ACL 2017

Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning

ACL 2017 deepmipt/DeepPavlov

End-to-end learning of recurrent neural networks (RNNs) is an attractive solution for dialog systems; however, current techniques are data-intensive and require thousands of dialogs to learn simple behaviors.

Get To The Point: Summarization with Pointer-Generator Networks

ACL 2017 abisee/cnn-dailymail

Neural sequence-to-sequence models have provided a viable new approach for abstractive text summarization (meaning they are not restricted to simply selecting and rearranging passages from the original text).

ABSTRACTIVE TEXT SUMMARIZATION

Semi-supervised Multitask Learning for Sequence Labeling

ACL 2017 marekrei/sequence-labeler

We propose a sequence labeling framework with a secondary training objective, learning to predict surrounding words for every word in the dataset.

CHUNKING GRAMMATICAL ERROR DETECTION LANGUAGE MODELLING NAMED ENTITY RECOGNITION (NER) PART-OF-SPEECH TAGGING

Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access

ACL 2017 MiuLab/KB-InfoBot

In this paper, we address this limitation by replacing symbolic queries with an induced "soft" posterior distribution over the KB that indicates which entities the user is interested in.

TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

ACL 2017 mandarjoshi90/triviaqa

We present TriviaQA, a challenging reading comprehension dataset containing over 650K question-answer-evidence triples.

READING COMPREHENSION

Multimodal Word Distributions

ACL 2017 benathi/multisense-prob-fasttext

Word embeddings provide point representations of words containing useful semantic information.

WORD EMBEDDINGS