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Thành Lê proslijedio/la je Tweet
Got promoted to a full professor at CMU:) Thanks to my amazing students, collaborators, and my mentors. CMU is a remarkable place, but what makes it truly unique is its brilliant students! Hard to find a better place to do ML and AI.
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Today we announce a novel, open-source method for text generation tasks (e.g., summarization or sentence fusion), which uses edit operations instead of generating text from scratch, leading to less errors and faster model execution. Read about it below.https://goo.gle/38XfRXU
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An Opinionated Guide to ML Research: “To make breakthroughs with idea-driven research, you need to develop an exceptionally deep understanding of your subject, and a perspective that diverges from the rest of the community—some can do it, but it’s hard.” http://joschu.net/blog/opinionated-guide-ml-research.html …pic.twitter.com/fyO6cyr9im
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Thành Lê proslijedio/la je Tweet
Transformers 2.4.0 is out
- Training transformers from scratch is now supported
- New models, including *FlauBERT*, Dutch BERT, *UmBERTo*
- Revamped documentation
- First multi-modal model, MMBT from @facebookai, text & images Bye bye Python 2
https://github.com/huggingface/transformers/releases …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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People asking me to teach classes clearly give zero fuck to the imposter syndrome of a former physics PhD turned lawyer before joining AI Anyway I'll co-teach NLPL Winter School w Yoav Goldberg talking transfer learning, its limits & where the field might head Will share slidespic.twitter.com/M1QFXBT5CP
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Thành Lê proslijedio/la je Tweet
Introducing the new Thinc, a refreshing functional take on deep learning!
Static type checking
Mix @PyTorch,@TensorFlow &@ApacheMXNet
Integrated config system
Extensible backends incl. JAX (experimental)
Variable-length sequences & morehttps://thinc.ai Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Thành Lê proslijedio/la je Tweet
Introducing
#MeenaBot, a 2.6B-param open-domain chatbot with near-human quality. Remarkably, we show strong correlation between perplexity & humanlikeness! Paper: https://arxiv.org/abs/2001.09977 Sample conversations: https://github.com/google-research/google-research/tree/master/meena … https://twitter.com/GoogleAI/status/1222230622355087360 …pic.twitter.com/3xNSV4r4uB
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Thành Lê proslijedio/la je Tweet
Facebook's AI Residency program, which gives residents 12 months of practical experience in AI working with leading researchers, is accepting applications until January 31st! Current residents Diana and Eric discuss their experience in this Q&A: https://ai.facebook.com/blog/qa-with-facebook-ai-residents-eric-mintun-and-diana-gonz%C3%A1lez/ …pic.twitter.com/wiNe0v9nA7
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Thành Lê proslijedio/la je Tweet
Today gave a talk at Google Research Berlin about our Transformer analysis work. Met a lot of great people and feel totally happy :) Want to know details? Here are the blog posts: The Story of Heads: https://lena-voita.github.io/posts/acl19_heads.html …, Evolution of Representations: https://lena-voita.github.io/posts/emnlp19_evolution.html …pic.twitter.com/x3EDsrUkjZ
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Thành Lê proslijedio/la je Tweet
We're releasing mBART, a new seq2seq multilingual pretraining system for machine translation across 25 languages. It gives significant improvements for document-level translation and low-resource languages. Read our paper to learn more: https://arxiv.org/pdf/2001.08210.pdf …pic.twitter.com/tJbRcOTqik
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Thành Lê proslijedio/la je Tweet
Following the tradition, I am going to share all the course material for "STAT 453: Introduction to Deep Learning and Generative Models" I am teaching this semester :)https://github.com/rasbt/stat453-deep-learning-ss20 …
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New lecture series
We've teamed up with @ai_ucl to bring you the#UCLxDeepMind Deep Learning Lecture Series: 12 lectures covering a range of topics in Deep Learning - all led by DeepMind researchers, all free, and all open to everyone. Info & tickets:https://www.eventbrite.co.uk/o/ucl-x-deepmind-deep-learning-lecture-series-general-29078980901 …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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To make my research more reproducible, extensible and comparable to that of others & out of need to homogenize the language we use to express nn pruning methods, I contributed `nn.utils.prune` to
#PyTorch 1.4 (see highlights https://github.com/pytorch/pytorch/releases/tag/v1.4.0 …) Try it out & build on it!
https://twitter.com/PyTorch/status/1217596623167152129 …pic.twitter.com/NqURm90B0E
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Thành Lê proslijedio/la je Tweet
Open Syllabus Project https://opensyllabus.org/ Open Syllabus is a non-profit organization that maps the curriculum of higher education. Database of / stats from 7M class syllabi
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BigGAN samples are famously photo-realistic but limited in diversity for some classes. Slightly modifying only the class embeddings (network unchanged) can reduce the diversity gap by ~50%! Work with Long Mai and led by fantastic
@MkQili!! Paper & video: http://anhnguyen.me/project/biggan-am/ …pic.twitter.com/MhIOxCepV5
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By restructuring math expressions as a language, Facebook AI has developed the first neural network that uses symbolic reasoning to solve advanced mathematics problems. https://ai.facebook.com/blog/using-neural-networks-to-solve-advanced-mathematics-equations/ …pic.twitter.com/IL2H8ygDYC
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Great advice from
@Thom_Wolf on why you should release your code and make it as easy to use! It usually takes me >4 days to prepare the code, though. Getting it readable, well-explained, clean and logical (yet still equivalent to the original experiments) usually takes 1-2 weekshttps://twitter.com/Thom_Wolf/status/1216990543533821952 …
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Thành Lê proslijedio/la je Tweet
I often meet research scientists interested in open-sourcing their code/research and asking for advice. Here is a thread for you. First: why should you open-source models along with your paper? Because science is a virtuous circle of knowledge sharing not a zero-sum competitionpic.twitter.com/x16jgKmLFr
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2.1 is out
Notable features:
- The experimental TextVectorization layer allows you to include your text processing logic inside your model (for cleaner deployment & serialization)
- The standard TF pip package now includes GPU support by defaulthttps://github.com/tensorflow/tensorflow/releases/tag/v2.1.0 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Thành Lê proslijedio/la je Tweet
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@stanfordnlp people’s#ICLR2020 papers #2—ELECTRA:@clark_kev and colleagues (incl. at@GoogleAI) show how to build a much more compute/energy efficient discriminative pre-trainer for text encoding than BERT etc. using instead replaced token detection https://openreview.net/forum?id=r1xMH1BtvB …pic.twitter.com/lFAr6XYSWx
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