Search Results for author: Antoine Bordes

Found 40 papers, 25 papers with code

Generating Fact Checking Briefs

no code implementations EMNLP 2020 Angela Fan, Aleksandra Piktus, Fabio Petroni, Guillaume Wenzek, Marzieh Saeidi, Andreas Vlachos, Antoine Bordes, Sebastian Riedel

Fact checking at scale is difficult -- while the number of active fact checking websites is growing, it remains too small for the needs of the contemporary media ecosystem.

Fact Checking Question Answering

Image-Chat: Engaging Grounded Conversations

no code implementations ACL 2020 Kurt Shuster, Samuel Humeau, Antoine Bordes, Jason Weston

To test such models, we collect a dataset of grounded human-human conversations, where speakers are asked to play roles given a provided emotional mood or style, as the use of such traits is also a key factor in engagingness (Guo et al., 2019).

Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions

no code implementations22 Jun 2020 Stephen Roller, Y-Lan Boureau, Jason Weston, Antoine Bordes, Emily Dinan, Angela Fan, David Gunning, Da Ju, Margaret Li, Spencer Poff, Pratik Ringshia, Kurt Shuster, Eric Michael Smith, Arthur Szlam, Jack Urbanek, Mary Williamson

We present our view of what is necessary to build an engaging open-domain conversational agent: covering the qualities of such an agent, the pieces of the puzzle that have been built so far, and the gaping holes we have not filled yet.

Continual Learning

ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations

1 code implementation ACL 2020 Fernando Alva-Manchego, Louis Martin, Antoine Bordes, Carolina Scarton, Benoît Sagot, Lucia Specia

Furthermore, we motivate the need for developing better methods for automatic evaluation using ASSET, since we show that current popular metrics may not be suitable when multiple simplification transformations are performed.

MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases

1 code implementation1 May 2020 Louis Martin, Angela Fan, Éric de la Clergerie, Antoine Bordes, Benoît Sagot

Progress in sentence simplification has been hindered by a lack of labeled parallel simplification data, particularly in languages other than English.

Parallel Corpus Mining Text Simplification

Augmenting Transformers with KNN-Based Composite Memory for Dialogue

no code implementations27 Apr 2020 Angela Fan, Claire Gardent, Chloe Braud, Antoine Bordes

Various machine learning tasks can benefit from access to external information of different modalities, such as text and images.

Controllable Sentence Simplification

1 code implementation LREC 2020 Louis Martin, Benoît Sagot, Éric de la Clergerie, Antoine Bordes

Text simplification aims at making a text easier to read and understand by simplifying grammar and structure while keeping the underlying information identical.

Text Simplification

Reference-less Quality Estimation of Text Simplification Systems

1 code implementation WS 2018 Louis Martin, Samuel Humeau, Pierre-Emmanuel Mazaré, Antoine Bordes, Éric Villemonte de la Clergerie, Benoît Sagot

We show that n-gram-based MT metrics such as BLEU and METEOR correlate the most with human judgment of grammaticality and meaning preservation, whereas simplicity is best evaluated by basic length-based metrics.

Machine Translation Text Simplification

Image Chat: Engaging Grounded Conversations

3 code implementations2 Nov 2018 Kurt Shuster, Samuel Humeau, Antoine Bordes, Jason Weston

To test such models, we collect a dataset of grounded human-human conversations, where speakers are asked to play roles given a provided emotional mood or style, as the use of such traits is also a key factor in engagingness (Guo et al., 2019).

Engaging Image Captioning Via Personality

no code implementations CVPR 2019 Kurt Shuster, Samuel Humeau, Hexiang Hu, Antoine Bordes, Jason Weston

While such tasks are useful to verify that a machine understands the content of an image, they are not engaging to humans as captions.

Image Captioning

Training Millions of Personalized Dialogue Agents

1 code implementation EMNLP 2018 Pierre-Emmanuel Mazaré, Samuel Humeau, Martin Raison, Antoine Bordes

Current dialogue systems are not very engaging for users, especially when trained end-to-end without relying on proactive reengaging scripted strategies.

Weaver: Deep Co-Encoding of Questions and Documents for Machine Reading

no code implementations27 Apr 2018 Martin Raison, Pierre-Emmanuel Mazaré, Rajarshi Das, Antoine Bordes

This paper aims at improving how machines can answer questions directly from text, with the focus of having models that can answer correctly multiple types of questions and from various types of texts, documents or even from large collections of them.

Open-Domain Question Answering Reading Comprehension

DeSIGN: Design Inspiration from Generative Networks

1 code implementation3 Apr 2018 Othman Sbai, Mohamed Elhoseiny, Antoine Bordes, Yann Lecun, Camille Couprie

Can an algorithm create original and compelling fashion designs to serve as an inspirational assistant?

Image Generation

Fader Networks:Manipulating Images by Sliding Attributes

no code implementations NeurIPS 2017 Guillaume Lample, Neil Zeghidour, Nicolas Usunier, Antoine Bordes, Ludovic Denoyer, Marc'Aurelio Ranzato

This paper introduces a new encoder-decoder architecture that is trained to reconstruct images by disentangling the salient information of the image and the values of attributes directly in the latent space.

