I've noticed a slight uptick recently of folks reaching out to me asking for help with NLP problems where the underlying problem is one I consider unsolvable (at least practically). 😣
Here are some questions you to ask yourself *before* you invest a lot of time.
As an experienced NLP researcher, I think this is really good advice that anyone getting into the field should know.
Also as an experienced NLP researcher, problems that seem unsolvable and have no good data or evaluation are maybe the most fun 😃
“Requiring students to ante up conference funds ... without the hope of being reimbursed for months makes academia less welcoming for scientists who are financially disadvantaged.” This week’s Working Life. https://t.co/DdteD6wNTi
The "Imagenet in 1 hour" paper from @priy2201 is overflowing with wonderful little tricks. Here's one of my favorites - something that many researchers are still not aware of, but really makes model training easier
https://t.co/uf8TkpCkIQ
Does the best number of BPE merges for language modeling¹ depend on the language²? Yes!
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¹ Why use BPE for LMs? It's a surprisingly good open-vocab baseline, see https://t.co/SlrY7yTK0m .
² Ooh, multiple languages? Yup, this is follow-up to https://t.co/gAS5VLdZ7f !
Our #EMNLP2018 paper (last one, I promise!) introduces a data set for "Machine Translation of Noisy Text" by @pmichelX. I'm really excited about this data set, a *natural* test-bed for noise-robust sequence-to-sequence models. https://t.co/poT1DdVmUU
Interesting: "Logged off: Meet the teens who refuse to use social media" https://t.co/xKkVYYGmSp And, yes, I note the irony in posting this here -- though Twitter is not the same as FB, Instagram, etc.
I say this to parents at school. The fat tech cats make their billions off you giving your children the latest tech gadget while they fill their houses with books.
Periodic reminder: I maintain the BIG #NLProc Directory. Consider signing up, or use it as a resource for hiring, finding invited speakers and more!
https://t.co/oONBxkjg0S #Coling2018