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NLP-progress reviews and mentions
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Upcoming App Announcement: Lemmatize, a Foreign Language Reader
A standard step in Chinese text processing is word segmentation, which deals with this problem.
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[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.
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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)
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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.
- Typo correction using NLP
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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.
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A note from our sponsor - SaaSHub
www.saashub.com | 29 Mar 2024
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sebastianruder/NLP-progress is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of NLP-progress is Python.