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Jonathan Berant proslijedio/la je Tweet
Break it down! Introducing the "Break"
#NLU benchmark for testing the ability of models to break down a question into required steps for computing the answer. Accepted for#TACL2020. Learn more about Break in this post by Tomer Wolfson on the AI2 Blog:https://medium.com/ai2-blog/break-mapping-natural-language-questions-to-their-meaning-representation-31bb753701d6 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
We define a mean. rep. (QDMR) that decomposes questions to a sequence of steps that can be executed against any context (image, text, DB), crowdsource >80K question-QDMR pairs using questions from 10 existing datasets, show usefulness for RC and release a QDMR parser. Enjoy! 2/2
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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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Jonathan Berant proslijedio/la je Tweet
We present our new year special: “oLMpics - On what Language Model pre-training captures״, http://arxiv.org/abs/1912.13283 , Exploring what symbolic reasoning skills are learned from an LM objective. We introduce 8 oLMpic games and controls for disentangling pre-training from fine-tuning.pic.twitter.com/ECQ7ZpcKlg
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Jonathan Berant proslijedio/la je Tweet
רשמו בהיומנים - אדבר על פרישוּת (interpretability) רשתות נוירונים בסמינר לימוד המכונה של אוניברסיטת ת"א שבועיים מהיום, 1/1 למניינם, ב-13:00
#3ביקור3מולדת ותודה ל-@JonathanBerant על ההזמנה!https://twitter.com/yuvalpi/status/1168744599378124801 …
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Jonathan Berant proslijedio/la je Tweet
תודה
לעשרות התומכות והתומכים שבחרו להגדיל את התמיכה החודשית שלהם ב"שקוף" בחודש האחרון!
קצת נתונים, נכון להיום:
+ תומכות ותומכים קבועים: 2,811
+ סכום תמיכה חודשי מצטבר: 92,905 ש"ח
+ השקיפות הגדולה בישראל:
הצטרפו עכשיו לגוף התקשורת שעובד רק בשבילכם: http://shakuf.ly/join-mol pic.twitter.com/lIMa4bBjkj
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Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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"Don't paraphrase, detect"!
@jonherzig presenting an analysis of dist. shift issues in collecting sem. parsing data with 'overnight' and propose a new method that iteratively trains a paraphrase model. Session 8B: Sentence-level Semantics II, 17:24, https://arxiv.org/abs/1908.09940Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Check out this excellent work by Ben!https://twitter.com/ben_bogin/status/1191880155574063105 …
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Jonathan Berant proslijedio/la je Tweet
@megamor2,@yoavgo,@JonathanBerant. Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets. (Video presentation) https://www.aclweb.org/anthology/D19-1107/ …#emnlp2019Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
"Are we modeling the task or the annotator? "
#emnlp2019 today (Tue) at 1530@megamor2 will present our work on annotator bias in Session3A machine learning ii. Come check it out! https://arxiv.org/abs/1908.07898@yoavgoHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jonathan Berant proslijedio/la je Tweet
congrats also to the AI2/TAU/Utah team for the honorable mention of their work on challenges in active learning.
@JonathanBerant@GabiStanovskyhttps://twitter.com/conll2019/status/1191222112305856512 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jonathan Berant proslijedio/la je Tweet
yay!
@hila_gonen and@YovaKem 's work just won#CoNLL2019 best paper! we look at what happens to word embeddings in languages in which inanimate nouns have gender (spoiler: they cluster into gender groups) and attempt to control for that, improving the embeddings quality.https://twitter.com/conll2019/status/1191221004661485568 …
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Congrats to Omri and all our other great collaborators!https://twitter.com/conll2019/status/1191222112305856512 …
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Jonathan Berant proslijedio/la je Tweet
Big congrats to the winners of the
#conll2019 paper awards: 1) Best Paper: https://www.aclweb.org/anthology/K19-1043/ … by Gonen, Kementchedjhieva, Goldberg; 2) Best Paper for Research Inspired by Human Language Learning: https://www.aclweb.org/anthology/K19-1008/ … by Rabinovich, Watson, Beekhuizen, Stevenson.pic.twitter.com/UqaAUc70U1
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Jonathan Berant proslijedio/la je Tweet
We also had 2 honorable mentions for each best paper category: Honorable mentions for best paper: 1) https://www.aclweb.org/anthology/K19-1042/ … by Koshorek, Stanovsky, Zhou, Srikumar, Berant 2) https://www.aclweb.org/anthology/K19-1001/ … by Jumelet, Zuidema, Hupkes
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Jonathan Berant proslijedio/la je Tweet
Best paper at
@conll2019: Gonen et al. on debiasing word embeddings. Congrats!#emnlp2019 @emnlp2019#NLProcPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jonathan Berant proslijedio/la je Tweet
Omri Koshorek talking active learning with
@GabiStanovsky, Yichu Zhou,@viveksrikumar and@JonathanBerant at#coling2019#emnlp2019 https://arxiv.org/abs/1910.02228 pic.twitter.com/ZmZ538mwQG
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Jonathan Berant proslijedio/la je Tweet
@AlonTalmor talking about the MRQA 2019 shared task baseline model!pic.twitter.com/Qpzf4a7g7Z
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Jonathan Berant proslijedio/la je Tweet
@robinomial kicking off MRQA 2019! Please come by to room 201-BC at EMNLP for some discussion on machine reading!pic.twitter.com/2XjQR1yB9O
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