b'ADAPT Centre'

research

∙ 04/16/2019

CloudSegNet: A Deep Network for Nychthemeron Cloud Image Segmentation

We analyze clouds in the earth's atmosphere using ground-based sky camer...

Soumyabrata Dev, et al. ∙

research

∙ 10/10/2018

End-to-End Content and Plan Selection for Data-to-Text Generation

Learning to generate fluent natural language from structured data with n...

Sebastian Gehrmann, et al. ∙

research

∙ 04/03/2020

A Set of Recommendations for Assessing Human-Machine Parity in Language Translation

The quality of machine translation has increased remarkably over the pas...

Samuel Läubli, et al. ∙

research

∙ 12/19/2017

Any-gram Kernels for Sentence Classification: A Sentiment Analysis Case Study

Any-gram kernels are a flexible and efficient way to employ bag-of-n-gra...

Rasoul Kaljahi, et al. ∙

research

∙ 04/14/2017

Exploiting Cross-Sentence Context for Neural Machine Translation

In translation, considering the document as a whole can help to resolve ...

Longyue Wang, et al. ∙

research

∙ 02/04/2017

Doubly-Attentive Decoder for Multi-modal Neural Machine Translation

We introduce a Multi-modal Neural Machine Translation model in which a d...

Iacer Calixto, et al. ∙

research

∙ 02/03/2017

Multilingual Multi-modal Embeddings for Natural Language Processing

We propose a novel discriminative model that learns embeddings from mult...

Iacer Calixto, et al. ∙

research

∙ 01/23/2017

Incorporating Global Visual Features into Attention-Based Neural Machine Translation

We introduce multi-modal, attention-based neural machine translation (NM...

Iacer Calixto, et al. ∙

research

∙ 05/15/2016

Machine Translation Evaluation: A Survey

We introduce the Machine Translation (MT) evaluation survey that contain...

Aaron Li-Feng Han, et al. ∙

research

∙ 01/10/2018

Translating Pro-Drop Languages with Reconstruction Models

Pronouns are frequently omitted in pro-drop languages, such as Chinese, ...

Longyue Wang, et al. ∙

research

∙ 01/15/2018

What Level of Quality can Neural Machine Translation Attain on Literary Text?

Given the rise of a new approach to MT, Neural MT (NMT), and its promisi...

Antonio Toral, et al. ∙

research

∙ 04/05/2018

Chinese-Portuguese Machine Translation: A Study on Building Parallel Corpora from Comparable Texts

Although there are increasing and significant ties between China and Por...

Siyou Liu, et al. ∙

research

∙ 05/20/2018

Generating High-Quality Surface Realizations Using Data Augmentation and Factored Sequence Models

This work presents a new state of the art in reconstruction of surface r...

Henry Elder, et al. ∙

research

∙ 09/03/2018

Multi-Level Structured Self-Attentions for Distantly Supervised Relation Extraction

Attention mechanisms are often used in deep neural networks for distantl...

Jinhua Du, et al. ∙

research

∙ 10/10/2018

Persistence pays off: Paying Attention to What the LSTM Gating Mechanism Persists

Language Models (LMs) are important components in several Natural Langua...

Giancarlo D. Salton, et al. ∙

research

∙ 10/15/2018

Learning to Jointly Translate and Predict Dropped Pronouns with a Shared Reconstruction Mechanism

Pronouns are frequently omitted in pro-drop languages, such as Chinese, ...

Longyue Wang, et al. ∙

research

∙ 12/22/2018

TEST: A Terminology Extraction System for Technology Related Terms

Tracking developments in the highly dynamic data-technology landscape ar...

Murhaf Hossari, et al. ∙

research

∙ 01/19/2019

What Makes a Good Conversation? Challenges in Designing Truly Conversational Agents

Conversational agents promise conversational interaction but fail to del...

Leigh Clark, et al. ∙

research

∙ 04/25/2019

Predicting Stroke from Electronic Health Records

Studies have identified various risk factors associated with the onset o...

Chidozie Shamrock Nwosu, et al. ∙

research

∙ 05/24/2019

Designing a Symbolic Intermediate Representation for Neural Surface Realization

Generated output from neural NLG systems often contain errors such as ha...

