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Year Published

129 Results

July 31, 2017

Enriching Word Vectors with Subword Information

TACL, Association for Computational Linguistics (ACL 2017)

In this paper, we propose a new approach based on the skipgram model, where each word is represented as a bag of character n-grams.

By: Armand Joulin, Edouard Grave, Piotr Bojanowski, Tomas Mikolov
July 31, 2017

Learning Multilingual Joint Sentence Embeddings with Neural Machine Translation

ACL workshop on Representation Learning for NLP (ACL)

In this paper, we use the framework of neural machine translation to learn joint sentence representations across six very different languages. Our aim is that a representation which is independent of the language, is likely to capture the underlying semantics.

By: Holger Schwenk, Matthijs Douze
July 30, 2017

Automatically Generating Rhythmic Verse with Neural Networks

Association for Computational Linguistics (ACL 2017)

We propose two novel methodologies for the automatic generation of rhythmic poetry in a variety of forms.

By: Jack Hopkins, Douwe Kiela
July 30, 2017

A Convolutional Encoder Model for Neural Machine Translation

Association for Computational Linguistics 2017 (ACL 2017)

The prevalent approach to neural machine translation relies on bi-directional LSTMs to encode the source sentence. We present a faster and simpler architecture based on a succession of convolutional layers.

By: Jonas Gehring, Michael Auli, David Grangier, Yann Dauphin
July 30, 2017

Reading Wikipedia to Answer Open-Domain Questions

Association for Computational Linguistics (ACL 2017)

This paper proposes to tackle open- domain question answering using Wikipedia as the unique knowledge source: the answer to any factoid question is a text span in a Wikipedia article.

By: Danqi Chen, Adam Fisch, Jason Weston, Antoine Bordes
July 21, 2017

Densely Connected Convolutional Networks

CVPR 2017

In this paper, we embrace the observation that hat convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the input and those close to the output, and introduce the Dense Convolutional Network (DenseNet), which connects each layer to every other layer in a feed-forward fashion.

By: Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger
July 21, 2017

Discovering Causal Signals in Images

CVPR 2017

This paper establishes the existence of observable footprints that reveal the “causal dispositions” of the object categories appearing in collections of images.

By: David Lopez-Paz, Robert Nishihara, Soumith Chintala, Bernhard Scholkopf, Leon Bottou
July 21, 2017

Relationship Proposal Networks

Conference on Computer Vision and Pattern Recognition 2017

In this paper we address the challenges of image scene object recognition by using pairs of related regions in images to train a relationship proposer that at test time produces a manageable number of related regions.

By: Ahmed Elgammal, Ji Zhang, Mohamed Elhoseiny, Scott Cohen, Walter Chang
July 21, 2017

Link the head to the “beak”: Zero Shot Learning from Noisy Text Description at Part Precision

CVPR 2017

In this paper, we study learning visual classifiers from unstructured text descriptions at part precision with no training images. We propose a learning framework that is able to connect text terms to its relevant parts and suppress connections to non-visual text terms without any part-text annotations. F

By: Mohamed Elhoseiny, Yizhe Zhu, Han Zhang, Ahmed Elgammal
July 21, 2017

CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning

CVPR 2017

We present a diagnostic dataset that tests a range of visual reasoning abilities. It contains minimal biases and has detailed annotations describing the kind of reasoning each question requires.

By: Bharath Hariharan, Justin Johnson, Larry Zitnick, Laurens van der Maaten, Li Fei-Fei, Ross Girshick