Robert Ross


2021

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Formulating Automated Responses to Cognitive Distortions for CBT Interactions
Ignacio de Toledo Rodriguez | Giancarlo Salton | Robert Ross
Proceedings of the Fourth International Conference on Natural Language and Speech Processing (ICNLSP 2021)

2020

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Language-Driven Region Pointer Advancement for Controllable Image Captioning
Annika Lindh | Robert Ross | John Kelleher
Proceedings of the 28th International Conference on Computational Linguistics

Controllable Image Captioning is a recent sub-field in the multi-modal task of Image Captioning wherein constraints are placed on which regions in an image should be described in the generated natural language caption. This puts a stronger focus on producing more detailed descriptions, and opens the door for more end-user control over results. A vital component of the Controllable Image Captioning architecture is the mechanism that decides the timing of attending to each region through the advancement of a region pointer. In this paper, we propose a novel method for predicting the timing of region pointer advancement by treating the advancement step as a natural part of the language structure via a NEXT-token, motivated by a strong correlation to the sentence structure in the training data. We find that our timing agrees with the ground-truth timing in the Flickr30k Entities test data with a precision of 86.55% and a recall of 97.92%. Our model implementing this technique improves the state-of-the-art on standard captioning metrics while additionally demonstrating a considerably larger effective vocabulary size.

2019

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Energy-Based Modelling for Dialogue State Tracking
Anh Duong Trinh | Robert Ross | John Kelleher
Proceedings of the First Workshop on NLP for Conversational AI

The uncertainties of language and the complexity of dialogue contexts make accurate dialogue state tracking one of the more challenging aspects of dialogue processing. To improve state tracking quality, we argue that relationships between different aspects of dialogue state must be taken into account as they can often guide a more accurate interpretation process. To this end, we present an energy-based approach to dialogue state tracking as a structured classification task. The novelty of our approach lies in the use of an energy network on top of a deep learning architecture to explore more signal correlations between network variables including input features and output labels. We demonstrate that the energy-based approach improves the performance of a deep learning dialogue state tracker towards state-of-the-art results without the need for many of the other steps required by current state-of-the-art methods.

2017

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Attentive Language Models
Giancarlo Salton | Robert Ross | John Kelleher
Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

In this paper, we extend Recurrent Neural Network Language Models (RNN-LMs) with an attention mechanism. We show that an “attentive” RNN-LM (with 11M parameters) achieves a better perplexity than larger RNN-LMs (with 66M parameters) and achieves performance comparable to an ensemble of 10 similar sized RNN-LMs. We also show that an “attentive” RNN-LM needs less contextual information to achieve similar results to the state-of-the-art on the wikitext2 dataset.

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Idiom Type Identification with Smoothed Lexical Features and a Maximum Margin Classifier
Giancarlo Salton | Robert Ross | John Kelleher
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017

In our work we address limitations in the state-of-the-art in idiom type identification. We investigate different approaches for a lexical fixedness metric, a component of the state-of the-art model. We also show that our Machine Learning based approach to the idiom type identification task achieves an F1-score of 0.85, an improvement of 11 points over the state-of the-art.

2016

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Idiom Token Classification using Sentential Distributed Semantics
Giancarlo Salton | Robert Ross | John Kelleher
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

2014

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Evaluation of a Substitution Method for Idiom Transformation in Statistical Machine Translation
Giancarlo Salton | Robert Ross | John Kelleher
Proceedings of the 10th Workshop on Multiword Expressions (MWE)

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An Empirical Study of the Impact of Idioms on Phrase Based Statistical Machine Translation of English to Brazilian-Portuguese
Giancarlo Salton | Robert Ross | John Kelleher
Proceedings of the 3rd Workshop on Hybrid Approaches to Machine Translation (HyTra)

2013

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Proceedings of the IWCS 2013 Workshop on Computational Models of Spatial Language Interpretation and Generation (CoSLI-3)
John Kelleher | Robert Ross | Simon Dobnik
Proceedings of the IWCS 2013 Workshop on Computational Models of Spatial Language Interpretation and Generation (CoSLI-3)

2012

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Proceedings of the 1st Workshop on Speech and Multimodal Interaction in Assistive Environments
Dimitra Anastasiou | Desislava Zhekova | Cui Jian | Robert Ross
Proceedings of the 1st Workshop on Speech and Multimodal Interaction in Assistive Environments