Henry Elder, et al. ∙

research

∙ 11/18/2019

Using Mapping Languages for Building Legal Knowledge Graphs from XML Files

This paper presents our experience on building RDF knowledge graphs for ...

Ademar Crotti Junior, et al. ∙

research

∙ 02/14/2020

Semantic Relatedness and Taxonomic Word Embeddings

This paper connects a series of papers dealing with taxonomic word embed...

Magdalena Kacmajor, et al. ∙

research

∙ 04/23/2020

A Tool for Facilitating OCR Postediting in Historical Documents

Optical character recognition (OCR) for historical documents is a comple...

Alberto Poncelas, et al. ∙

research

∙ 05/01/2020

Facilitating Access to Multilingual COVID-19 Information via Neural Machine Translation

Every day, more people are becoming infected and dying from exposure to ...

Andy Way, et al. ∙

research

∙ 05/01/2020

Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation

Machine translation (MT) has benefited from using synthetic training dat...

Xabier Soto, et al. ∙

research

∙ 05/06/2020

Shape of synth to come: Why we should use synthetic data for English surface realization

The Surface Realization Shared Tasks of 2018 and 2019 were Natural Langu...

Henry Elder, et al. ∙

research

∙ 05/02/2020

Treebank Embedding Vectors for Out-of-domain Dependency Parsing

A recent advance in monolingual dependency parsing is the idea of a tree...

Joachim Wagner, et al. ∙

research

∙ 05/14/2020

Towards Socially Responsible AI: Cognitive Bias-Aware Multi-Objective Learning

Human society had a long history of suffering from cognitive biases lead...

Procheta Sen, et al. ∙

research

∙ 06/04/2020

Response to LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts

Live video commenting systems are an emerging feature of online video si...

Hao Wu, et al. ∙

research

∙ 07/06/2020

Finally a Case for Collaborative VR?: The Need to Design for Remote Multi-Party Conversations

Amid current social distancing measures requiring people to work from ho...

Anna Bleakley, et al. ∙

research

∙ 07/27/2021

gaBERT – an Irish Language Model

The BERT family of neural language models have become highly popular due...

James Barry, et al. ∙

research

∙ 08/03/2021

Impact of Load Demand Dataset Characteristics on Clustering Validation Indices

With the inclusion of smart meters, electricity load consumption data ca...

Mayank Jain, et al. ∙

research

∙ 09/02/2021

Quantifying Reproducibility in NLP and ML

Reproducibility has become an intensely debated topic in NLP and ML over...

Anya Belz, et al. ∙

research

∙ 09/10/2021

Enhancing Self-Disclosure In Neural Dialog Models By Candidate Re-ranking

Neural language modelling has progressed the state-of-the-art in differe...

Mayank Soni, et al. ∙

research

∙ 10/19/2021

Identifying Stroke Indicators Using Rough Sets

Stroke is widely considered as the second most common cause of mortality...

Muhammad Salman Pathan, et al. ∙

research

∙ 11/04/2021

Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods

Despite the widespread use of Knowledge Graph Embeddings (KGE), little i...

Peru Bhardwaj, et al. ∙

research

∙ 11/11/2021

Poisoning Knowledge Graph Embeddings via Relation Inference Patterns

We study the problem of generating data poisoning attacks against Knowle...

Peru Bhardwaj, et al. ∙

research

∙ 11/16/2021

PROVENANCE: An Intermediary-Free Solution for Digital Content Verification

The threat posed by misinformation and disinformation is one of the defi...

Bilal Yousuf, et al. ∙

research

∙ 03/01/2022

A predictive analytics approach for stroke prediction using machine learning and neural networks

The negative impact of stroke in society has led to concerted efforts to...

Soumyabrata Dev, et al. ∙

research

∙ 04/12/2022

Quantified Reproducibility Assessment of NLP Results

This paper describes and tests a method for carrying out quantified repr...

Anya Belz, et al. ∙

research

∙ 04/13/2022

DMCNet: Diversified Model Combination Network for Understanding Engagement from Video Screengrabs

Engagement is an essential indicator of the Quality-of-Learning Experien...

Sarthak Batra, et al. ∙

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