NLPExplorer

Learning Grounded Meaning Representations with Autoencoders

Carina Silberer | Mirella Lapata |

Paper Details:

Month: June
Year: 2014
Location: Baltimore, Maryland
Venue: ACL |

Citations

URL

Predicting the Evocation Relation between Lexicalized Concepts
Yoshihiko Hayashi |

Is an Image Worth More than a Thousand Words? On the Fine-Grain Semantic Differences between Visual and Linguistic Representations
Guillem Collell | Marie-Francine Moens |

Multimodal Grounding for Language Processing
Lisa Beinborn | Teresa Botschen | Iryna Gurevych |

Learning Image Embeddings using Convolutional Neural Networks for Improved Multi-Modal Semantics
Douwe Kiela | Léon Bottou |

Learning Abstract Concept Embeddings from Multi-Modal Data: Since You Probably Can’t See What I Mean
Felix Hill | Anna Korhonen |

Visual Bilingual Lexicon Induction with Transferred ConvNet Features
Douwe Kiela | Ivan Vulić | Stephen Clark |

Multi- and Cross-Modal Semantics Beyond Vision: Grounding in Auditory Perception
Douwe Kiela | Stephen Clark |

Comparing Data Sources and Architectures for Deep Visual Representation Learning in Semantics
Douwe Kiela | Anita Lilla Verő | Stephen Clark |

Numerically Grounded Language Models for Semantic Error Correction
Georgios Spithourakis | Isabelle Augenstein | Sebastian Riedel |

Deriving continous grounded meaning representations from referentially structured multimodal contexts
Sina Zarrieß | David Schlangen |

Associative Multichannel Autoencoder for Multimodal Word Representation
Shaonan Wang | Jiajun Zhang | Chengqing Zong |

A vision-grounded dataset for predicting typical locations for verbs
Nelson Mukuze | Anna Rohrbach | Vera Demberg | Bernt Schiele |

Combining Language and Vision with a Multimodal Skip-gram Model
Angeliki Lazaridou | Nghia The Pham | Marco Baroni |

Multimodal Semantic Learning from Child-Directed Input
Angeliki Lazaridou | Grzegorz Chrupała | Raquel Fernández | Marco Baroni |

The Emergence of Semantics in Neural Network Representations of Visual Information
Dhanush Dharmaretnam | Alona Fyshe |

Perceptually Grounded Selectional Preferences
Ekaterina Shutova | Niket Tandon | Gerard de Melo |

Exploiting Image Generality for Lexical Entailment Detection
Douwe Kiela | Laura Rimell | Ivan Vulić | Stephen Clark |

Learning Text Pair Similarity with Context-sensitive Autoencoders
Hadi Amiri | Philip Resnik | Jordan Boyd-Graber | Hal Daumé III |

Multimodal Pivots for Image Caption Translation
Julian Hitschler | Shigehiko Schamoni | Stefan Riezler |

Multi-Modal Representations for Improved Bilingual Lexicon Learning
Ivan Vulić | Douwe Kiela | Stephen Clark | Marie-Francine Moens |

Domain Specific Named Entity Recognition Referring to the Real World by Deep Neural Networks
Suzushi Tomori | Takashi Ninomiya | Shinsuke Mori |

MMFeat: A Toolkit for Extracting Multi-Modal Features
Douwe Kiela |

Interpretable and Compositional Relation Learning by Joint Training with an Autoencoder
Ryo Takahashi | Ran Tian | Kentaro Inui |

Do Neural Network Cross-Modal Mappings Really Bridge Modalities?
Guillem Collell | Marie-Francine Moens |

Replicability Analysis for Natural Language Processing: Testing Significance with Multiple Datasets
Rotem Dror | Gili Baumer | Marina Bogomolov | Roi Reichart |

Learning Representations Specialized in Spatial Knowledge: Leveraging Language and Vision
Guillem Collell | Marie-Francine Moens |

Semantic Frames and Visual Scenes: Learning Semantic Role Inventories from Image and Video Descriptions
Ekaterina Shutova | Andreas Wundsam | Helen Yannakoudakis |

Comparing Attribute Classifiers for Interactive Language Grounding
Yanchao Yu | Arash Eshghi | Oliver Lemon |

Capturing Discriminative Attributes in a Distributional Space: Task Proposal
Alicia Krebs | Denis Paperno |

Interactively Learning Visually Grounded Word Meanings from a Human Tutor
Yanchao Yu | Arash Eshghi | Oliver Lemon |

Training an adaptive dialogue policy for interactive learning of visually grounded word meanings
Yanchao Yu | Arash Eshghi | Oliver Lemon |

Clinical Text Prediction with Numerically Grounded Conditional Language Models
Georgios Spithourakis | Steffen Petersen | Sebastian Riedel |

Complex Verbs are Different: Exploring the Visual Modality in Multi-Modal Models to Predict Compositionality
Maximilian Köper | Sabine Schulte im Walde |

The BURCHAK corpus: a Challenge Data Set for Interactive Learning of Visually Grounded Word Meanings
Yanchao Yu | Arash Eshghi | Gregory Mills | Oliver Lemon |

Spectral Graph-Based Method of Multimodal Word Embedding
Kazuki Fukui | Takamasa Oshikiri | Hidetoshi Shimodaira |

Learning how to Learn: An Adaptive Dialogue Agent for Incrementally Learning Visually Grounded Word Meanings
Yanchao Yu | Arash Eshghi | Oliver Lemon |

VOILA: An Optimised Dialogue System for Interactively Learning Visually-Grounded Word Meanings (Demonstration System)
Yanchao Yu | Arash Eshghi | Oliver Lemon |

Incorporating visual features into word embeddings: A bimodal autoencoder-based approach
Mika Hasegawa | Tetsunori Kobayashi | Yoshihiko Hayashi |

Field Of Study

Linguistic Trends

Embeddings

Task

Semantic Similarity Information Retrieval Question Answering

Approach

Deep Learning

Language

Chinese English

Dataset

News

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