NLP-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks. (by sebastianruder)

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Reviews and mentions

Posts with mentions or reviews of NLP-progress. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-12.
  • [P] NLP "tl;dr" Notes on Transformers
    It would also be cool to have some charts with parameter density and even overall effectiveness (a tl;dr version of SOTA-trackers, maybe?) if that doesn't prove too infeasible.
  • What are state-of-the-art methods for abstractive text summarization ?
  • BreadPanes 81: "They/Them"
    As I said It increase ambiguity and cognitive overheard, needlessly given that "it" exists. Moreover it also make it harder for artificial intelligence to understand human text https://github.com/sebastianruder/NLP-progress/blob/master/english/coreference_resolution.md
  • [Request] Curated Advanced NLP Resources
    I could not find it on the internet (including on GitHub, Kaggle, Medium, or Reddit.) And, I know about NLP Progress and The Super Duper NLP Repo.
  • How do you guys find/ keep up to date with the latest NLP papers?
    Another great resource for keeping tabs on the state of the art performance for common tasks is: NLP Progress
    For someone who needs to be on top of the latest research - Twitter (distraction-prone, marketing-friendly, instantly-gratifying, quick), newsletters in ML + NLP (https://jack-clark.net/, ruder.io, offconvex.org, etc.) (distraction-free, generic, time-consuming), SOTA chasing (https://paperswithcode.com/, http://nlpprogress.com/) (distraction-free, generic + focused, code-friendly)
  • How to do undergrad research the right way?
    NLP is a very broad topic and like you said it can be extremely overwhelming to keep up with all the recent advancements, especially if you are a beginner. I would suggest you to take a look at nlp_tasks or NLP-progress or The Big Bad NLP Database to get an idea of the different tasks in NLP and see if you can find anything that looks interesting to you.
  • Consejo o ayuda
    that's hard to say without much more information. e.g., how are you encoding the text and passing as input to the neural net? can you say more about the architecture? e.g., RNN, LSTM, transformer? if you're doing NLP, there are lots of good options to try. E.g., check out hugging face or spacy. this is also a good resource: https://github.com/sebastianruder/NLP-progress
  • Current Sota for Multiclass Text Classification?
    Does anyone know where i can find data on the best performing multiclass text classifiers? This is the only info i could find and it seems it hasn't been updated since 2019.
  • Typo correction using NLP
  • What are some classification tasks where BERT-based models don't work well? In a similar vein, what are some generative tasks where fine-tuning GPT-2/LM does not work well?
    One place to start is nlp progress if leader boards are your thing, if the model on top of the leader board is not a transformer based model and one further down is, you have your answer.
  • SOTA approaches in question answering

Stats

Basic NLP-progress repo stats
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7.5
6 days ago

sebastianruder/NLP-progress is an open source project licensed under MIT License which is an OSI approved license.

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