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Natural Language Understanding

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ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

ICLR 2020 huggingface/transformers

Then, instead of training a model that predicts the original identities of the corrupted tokens, we train a discriminative model that predicts whether each token in the corrupted input was replaced by a generator sample or not.

LANGUAGE MODELLING NATURAL LANGUAGE UNDERSTANDING

Cross-lingual Language Model Pretraining

NeurIPS 2019 huggingface/transformers

On unsupervised machine translation, we obtain 34. 3 BLEU on WMT'16 German-English, improving the previous state of the art by more than 9 BLEU.

LANGUAGE MODELLING NATURAL LANGUAGE UNDERSTANDING UNSUPERVISED MACHINE TRANSLATION

Improving Language Understanding by Generative Pre-Training

Preprint 2018 huggingface/transformers

We demonstrate that large gains on these tasks can be realized by generative pre-training of a language model on a diverse corpus of unlabeled text, followed by discriminative fine-tuning on each specific task.

DOCUMENT CLASSIFICATION LANGUAGE MODELLING NATURAL LANGUAGE INFERENCE NATURAL LANGUAGE UNDERSTANDING QUESTION ANSWERING SEMANTIC SIMILARITY SEMANTIC TEXTUAL SIMILARITY

AllenNLP: A Deep Semantic Natural Language Processing Platform

WS 2018 allenai/allennlp

This paper describes AllenNLP, a platform for research on deep learning methods in natural language understanding.

NATURAL LANGUAGE UNDERSTANDING READING COMPREHENSION SEMANTIC ROLE LABELING

Benchmarking Natural Language Understanding Services for building Conversational Agents

13 Mar 2019RasaHQ/rasa

We have recently seen the emergence of several publicly available Natural Language Understanding (NLU) toolkits, which map user utterances to structured, but more abstract, Dialogue Act (DA) or Intent specifications, while making this process accessible to the lay developer.

INTENT CLASSIFICATION NATURAL LANGUAGE UNDERSTANDING

Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces

25 May 2018snipsco/snips-nlu

This paper presents the machine learning architecture of the Snips Voice Platform, a software solution to perform Spoken Language Understanding on microprocessors typical of IoT devices.

NATURAL LANGUAGE UNDERSTANDING SPEECH RECOGNITION SPOKEN LANGUAGE UNDERSTANDING

A Neural Conversational Model

19 Jun 2015farizrahman4u/seq2seq

We find that this straightforward model can generate simple conversations given a large conversational training dataset.

COMMON SENSE REASONING NATURAL LANGUAGE UNDERSTANDING

Neural Architecture Search with Reinforcement Learning

5 Nov 2016carpedm20/ENAS-pytorch

Our cell achieves a test set perplexity of 62. 4 on the Penn Treebank, which is 3. 6 perplexity better than the previous state-of-the-art model.

IMAGE CLASSIFICATION LANGUAGE MODELLING NATURAL LANGUAGE UNDERSTANDING NEURAL ARCHITECTURE SEARCH