StarSpace: Embed All The Things!

2 code implementations12 Sep 2017 Ledell Wu, Adam Fisch, Sumit Chopra, Keith Adams, Antoine Bordes, Jason Weston

A framework for training and evaluating AI models on a variety of openly available dialogue datasets.

Text Classification Word Embeddings

Fader Networks: Manipulating Images by Sliding Attributes

3 code implementations1 Jun 2017 Guillaume Lample, Neil Zeghidour, Nicolas Usunier, Antoine Bordes, Ludovic Denoyer, Marc'Aurelio Ranzato

This paper introduces a new encoder-decoder architecture that is trained to reconstruct images by disentangling the salient information of the image and the values of attributes directly in the latent space.

ParlAI: A Dialog Research Software Platform

18 code implementations EMNLP 2017 Alexander H. Miller, Will Feng, Adam Fisch, Jiasen Lu, Dhruv Batra, Antoine Bordes, Devi Parikh, Jason Weston

We introduce ParlAI (pronounced "par-lay"), an open-source software platform for dialog research implemented in Python, available at http://parl. ai.

Visual Question Answering

Reading Wikipedia to Answer Open-Domain Questions

9 code implementations ACL 2017 Danqi Chen, Adam Fisch, Jason Weston, Antoine Bordes

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.

Open-Domain Question Answering Reading Comprehension

Tracking the World State with Recurrent Entity Networks

3 code implementations12 Dec 2016 Mikael Henaff, Jason Weston, Arthur Szlam, Antoine Bordes, Yann Lecun

The EntNet sets a new state-of-the-art on the bAbI tasks, and is the first method to solve all the tasks in the 10k training examples setting.

Question Answering

Learning End-to-End Goal-Oriented Dialog

6 code implementations24 May 2016 Antoine Bordes, Y-Lan Boureau, Jason Weston

We show similar result patterns on data extracted from an online concierge service.

Goal-Oriented Dialog Slot Filling

Large-scale Simple Question Answering with Memory Networks

3 code implementations5 Jun 2015 Antoine Bordes, Nicolas Usunier, Sumit Chopra, Jason Weston

Training large-scale question answering systems is complicated because training sources usually cover a small portion of the range of possible questions.

Question Answering Transfer Learning

Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks

18 code implementations19 Feb 2015 Jason Weston, Antoine Bordes, Sumit Chopra, Alexander M. Rush, Bart van Merriënboer, Armand Joulin, Tomas Mikolov

One long-term goal of machine learning research is to produce methods that are applicable to reasoning and natural language, in particular building an intelligent dialogue agent.

Question Answering Reading Comprehension

Memory Networks

4 code implementations15 Oct 2014 Jason Weston, Sumit Chopra, Antoine Bordes

We describe a new class of learning models called memory networks.

Question Answering

Question Answering with Subgraph Embeddings

1 code implementation EMNLP 2014 Antoine Bordes, Sumit Chopra, Jason Weston

Training our system using pairs of questions and structured representations of their answers, and pairs of question paraphrases, yields competitive results on a competitive benchmark of the literature.

Question Answering

Open Question Answering with Weakly Supervised Embedding Models

no code implementations16 Apr 2014 Antoine Bordes, Jason Weston, Nicolas Usunier

Building computers able to answer questions on any subject is a long standing goal of artificial intelligence.

Question Answering

Translating Embeddings for Modeling Multi-relational Data

2 code implementations NeurIPS 2013 Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, Oksana Yakhnenko

We consider the problem of embedding entities and relationships of multi-relational data in low-dimensional vector spaces.

Link Prediction

Connecting Language and Knowledge Bases with Embedding Models for Relation Extraction

no code implementations EMNLP 2013 Jason Weston, Antoine Bordes, Oksana Yakhnenko, Nicolas Usunier

This paper proposes a novel approach for relation extraction from free text which is trained to jointly use information from the text and from existing knowledge.

Relation Extraction

Irreflexive and Hierarchical Relations as Translations

no code implementations26 Apr 2013 Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, Oksana Yakhnenko

We consider the problem of embedding entities and relations of knowledge bases in low-dimensional vector spaces.

A Semantic Matching Energy Function for Learning with Multi-relational Data

no code implementations15 Jan 2013 Xavier Glorot, Antoine Bordes, Jason Weston, Yoshua Bengio

Large-scale relational learning becomes crucial for handling the huge amounts of structured data generated daily in many application domains ranging from computational biology or information retrieval, to natural language processing.

Information Retrieval Link Prediction +1

A latent factor model for highly multi-relational data

no code implementations NeurIPS 2012 Rodolphe Jenatton, Nicolas L. Roux, Antoine Bordes, Guillaume R. Obozinski

While there is a large body of work focused on modeling these data, few considered modeling these multiple types of relationships jointly.

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