NAACL 2019

Pooled Contextualized Embeddings for Named Entity Recognition

NAACL 2019 zalandoresearch/flair

We make all code and pre-trained models available to the research community for use and reproduction.

#6 best model for Named Entity Recognition on CoNLL 2003 (English) (using extra training data)

NAMED ENTITY RECOGNITION

FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP

NAACL 2019 zalandoresearch/flair

We present FLAIR, an NLP framework designed to facilitate training and distribution of state-of-the-art sequence labeling, text classification and language models.

TEXT CLASSIFICATION

fairseq: A Fast, Extensible Toolkit for Sequence Modeling

NAACL 2019 facebookresearch/fairseq-py

fairseq is an open-source sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling, and other text generation tasks.

LANGUAGE MODELLING TEXT GENERATION

Star-Transformer

NAACL 2019 fastnlp/fastNLP

Although Transformer has achieved great successes on many NLP tasks, its heavy structure with fully-connected attention connections leads to dependencies on large training data.

NAMED ENTITY RECOGNITION NATURAL LANGUAGE INFERENCE SENTIMENT ANALYSIS TEXT CLASSIFICATION

Better Word Embeddings by Disentangling Contextual n-Gram Information

NAACL 2019 epfml/sent2vec

Pre-trained word vectors are ubiquitous in Natural Language Processing applications.

WORD EMBEDDINGS

Consistency by Agreement in Zero-shot Neural Machine Translation

NAACL 2019 google-research/language

Generalization and reliability of multilingual translation often highly depend on the amount of available parallel data for each language pair of interest.

MACHINE TRANSLATION ZERO-SHOT MACHINE TRANSLATION

compare-mt: A Tool for Holistic Comparison of Language Generation Systems

NAACL 2019 neulab/compare-mt

In this paper, we describe compare-mt, a tool for holistic analysis and comparison of the results of systems for language generation tasks such as machine translation.

MACHINE TRANSLATION TEXT GENERATION

Rethinking Complex Neural Network Architectures for Document Classification

NAACL 2019 castorini/hedwig

Neural network models for many NLP tasks have grown increasingly complex in recent years, making training and deployment more difficult.

DOCUMENT CLASSIFICATION LANGUAGE MODELLING

Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence

NAACL 2019 HSLCY/ABSA-BERT-pair

Aspect-based sentiment analysis (ABSA), which aims to identify fine-grained opinion polarity towards a specific aspect, is a challenging subtask of sentiment analysis (SA).

ASPECT-BASED SENTIMENT ANALYSIS NATURAL LANGUAGE INFERENCE QUESTION ANSWERING