EMNLP 2017
NeuroNER: an easy-to-use program for named-entity recognition based on neural networks
EMNLP 2017
• Franck-Dernoncourt/NeuroNER
• 
Named-entity recognition (NER) aims at identifying entities of interest in a text.
Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm
EMNLP 2017
• bfelbo/deepmoji
•
NLP tasks are often limited by scarcity of manually annotated data.
DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning
We study the problem of learning to reason in large scale knowledge graphs (KGs).
KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS
Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging
EMNLP 2017
• UKPLab/elmo-bilstm-cnn-crf
•
In this paper we show that reporting a single performance score is insufficient to compare non-deterministic approaches.
Fast and Accurate Entity Recognition with Iterated Dilated Convolutions
EMNLP 2017
• iesl/dilated-cnn-ner
•
Today when many practitioners run basic NLP on the entire web and large-volume traffic, faster methods are paramount to saving time and energy costs.
#4 best model for
Named Entity Recognition (NER)
on Ontonotes v5 (English)
Determining Semantic Textual Similarity using Natural Deduction Proofs
Determining semantic textual similarity is a core research subject in natural language processing.
Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback
EMNLP 2017
• khanhptnk/bandit-nmt
• 
Machine translation is a natural candidate problem for reinforcement learning from human feedback: users provide quick, dirty ratings on candidate translations to guide a system to improve.