82 citations · 244 across the 19 of their papers we have counts for
21 papers
Lon-ea at SemEval-2023 Task 11: A Comparison of Activation Functions for Soft and Hard Label Prediction
Peyman Hosseini, Mehran Hosseini, Sana Sabah Al-Azzawi +3
We study the influence of different activation functions in the output layer of deep neural network models for soft and hard label prediction in the learning with disagreement task…
CoRAL: a Context-aware Croatian Abusive Language Dataset
Ravi Shekhar, Mladen Karan, Matthew Purver
In light of unprecedented increases in the popularity of the internet and social media, comment moderation has never been a more relevant task. Semi-automated comment moderation sy…
Misspelling Semantics In Thai
Pakawat Nakwijit, Matthew Purver
User-generated content is full of misspellings. Rather than being just random noise, we hypothesise that many misspellings contain hidden semantics that can be leveraged for langua…
Measuring and Improving Compositional Generalization in Text-to-SQL via Component Alignment
Yujian Gan, Xinyun Chen, Qiuping Huang +1
In text-to-SQL tasks -- as in much of NLP -- compositional generalization is a major challenge: neural networks struggle with compositional generalization where training and test d…
Not All Comments are Equal: Insights into Comment Moderation from a Topic-Aware Model
Elaine Zosa, Ravi Shekhar, Mladen Karan +1
Moderation of reader comments is a significant problem for online news platforms. Here, we experiment with models for automatic moderation, using a dataset of comments from a popul…
Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalization
Yujian Gan, Xinyun Chen, Matthew Purver
Recently, there has been significant progress in studying neural networks for translating text descriptions into SQL queries under the zero-shot cross-domain setting. Despite achie…
Natural SQL: Making SQL Easier to Infer from Natural Language Specifications
Yujian Gan, Xinyun Chen, Jinxia Xie +4
Addressing the mismatch between natural language descriptions and the corresponding SQL queries is a key challenge for text-to-SQL translation. To bridge this gap, we propose an SQ…
A Longitudinal Multi-modal Dataset for Dementia Monitoring and Diagnosis
Dimitris Gkoumas, Bo Wang, Adam Tsakalidis +4
Dementia affects cognitive functions of adults, including memory, language, and behaviour. Standard diagnostic biomarkers such as MRI are costly, whilst neuropsychological tests su…
Evaluation of contextual embeddings on less-resourced languages
Matej Ulčar, Aleš Žagar, Carlos S. Armendariz +4
The current dominance of deep neural networks in natural language processing is based on contextual embeddings such as ELMo, BERT, and BERT derivatives. Most existing work focuses…
Towards Robustness of Text-to-SQL Models against Synonym Substitution
Yujian Gan, Xinyun Chen, Qiuping Huang +4
Recently, there has been significant progress in studying neural networks to translate text descriptions into SQL queries. Despite achieving good performance on some public benchma…
Multi-modal fusion with gating using audio, lexical and disfluency features for Alzheimer's Dementia recognition from spontaneous speech
Morteza Rohanian, Julian Hough, Matthew Purver
This paper is a submission to the Alzheimer's Dementia Recognition through Spontaneous Speech (ADReSS) challenge, which aims to develop methods that can assist in the automated pre…
Temporal Mental Health Dynamics on Social Media
Tom Tabak, Matthew Purver
We describe a set of experiments for building a temporal mental health dynamics system. We utilise a pre-existing methodology for distant-supervision of mental health data mining f…
How Furiously Can Colourless Green Ideas Sleep? Sentence Acceptability in Context
Jey Han Lau, Carlos S. Armendariz, Shalom Lappin +2
We study the influence of context on sentence acceptability. First we compare the acceptability ratings of sentences judged in isolation, with a relevant context, and with an irrel…
CoSimLex: A Resource for Evaluating Graded Word Similarity in Context
Carlos Santos Armendariz, Matthew Purver, Matej Ulčar +5
State of the art natural language processing tools are built on context-dependent word embeddings, but no direct method for evaluating these representations currently exists. Stand…
Exploring Semantic Incrementality with Dynamic Syntax and Vector Space Semantics
Mehrnoosh Sadrzadeh, Matthew Purver, Julian Hough +1
One of the fundamental requirements for models of semantic processing in dialogue is incrementality: a model must reflect how people interpret and generate language at least on a w…
Variability, polarimetry, and timing properties of single pulses from PSR J1713+0747 using the Large European Array for Pulsars
K. Liu, C. G. Bassa, G. H. Janssen +11
Single pulses preserve information about the pulsar radio emission and propagation in the pulsar magnetosphere, and understanding the behaviour of their variability is essential fo…
Words, Concepts, and the Geometry of Analogy
Stephen McGregor, Matthew Purver, Geraint Wiggins
This paper presents a geometric approach to the problem of modelling the relationship between words and concepts, focusing in particular on analogical phenomena in language and cog…
Single pulse and profile variability study of PSR J1022+1001
K. Liu, R. Karuppusamy, K. J. Lee +6
Millisecond pulsars (MSPs) are known as highly stable celestial clocks. Nevertheless, recent studies have revealed the unstable nature of their integrated pulse profiles, which may…
Strongly Incremental Repair Detection
Julian Hough, Matthew Purver
We present STIR (STrongly Incremental Repair detection), a system that detects speech repairs and edit terms on transcripts incrementally with minimal latency. STIR uses informatio…
Evaluating Neural Word Representations in Tensor-Based Compositional Settings
Dmitrijs Milajevs, Dimitri Kartsaklis, Mehrnoosh Sadrzadeh +1
We provide a comparative study between neural word representations and traditional vector spaces based on co-occurrence counts, in a number of compositional tasks. We use three dif…
Topic and Sentiment Analysis on OSNs: a Case Study of Advertising Strategies on Twitter
Shana Dacres, Hamed Haddadi, Matthew Purver
Social media have substantially altered the way brands and businesses advertise: Online Social Networks provide brands with more versatile and dynamic channels for advertisement th…