Based on our record, Unpaywall should be more popular than WordNet. It has been mentiond 44 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
TL;DR: The authors pretrain the model to classify images into Wordnet synsets[a] that appear in the caption, using a standard Cross Entropy loss. They keep the number of classes relatively small by removing any synsets that don't show up in captions at least 500 times in the dataset. It seems to work well. My immediate question is: Why not classify among the entire hierarchy of all Wordnet synsets? --- [a]... - Source: Hacker News / about 2 months ago
To operationalize this intuition, the Microsoft and UC Berkeley researchers use WordNet and Wiktionary to augment the text in image-text pairs. The concept itself is augmented for isolated concepts, such as the class labels in ImageNet, whereas for captions (such as from GCC), the least common noun phrase is augmented. Equipped with this additional structured knowledge, contrastively pretrained models exhibit... - Source: dev.to / 3 months ago
If you like this, definitely check out WordNet (https://wordnet.princeton.edu/). - Source: Hacker News / 6 months ago
I didn't understand well what you meant, but maybe this site can help you: https://wordnet.princeton.edu/. Source: over 1 year ago
What I'd do is work with a huge database like WordNet and then try to "extrapolate" BIP39 to 4096 words by creating queries against WordNet to obtain words meeting the constraints you'd like to keep. Source: over 1 year ago
You might also find this interesting: https://unpaywall.org/. Source: 7 months ago
> can you detail what the possible issue is? Why? Are you in a position to help everyone? (As you probably guessed while reading the comment you replied to, I don't really need help; more on that below). "Occasional" is not universal; as you aren't getting the problem in a here-and-now sense you can probably play around with the "here" part by using Tor Browser to see if you can get to the article via the link... - Source: Hacker News / 9 months ago
There are many of course the problem is that the ai hallucination problem is still a huge issue. For instance, getting all of https://unpaywall.org/ or something similar into an LLM would be a boon for scientists, but... If you can't trust what it is saying you will end up going back to pull the source anyway. The analysis it provides would probably be helpful though. Source: about 1 year ago
For problem 1. I can recommend this browser extension: https://unpaywall.org/ it basically redirects you to a legally available free version of any article you are looking at, if it can find one. Source: about 1 year ago
Try this: https://unpaywall.org, it’s legal. Source: about 1 year ago
VerbAce - VerbAce-Pro is an easy-to-use Desktop Translation Software. Translate in a mouse click
SCI-HUB - It provides mass and public access to tens of millions of research papers
Artha - Artha is a handy thesaurus based on WordNet with distinct features like global hotkey look-up...
arXiv - arXiv is a free distribution service and an open-access archive for scholarly articles.
WordWeb - One-click lookup in any almost any Windows program; Hundreds of thousands of definitions and synonyms; The latest international English words; Works offline, or reference to Wikipedia and web references.
12 Foot Ladder - Prepend 12ft.io/ to the URL of any paywalled page, and we'll try our best to remove the paywall and get you access to the article.