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Upcoming App Announcement: Lemmatize, a Foreign Language Reader
2 projects | reddit.com/r/languagelearning | 11 Nov 2021
A standard step in Chinese text processing is word segmentation, which deals with this problem.
Is there as site tracking computer vision process?
1 project | reddit.com/r/computervision | 3 Nov 2021
NLP has a github project tracking NLP progress, https://github.com/sebastianruder/NLP-progress. I wanna know if there is one tracking computer vision progress.
[P] NLP "tl;dr" Notes on Transformers
2 projects | reddit.com/r/MachineLearning | 12 Aug 2021
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 ?
1 project | reddit.com/r/LanguageTechnology | 3 Jun 2021
BreadPanes 81: "They/Them"
1 project | reddit.com/r/antifastonetoss | 22 May 2021
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
1 project | reddit.com/r/datascience | 5 May 2021
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?
2 projects | reddit.com/r/LanguageTechnology | 21 Apr 2021
Another great resource for keeping tabs on the state of the art performance for common tasks is: NLP Progress2 projects | reddit.com/r/LanguageTechnology | 21 Apr 2021
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?
2 projects | reddit.com/r/LanguageTechnology | 14 Apr 2021
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
1 project | reddit.com/r/deeplearning | 9 Apr 2021
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
How to create a dataset for training NER models when you only have entity data
1 project | reddit.com/r/LanguageTechnology | 18 Oct 2021
We have a list of entities in text files separated with a new line. We intend to train the flair model to detect these entities in text, but NER models require the entity to be labeled in a paragraph with BOI format.
Preparing data for training NER models
1 project | reddit.com/r/LanguageTechnology | 11 Oct 2021
Training most of the Named Entity Recognition (NER) models for example Flair usually needs to format data in BOI tagging) scheme as shown below where each sentence is separated by blank line
German POS Corpus for Commercial use
2 projects | reddit.com/r/LanguageTechnology | 5 Oct 2021
I had the same problem a couple years ago. I think Flair, form Zalando uses a different Corpus. However, it's not great and I am pretty sure they are infringing the license anyway...
Advice for how to approach classifying apartment posts on facebook?
1 project | reddit.com/r/LanguageTechnology | 4 Jun 2021
For example, my first approach to the pet sentences would be to label all sentences within a respective text corpus containing according information for either yes or no. You would then convert this to a tertiary tag set, something like ["pet allowed", "pet not allowed", "irrelevant"]. You could then try out a model based on SentenceBert, other sentence-level embeddings/language models or 1D CNNs for this. flairNLP (https://github.com/flairNLP/flair) is a small, little framework which provides comfortable high-level access to different common language models which integrates perfectly with pyTorch.
SpaCy VS Transformers for NER
2 projects | reddit.com/r/LanguageTechnology | 11 Mar 2021
For NER, if you don't need the full toolkit of spacy, I'd highly recommend checking out Flair. It will likely run faster than transformer-based models (like en_core_web_trf) and it tends to be one of the best performing approaches to NER.
[D] NLP Q: How to extract this part from a messy short text?
1 project | reddit.com/r/MachineLearning | 4 Mar 2021
You then train the whole thing on sequences where each position has a label that is begin/inside/outside and thus you can calculate cross-entropy loss. So all in all it is basically: https://github.com/flairNLP/flair, https://huggingface.co/transformers/model_doc/distilbert.html#tfdistilbertforsequenceclassification or any huggingface model "for sequence classificaiton" or but just char based instead of word based. The CRF layer (as included in flair) is optional but may be useful.
What are some alternatives?
Stanza - Official Stanford NLP Python Library for Many Human Languages
seqeval - A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)
gensim - Topic Modelling for Humans
spacy-models - 💫 Models for the spaCy Natural Language Processing (NLP) library
MAX-Toxic-Comment-Classifier - Detect 6 types of toxicity in user comments.
nnsplit - Semantic text segmentation. For sentence boundary detection, compound splitting and more.
BERT-NER - Pytorch-Named-Entity-Recognition-with-BERT