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## 0. Paper
paper: [arxiv](https://arxiv.org/abs/1906.02715)
## 1. What is it?
They analyze contextualized word representations from BERT.
## 2. What is amazing compared to previous works?…
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In #367 extra explicit warning content was added but @jokudasai made a good point that it's not contextualized very well--we should mention that users face the possibility of landlord retaliation _bec…
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@Sazan-Mahbub has volunteered to lead this section. It may grow to include others' contributions as well.
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As we expand to more cities, "the number of cars available" has to be contextualized to "the number of cars within a reasonable distance available". For instance, if we are in New York and there's onl…
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# Overview
Searching through the ontology shall become more convenient. This requires changes to the frontend and the backend as well. The frontend part (except the API to it) is **not** the scope …
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### Feature description
Allow the LanceDB and other Vector DB adapter to specify a "contextualize" or rolling window operation to join partitioned text chunks before applying the embedding function…
zilto updated
2 months ago
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Allow users to specify a base predictor that predicts population, cluster, or cohort models, so that contextualized models only learn context-specific effects not represented in the base predictor.
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Thanks for providing information, for the word embedding, I use following code as given in one of the examples
```
from sentence_transformers import SentenceTransformer
model = SentenceTransformer(…
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Here, we have coupled components between `Rule` and `Api`. We've already had it with the `apply` method. We can go forward as is, but we will assume the technical debt.
If in the future we…
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On Apr 22, he referred me to https://github.com/rchain/pi4u/tree/master/AFreshProofTheoryForLADL :
> That’s behind our current work by about 2 weeks. We’re incorporating [this paper](https://arxiv…