Search Results for author: Samuel Humeau

Found 10 papers, 6 papers with code

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).

Poly-encoders: Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring

2 code implementations ICLR 2020 Samuel Humeau, Kurt Shuster, Marie-Anne Lachaux, Jason Weston

The use of deep pre-trained transformers has led to remarkable progress in a number of applications (Devlin et al., 2018).

Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack

no code implementations IJCNLP 2019 Emily Dinan, Samuel Humeau, Bharath Chintagunta, Jason Weston

The detection of offensive language in the context of a dialogue has become an increasingly important application of natural language processing.

Learning to Speak and Act in a Fantasy Text Adventure Game

no code implementations IJCNLP 2019 Jack Urbanek, Angela Fan, Siddharth Karamcheti, Saachi Jain, Samuel Humeau, Emily Dinan, Tim Rocktäschel, Douwe Kiela, Arthur Szlam, Jason Weston

We analyze the ingredients necessary for successful grounding in this setting, and how each of these factors relate to agents that can talk and act successfully.

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 +1

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.

Multimodal Attribute Extraction

1 code implementation29 Nov 2017 Robert L. Logan IV, Samuel Humeau, Sameer Singh

The broad goal of information extraction is to derive structured information from unstructured data.

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