What is ACL paper?

What is ACL paper?

The ACL Anthology currently hosts 73877 papers on the study of computational linguistics and natural language processing. Subscribe to the mailing list to receive announcements and updates to the Anthology. The Anthology can archive your poster or presentation! Please submit them in PDF format by filling out this form.

How many types of machine learning are there?

These are three types of machine learning: supervised learning, unsupervised learning, and reinforcement learning.

Is ACL Anthology a journal?

The ACL Anthology Reference Corpus is an English corpus made up of conference and journal papers in natural language processing and computational linguistics. The corpus was prepared from papers of the ACL Anthology, up to 2015, containing 18,288 articles.

What are the top conferences for NLP/CL?

I found this very useful article about the top NLP/CL conferences, which mentions that to put it simply, for NLP, consider only these six top conferences: ACL, EMNLP, NAACL, EACL, COLING and CoNLL. Also maybe several other conferences in related fields: Special Interest Group on Information Retrieval (SIGIR)

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Where can I find resources about NLP?

LREC is the best conference to find information about resources for NLP and the place for people who create language resources to come together. But the papers are not peer-reviewed: look for the NLP-related content to also be published elsewhere, and only then trust the papers in LREC for their NLP content 7.

What does ijcnlp stand for?

International Joint Conference on Natural Language Processing (IJCNLP) IEEE International Conference on Semantic Computing (ICSC) Conference on Computational Natural Language Learning (CoNLL)

What’s new in word representation in NLP?

Word representation is a common task in NLP. Here, authors formulate new frameworks that combine classical word embedding techniques (like Skip-gram) with more modern approaches based on contextual embedding (BERT, XLNet). The left plot shows F1 scores of BERT-NCE and INFOWORD as we increase the percentage of training examples on SQuAD (dev).