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Kevin Clark proslijedio/la je Tweet
“we train a model on one GPU for 4 days that outperforms GPT (trained using 30x more compute) on the GLUE natural language understanding ... we match the performance of RoBERTa, the current state-of-the-art pre-trained transformer, while using less than 1/4 of the compute.”
https://twitter.com/stanfordnlp/status/1214637012805799939 …
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Kevin Clark proslijedio/la je Tweet
New analysis paper from my group! We zoom in on some of
@clark_kev et al.'s on syntax-sensitive attention heads in BERT (+RoBERTa, +...), and find interestingly mixed results.https://twitter.com/phu_pmh/status/1199731562046201856 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Kevin Clark proslijedio/la je Tweet
Excited to share new work!!! “Generalization through Memorization: Nearest Neighbor Language Models” We introduce kNN-LMs, which extend LMs with nearest neighbor search in embedding space, achieving a new state-of-the-art perplexity on Wikitext-103, without additional training!pic.twitter.com/hehcLnDaKz
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Kevin Clark proslijedio/la je Tweet
Excited to share our work on BART, a method for pre-training seq2seq models by de-noising text. BART outperforms previous work on a bunch of generation tasks (summarization/dialogue/QA), while getting similar performance to RoBERTa on SQuAD/GLUE
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Kevin Clark proslijedio/la je Tweet
How do we design probes that give us insight into a representation? In
#emnlp2019 paper with@percyliang, our "control tasks" help us understand the capacity of a probe to make decisions unmotivated by the repr. paper: https://arxiv.org/abs/1909.03368 blog: https://nlp.stanford.edu/~johnhew/interpreting-probes.html …pic.twitter.com/1NA5hoyF7t
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Kevin Clark proslijedio/la je Tweet
#BlackboxNLP best paper award went to: What does BERT look at? An Analysis of BERT’s Attention. Kevin Clark, Urvashi Khandelwal, Omer Levy and Christopher D. Manning.Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
BAM! Our new
#ACL2019 paper presents "Born-Again Multi-Task Networks," a simple way to improve multi-task learning using knowledge distillation. With@lmthang@ukhndlwl@quocleix@chrmanning. Paper: https://arxiv.org/pdf/1907.04829.pdf … Code:http://bit.ly/2NO8ufNHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Code for our paper "What Does BERT Look At? An Analysis of BERT's Attention" (https://arxiv.org/abs/1906.04341 ) has been released!https://github.com/clarkkev/attention-analysis …
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Check out our new
#BlackboxNLP paper "What Does BERT Look At? An Analysis of BERT's Attention" with@ukhndlwl@omerlevy@chrmanning! https://arxiv.org/abs/1906.04341 Among other things, we show that BERT's attention corresponds surprisingly well to aspects of syntax and coreference.pic.twitter.com/SWh1qMIKX1
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