Explore tweets tagged as #acl2021nlp
We often ask: what is the difference between Computational Linguistics and Natural Language Processing? A wonderful perspective from Prof. Junichi Tsuji, #ACL2021NLP Lifetime Achievement Award winner, with the message: It is time for us to reconnect NLP and CL!
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On which datapoints are smaller models better? 🤔Surprisingly, even pinpointing them is challenging and requires new statistical tools!😯 Check out our paper: Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level #NLProc #ACL2021NLP
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Happy to announce that 2 of our papers on commonsense reasoning got accepted to #ACL2021NLP (1main+1findings). 🎉One for analyzing and improving multilingual LMs on CSR; the other presents RiddleSense, a QA dataset for answering #riddles! Code, data & papers coming soon! @nlp_usc
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Wanna have some fun with your NLU models? Try out RiddleSense, our new QA dataset in #ACL2021NLP. It consists of multi-choice questions featuring both linguistic creativity and common-sense knowledge. Project website: https://t.co/NHAtrofRAn Paper: https://t.co/QS1nzsQ2jY [1/5]
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Introducing our #acl2021nlp work on evaluating and improving multi-lingual language models (ML-LMs) for commonsense reasoning (CSR). We present resources on probing & benchmarking, and a method for improving ML-LMs. [1/6] Paper, code, data, etc.: https://t.co/ghS0DZwYfi
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Is there a connection between Shapley Values and attention-based explanations in NLP? Yes! Our #ACL2021NLP paper proves that **attention flows** can be Shapley Value explanations, but regular attention and leave-one-out cannot. https://t.co/qvcmh2raq8 w/ @jurafsky @stanfordnlp
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Join us for the Workshop on Natural Language Processing for Programming @Nlp4Prog on Aug 6th (9AM-6PM ET) at #ACL2021NLP, featuring a stellar multi-disciplinary lineup of speakers from PL/NLP/HCI/Robotics. Check out the program here https://t.co/8dCRyUHCMt
@osunlp
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BERT's tokenizations are sometimes morphologically superb-iza-rre, but does that impact BERT's semantic representations of complex words? Our upcoming #ACL2021NLP paper (w/ Janet Pierrehumbert & @HinrichSchuetze) takes a look at this question. https://t.co/wluiIDnswE /1
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Honored and flattered to receive the best paper award of #ACL2021NLP. Thank to wonderful co-authors Jingjing, Hao, Chun and Zaixiang, to the extraordinary MLNLC team at Bytedance AI Lab, and zhenyuan, weiying, hang, and ACL committee for support! to Olympic sprinter #SuBingtian
Congratulations to the authors who have won our paper awards! https://t.co/kjcmNW8Hgo
#ACL2021NLP
#NLProc
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We’ll be presenting “Learning to Generate Task-Specific Adapters from Task Description” at Poster 2G (5-7pm PT). Please come and chat with us! 😊 #acl2021nlp TL;DR: We train a hypernetwork that takes in a task description and generates task-specific adapter parameters.
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Earlier today I gave an invited talk #ACL2021NLP. My sister took some impromptu pictures. The times we live in...
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UCSB #NLProc Group welcomes new faculty and co-Director Prof. Lei Li @lileics: https://t.co/QRYFEnVLEF Don’t forget to check out his #ACL2021NLP Best Paper on optimal transport for vocabulary reduction next week.
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Word meaning varies across linguistic and extralinguistic contexts, but so far there has been no attempt in #NLProc to model both types of variation jointly. Our #ACL2021NLP paper fills this gap by introducing dynamic contextualized word embeddings. https://t.co/we3m2lpsR2 [1/4]
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[#acl2021nlp Note Series] Excited about @radamihalcea's ACL Presidential Address @aclmeeting! Don't just chase "accuracy," but care about "more dimensions": interpretability, generalizability, ethics, NLP for social good, environmental cost of NLP, D&I, etc! /1
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Thrilled to announce that our paper received the Test of Time Award from the Association for Computational Linguistics!!! @aclmeeting #ACL2021NLP #NLProc 1/n
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PSA people tweeting #NLProc papers. Twitter appears to be classifying #ACL2021 tweets as "Sports". Might have better luck using #ACL2021NLP
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🚨#NLPaperAlert #ACL2021NLP #NLProc "Evaluation Examples Are Not Equally Informative: How Should That Change NLP Leaderboards?" w/@barrowjoseph @miserlis_ John P. Lalor @robinomial @boydgraber
https://t.co/YkX3kcOh50 Chat at #ACL2021NLP
https://t.co/94v5U33Wo2 Summary thread:
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I highly recommend this #ACL2021NLP outstanding paper on machine translation evaluation: https://t.co/CheAGTZah3 It shows the (increasing) lack of rigor in MT evaluation, and gives 4 concrete recommendations that should be easy to follow and required by all MT reviewers!
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