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femag 2023

Timo Schick (@timo_schick) / X

Por um escritor misterioso

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Timo Schick (@timo_schick) / X
timoschick (Timo Schick)
Timo Schick (@timo_schick) / X
Masoud Jalili @ICCV (@_masoudjalili) / X
Timo Schick (@timo_schick) / X
Shabnam Rashtchi (@ShabnamRashtchi) / X
Timo Schick (@timo_schick) / X
Timo Schick on X: Interested in distilling zero-shot knowledge from big LMs like GPT-3? Or in learning more about a movie called Bullfrogs on Poopy Mountain? 🐸💩 Check out our blog post
Timo Schick (@timo_schick) / X
Timo Schick on X: 🎉 With some delay, I'm happy to share that our papers on GenPET and DINO (w/@HinrichSchuetze) have been accepted to #EMNLP2021 #NLProc 🥳 🐶 GenPET Paper: Code
Timo Schick (@timo_schick) / X
Philipp Burckhardt (@burckhap) / X
Timo Schick (@timo_schick) / X
GPT-3 vs PET: Not Big but Beautiful, by Chetana Didugu
Timo Schick (@timo_schick) / X
Timo Schick on X: This is achieved by combining PET ( with pretrained ALBERT. Key factors for strong performance include concurrently using multiple task descriptions and using labeled data to perform actual
Timo Schick (@timo_schick) / X
Timo Schick on X: 🎉 With quite some delay, I'm happy to annouce that Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification (w/ Helmut Schmid & @HinrichSchuetze) has
Timo Schick (@timo_schick) / X
Timo Schick on X: 🎉 New paper 🎉 We introduce Unnatural Instructions, a dataset of 64k instructions, inputs and outputs generated entirely by a LLM. Models trained on this data outperform models
de por adulto (o preço varia de acordo com o tamanho do grupo)