"Experimental Standards for Deep Learning in Natural Language Processing Research", an updated version of our workshop paper, got accepted at @emnlpmeeting! #emnlp2022 🥳 Check the version below to learn how to make your empirical research more rigorous! https://t.co/HZrUGGikqJ
I am excited to announce a new version of deep-significance, version 1.2.6! 🥳 Below I'll talk about changes that were made while writing a demo paper, which can be found here: https://t.co/ohS89UK3MY, the package itself is at https://t.co/45tri56ifG 🧵 (1/5)
I'm so happy to finally announce our work with @jesfrellsen and @ch_hardmeier at @emnlpmeeting: We create a large benchmark of uncertainty quantification for #NLProc (8 models, up to 7 metrics) on three different languages! 🧵 (1/10) https://t.co/Ez5vJkRkbZ #emnlp2022