The video-sharing service has put up posters in Westminster ahead of the Government's highly anticipated decision on whether or not to ban under-16s from social media.

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Surprised there's no real tooling for this given how much research exists on continual learning. Built pyrecall to fill the gap. Snapshots skill scores before/after fine-tuning, flags regressions, rolls back LoRA adapters by name. Fully local, no external APIs. v0.1.0, MIT, pip install pyrecall Curious if anyone has thoughts on the benchmark design that's the part I'm least confident about. https://github.com/Arths17/Pyrecall submitted by /u/Level_Frosting_7950 [link] [Kommentare]

Submitted a short theoretical paper to TMLR and got desk-rejected with "does not meet our editorial standards or allow us to assess claims and evidence" and "not a suitable venue for this work." Is this a common outcome for first submissions? Curious what typically drives this kind of rejection, scope mismatch, insufficient experiments, or something else. Not looking to appeal, just trying to understand the bar so I don't waste time on the wrong venue next time. Anyone else gotten this and figured out what the actual issue was? submitted by /u/observer678 [link] [Kommentare]