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Work with me this summer on conversational AI at PolyAI Singaporehttps://www.polyai.com/careers/machine-learning-intern/ …
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Matt Henderson proslijedio/la je Tweet
Excited to share our
@iclr_conf#iclr2020 work NADST: The first Non-Autoregressive neural model for Dialogue State Tracking (DST) w/ SOTA on MultiWOZ2.1, reducing inference latency by an order (https://openreview.net/forum?id=H1e_cC4twS …). Joint work w/@LHung1610 and@RichardSocher at@SFResearch!Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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The
#NeurIPS2019 conversational AI workshop is today - http://alborz-geramifard.com/workshops/neurips19-Conversational-AI/Main.html …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Henderson proslijedio/la je Tweet
Have you tried the new ConveRT featurizer yet? We're keen to see how the new pipeline performs on your dataset. Join the discussion in the community forum and contribute your evaluation numbers http://ow.ly/DuUk50xlCIt http://ow.ly/Tvh950xlCIu
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Our ConveRT model has been implemented in Rasa, making it very easy to use as a feature extractor for intent classificationhttps://twitter.com/alanmnichol/status/1199375971633250305 …
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it is working a lot better than other attention mechanisms I've tried for my task-pic.twitter.com/ZH3mlZbPaI
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their prior filter, convolved on the previous alignment, helps guide the model to alignments that move forward in time code for animation https://pastebin.com/vTEUcdAU pic.twitter.com/VRoEf2AyVh
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this is a great paper with an elegant idea for learning monotonic attention that generalises to long sequences https://arxiv.org/abs/1910.10288 https://twitter.com/daisystanton/status/1187604793046401024 …
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ConveRT results on DSTC7 can be reproduced using the code in the repo: https://github.com/PolyAI-LDN/polyai-models/tree/master/dstc7 …pic.twitter.com/8sGFIR7uJ4
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get started using the model for classification, response retrieval etc. using
@GoogleColab: https://colab.research.google.com/gist/matthen/1fc745ae1c91a9ba32413ed9ab2acc09/convert-examples.ipynb …pic.twitter.com/mNAreWCrvI
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The efficient ConveRT (Conversational representations from transformers) model is available as a
@TensorFlow hub module at:https://github.com/PolyAI-LDN/polyai-models …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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@poly_ai has released ConveRT, a pretrained sentence encoder optimized for conversational understanding. It's under 60MB, is substantially faster & cheaper to train than standard encoder models (BERT etc.), and beats those models on conversational tasks: https://arxiv.org/abs/1911.03688Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Henderson proslijedio/la je Tweet
This never ends. This year, so far, 15 out of 44 people to attend
@black_in_ai workshop at@NeurIPSConf (which is still in Canada) have been denied visas. That's 33%. We had all this press last year, they were supposed to help us this year.Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Henderson proslijedio/la je Tweet
Here's to hoping 2020 will bring 10x as efficient models instead of 10% reductions in GLUE error rates :)https://twitter.com/Thom_Wolf/status/1189271899316064256 …
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Matt Henderson proslijedio/la je Tweet
Super excited to be organizing the 2nd NLP For Conversational AI Workshop held at
#acl2020. If you like Seattle coffee
, Washington hikes
, and talking machines
, we look forward to seeing you there! @aclmeetinghttps://bit.ly/2BPtDO0Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
drawing hyperbolic fractals with the chaos game in hyperbolic spacepic.twitter.com/8yKgdvqNxW
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how could you draw a sierpinski triangle in the hyperbolic disk? one way is to start with some points, and repeatedly move each one half way to a random one of the corners, using the hyperbolic geometry. when the corners are close enough, you get the original sierpinskipic.twitter.com/mrFzoyZxdJ
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Matt Henderson proslijedio/la je Tweet
Thanks to
@matthen2, I got to test out my new candidate DeOldify model on a use case that I think will be quite appealing for many people: wedding photos! Thanks Matt!pic.twitter.com/OEscz5XhiW
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We'll promote sensible trade-offs between performances & models that are
- computationally more efficient
- conceptually simpler
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