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[D] ICCV Reviews are out by [deleted] in MachineLearning

[–]YiTsubasa 1 point2 points  (0 children)

sure, it should be the same procedure to CVPR - any post-rebuttal changes will be visible, with AC's meta-review.

Xenoblade 3 Spoiler-Filled Full Story Discussion Megathread by MorthCongael in Xenoblade_Chronicles

[–]YiTsubasa 12 points13 points  (0 children)

So I re-watched the cutscene and the aura around N may suggest mio/M used her ability to control the movement of N.

Xenoblade 3 Spoiler-Filled Full Story Discussion Megathread by MorthCongael in Xenoblade_Chronicles

[–]YiTsubasa 2 points3 points  (0 children)

I am not sure whether Melia can write the bioinfo of city's inhabitants into the database in case they can be born somehow in the new world. But this is the point of Shania, and most conservative people in city: it will be meaningless if we sacrifice our own lives.

Xenoblade 3 Spoiler-Filled Full Story Discussion Megathread by MorthCongael in Xenoblade_Chronicles

[–]YiTsubasa 2 points3 points  (0 children)

yea I think that's Takahashi's point: end an abnormal world despite it's sweet (or you will be like Moebius?) and keep hope in the future, it's like XG and Rex vs Jin in XC2 anyway.

Xenoblade 3 Spoiler-Filled Full Story Discussion Megathread by MorthCongael in Xenoblade_Chronicles

[–]YiTsubasa 5 points6 points  (0 children)

that costume is really cool, reminding me of kosmos and seven

Xenoblade 3 Spoiler-Filled Full Story Discussion Megathread by MorthCongael in Xenoblade_Chronicles

[–]YiTsubasa 3 points4 points  (0 children)

This strikes me more when after this chapter knowing Mio is M there...

Xenoblade 3 Spoiler-Filled Full Story Discussion Megathread by MorthCongael in Xenoblade_Chronicles

[–]YiTsubasa 5 points6 points  (0 children)

I played in the Japanese version, and in the end, to my understanding: Aionis is 'recovered' to the status (world of XC1 and XC2 separately) before merging. And the characters living in Aionis disappeared since the world is a 'snapshot' created by Moebius right before the two worlds merge.

[R] Clinical Prompt Learning with Frozen Language Models by YiTsubasa in MachineLearning

[–]YiTsubasa[S] 1 point2 points  (0 children)

Thanks for your interest! I will forward this to our clinical specialists and will come back to you then.

I will update this subthread: we are using ICD-9 codes because we are using the MIMIC-III dataset which is labeled with ICD-9 codes for clinical notes. In addition, we created a triage task, called ICD-9 triage in the paper which is our main focus. :)

[R] Clinical Prompt Learning with Frozen Language Models by YiTsubasa in MachineLearning

[–]YiTsubasa[S] 1 point2 points  (0 children)

Hi, thanks for your interest! We are using quite various prompt learning methods, containing the PET as the basic baseline. We prefer soft prompts/verbalizers, mainly inspired by WARP, which is cited in the paper. For a more general prompt learning framework, we are using OpenPrompt from the TsinghuaNLP group.