.io/Break/
@megamor2@yoavgo@nlpmattg@ankgup2 1/2pic.twitter.com/giom73Vla4
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And the reason we should probably be kinder to ourselves when we relive these things: I don't remember this. I remember talking to
@qi2peng2 about the poster, but not this particular part.https://twitter.com/qi2peng2/status/1224173967755231234 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Gardner proslijedio/la je Tweet
AKBC 2020 Abstract Deadline (February 6) is next week! Full papers are due Feb 13th! Please submit your finest work to the conference. Website (http://akbc.ws/2020/cfp/ ) has been updated with submission details.
#AKBC#AKBC2020Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Gardner proslijedio/la je Tweet
In
#nlphighlights episode 103, Brendan O’Connor@brendan642 tells about analyzing social media text to address a variety of social and sociolinguistic questions.https://soundcloud.com/nlp-highlights/103-processing-language-in-social-media-with-brendan-oconnor …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Gardner proslijedio/la je Tweet
We're proud to announce the recipients of the AI2 Outstanding Intern of the Year award for 2019: Sarthak Jain and
@Eric_Wallace_! Learn more about our Outstanding Intern award and these two fantastic awardees here: https://allenai.org/outstanding-interns.html …#AI#AIJobs#AIinternshippic.twitter.com/hdOqezBZCA
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Matt Gardner proslijedio/la je Tweet
So the question, the reason I posted this on twitter, is: at what point is it reasonable as a reviewer to refuse to spend time on a review? And if you get to that point, how do you convey that in a reasonable way in your review?
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This is blatantly dishonest and a waste of everyone's time, particularly that of honest reviewers who want to do a good job and give each paper the review they hope their own paper would get.
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Either of these two approaches is ok. The first one is more likely to result in an accepted paper, realistically, but it's also potentially a whole lot more work. What you *can't* do is just ignore the new work and pretend that your method is SOTA when you know it isn't.
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Or (2) discuss the contributions of the other work, talk about how they relate to your work, give some context to the reader about where your work fits in. Make an argument that you're doing science, not leaderboard chasing, and that your experiments still let us do science.
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Yes, you have to do some work to update your paper, but you have two avenues to proceed: (1) incorporate the basic technique that beat your approach, and show that your contributions are still useful, even on top of whatever else the other work did.
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Secondly, what should an author do in this situation? It really sucks to have a paper rejected in the fast-paced world of leaderboard chasing, I know. Hopefully there was some science in your paper, though, not just a SOTA claim, and that science is likely still valid.
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Asking now, because there's still time for me to fix this review, if I'm missing something here. I very much don't want to make a false accusation, or do the wrong thing. But modern leaderboards leave a paper trail that makes this case pretty obvious.
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So, what should you do as a reviewer in this situation? Do we have any clear guidelines? I basically wrote a strongly worded review that it sure looked like something was up, making me not want to waste my time giving the paper a thorough review. Was that out of line?
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Do not just resubmit your paper without updates to the next conference! *Especially*, do not still claim SOTA when you know full well that you are no longer SOTA. This is a very clear violation of academic integrity.
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So, clearly the authors knew about the better results (they had to have looked at the leaderboard to make their updated submission), but completely omitted them from their paper, even though some were published at EMNLP.
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