Comment by intelkishan
Comment by intelkishan 2 days ago
I have seen this particular work example to work. You don't get the exact match but the closest one is indeed Queen.
Comment by intelkishan 2 days ago
I have seen this particular work example to work. You don't get the exact match but the closest one is indeed Queen.
Thank you for the comment!
This led me to do a bit more research, and I see indeed the queen result is in itself infact "cheating" a bit: https://blog.esciencecenter.nl/king-man-woman-king-9a7fd2935...
#TheMoreYouKnow
It's a pretty exotic type of addition that would lead to the second set of examples, just trying to get an idea of its nature.
Shouldn't this itself be a part of training?
Having set of "king - male + female = queen" like relations, including more complex phrases to align embeddings.
It seems like terse, lightweight, information dense way to address essence of knowldge.
Yes but it doesn't generalize very well. Even on simple features like gender. If you go look at embeddings you'll find that man and woman are neighbors, just as king and queen are[0]. This is a better explanation for the result as you're just taking very small steps in the latent space.
Here, play around[1]
Or some that should be trivial Working in very high dimensions is funky stuff. Embedding high dimensions into low dimensions results in even funkier stuff[0] https://projector.tensorflow.org/
[1] https://www.cs.cmu.edu/~dst/WordEmbeddingDemo/