Research Area
Year Published

430 Results

July 28, 2019

ELI5: Long Form Question Answering

Association for Computational Linguistics (ACL)

We introduce the first large-scale corpus for long-form question answering, a task requiring elaborate and in-depth answers to open-ended questions. The dataset comprises 270K threads from the Reddit forum “Explain Like I’m Five” (ELI5) where an online community provides answers to questions which are comprehensible by five year olds.

By: Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, Michael Auli

July 28, 2019

Miss Tools and Mr Fruit: Emergent communication in agents learning about object affordances

Association for Computational Linguistics (ACL)

Recent research studies communication emergence in communities of deep network agents assigned a joint task, hoping to gain insights on human language evolution. We propose here a new task capturing crucial aspects of the human environment, such as natural object affordances, and of human conversation, such as full symmetry among the participants.

By: Diane Bouchacourt, Marco Baroni

July 28, 2019

Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings

Association for Computational Linguistics (ACL)

We consider the task of inferring is-a relationships from large text corpora. For this purpose, we propose a new method combining hyperbolic embeddings and Hearst patterns. This approach allows us to set appropriate constraints for inferring concept hierarchies from distributional contexts while also being able to predict missing is-a-relationships and to correct wrong extractions.

By: Matt Le, Stephen Roller, Laetitia Papaxanthos, Douwe Kiela, Maximilian Nickel

July 28, 2019

What makes a good conversation? How controllable attributes affect human judgments

North American Chapter of the Association for Computational Linguistics (NAACL)

In this work, we examine two controllable neural text generation methods, conditional training and weighted decoding, in order to control four important attributes for chitchat dialogue: repetition, specificity, response-relatedness and question-asking.

By: Abigail See, Stephen Roller, Douwe Kiela, Jason Weston

July 28, 2019

CNNs found to jump around more skillfully than RNNs: Compositional generalization in seq2seq convolutional networks

Annual Meeting of the Association for Computational Linguistics (ACL)

We test here a convolutional network (CNN) on these tasks, reporting hugely improved performance with respect to RNNs. Despite the big improvement, the CNN has however not induced systematic rules, suggesting that the difference between compositional and non-compositional behaviour is not clear-cut.

By: Roberto Dessi, Marco Baroni

July 28, 2019

Translating Translationese: A Two-Step Approach to Unsupervised Machine Translation

Association for Computational Linguistics (ACL)

Given a rough, word-by-word gloss of a source language sentence, target language natives can uncover the latent, fully-fluent rendering of the translation. In this work we explore this intuition by breaking translation into a two step process: generating a rough gloss by means of a dictionary and then ‘translating’ the resulting pseudo-translation, or ‘Translationese’ into a fully fluent translation.

By: Nima Pourdamghani, Nada Aldarrab, Marjan Ghazvininejad, Kevin Knight, Jonathan May

July 27, 2019

Adaptive Attention Span in Transformers

Association for Computational Linguistics (ACL)

We propose a novel self-attention mechanism that can learn its optimal attention span. This allows us to extend significantly the maximum context size used in Transformer, while maintaining control over their memory footprint and computational time.

By: Sainbayar Sukhbaatar, Edouard Grave, Piotr Bojanowski, Armand Joulin

July 27, 2019

Unsupervised Question Answering by Cloze Translation

Association for Computational Linguistics (ACL)

Obtaining training data for Question Answering (QA) is time-consuming and resource-intensive, and existing QA datasets are only available for limited domains and languages. In this work, we explore to what extent high quality training data is actually required for Extractive QA, and investigate the possibility of unsupervised Extractive QA.

By: Patrick Lewis, Ludovic Denoyer, Sebastian Riedel

July 27, 2019

Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings

Association for Computational Linguistics (ACL)

Machine translation is highly sensitive to the size and quality of the training data, which has led to an increasing interest in collecting and filtering large parallel corpora. In this paper, we propose a new method for this task based on multilingual sentence embeddings.

By: Mikel Artetxe, Holger Schwenk

July 26, 2019

On the Distribution of Deep Clausal Embeddings: A Large Cross-linguistic Study

Association for Computational Linguistics (ACL)

We introduce here a collection of large, dependency-parsed written corpora in 17 languages, that allow us, for the first time, to capture clausal embedding through dependency graphs and assess their distribution.

By: Damián E. Blasi, Ryan Cotterell, Lawrence Wolf-Sonkin, Sabine Stoll, Balthasar Bickel, Marco Baroni