Update: we have extended the submission deadline to July 1st 12:00 CEST. Looking forward to receive your new and/or recently accepted paper as submission to our #ECCV2026 hyperbolic learning workshop!

Do you have a new research on hyperbolic learning or did you have a paper accepted on this topic in the last year? Submit your work to our ECCV 2026 Beyond Euclidean workshop on Hyperbolic Deep Learning for Computer Vision! Deadline: June 24th Details: sites.google.com/view/beyond…

If you're at #ICLR2026, come check out our poster on the alignment between video understanding in the brain and in deep learning!

Thank you inviting me to the winter school, it was great to meet everyone!

Perhaps not a perfect match, but scattering networks: biorxiv.org/content/10.64898…

Same here, no need for emergency reviews in my batch. Although verbose, it seems that the messages from the PCs are taken seriously by the reviewers.

Yes, one month between submission and reviewer assignment is a huge gap. I wonder whether the openreview issues of this year played a role.

I remember 10 years every reviewer had to review around 10 papers. The short review window is not good, but I can promise it was worse in the not so distant past.

I am very excited to visit the ELLIS Unit in Barcelona next month!

Unfortunately, the latter is a realistic scenario and already happened. Beyond bribing, people can hold grudges, threaten, sabotage papers in future conferences, etc. We care too much about careers instead of science and people end up doing unhealthy things to advance them.

What else were they supposed to do though? They can't pretend it didn't happen because people would bribe/blackmail ACs at large scale. The only other solution is to start all over, which is much more of a time waste. Please tell me, what do you propose?

I have funding for 2 new PhD students on hyperbolic deep learning. Interested in joining this exciting research direction? Check out the vacancy and consider applying! Link: werkenbij.uva.nl/en/vacancie…

I will even go as far as to say that the review quality has been stable over the last decade (seen as author and AC). My advice, especially for new students, is to not go to twitter after reviews have been released, too many frustrated people with ill-intended messages. [4/4]

In my experience, most reviews contribute to the process and with 4 reviews per paper, a noise review can be compensated by others. There are still plenty of cases with errors, but this problem is as old as peer review itself. [3/4]

People calling for the end of peer review over a few cherry-picked bad reviews and having the audacity to call the process unscientific is such a crazy take. I often get the feeling that people hope for bad reviews so that they can shout on twitter. [2/4]