This paper presents the shared task on Multilingual Idiomaticity Detection and Sentence Embedding, which consists of two subtasks: (a) a binary classification task aimed at identifying whether a sentence contains an idiomatic expression, and (b) a task based on semantic text similarity which requires the model to adequately represent potentially idiomatic expressions in context. Each subtask includes different settings regarding the amount of training data. Besides the task description, this paper introduces the datasets in English, Portuguese, and Galician and their annotation procedure, the evaluation metrics, and a summary of the participant systems and their results. The task had close to 100 registered participants organised into twent...
Given the limited size of existing idiom corpora, we aim to enable progress in automatic idiom proce...
One of the most intriguing phenomena in human languages is the creation and use of idiomatic express...
Neural Machine Translation (NMT) has been widely used in recent years with significant improvements ...
We describe the University of Alberta systems for the SemEval-2022 Task 2 on multilingual idiomatici...
Deep neural models, in particular Transformer-based pre-trained language models, require a significa...
This paper describes our system for SemEval-2022 Task 2 Multilingual Idiomaticity Detection and Sent...
Large Language Models have been successful in a wide variety of Natural Language Processing tasks by...
Despite their success in a variety of NLP tasks, pre-trained language models, due to their heavy rel...
Deep neural models, in particular Transformer-based pre-trained language models, require a significa...
We propose a multilingual adversarial training model for determining whether a sentence contains an ...
This paper describes an approach to detect idiomaticity only from the contextualized representation ...
In this thesis, we are concerned with idiomatic expressions and how to handle them within NLP. Idiom...
Accurate assessment of the ability of embedding models to capture idiomaticity may require evaluatio...
This paper describes an experiment to evaluate the impact of idioms on Statis- tical Machine Transla...
An idiom is a multiword expression (MWE) whose meaning is non- compositional, i.e., the meaning of t...
Given the limited size of existing idiom corpora, we aim to enable progress in automatic idiom proce...
One of the most intriguing phenomena in human languages is the creation and use of idiomatic express...
Neural Machine Translation (NMT) has been widely used in recent years with significant improvements ...
We describe the University of Alberta systems for the SemEval-2022 Task 2 on multilingual idiomatici...
Deep neural models, in particular Transformer-based pre-trained language models, require a significa...
This paper describes our system for SemEval-2022 Task 2 Multilingual Idiomaticity Detection and Sent...
Large Language Models have been successful in a wide variety of Natural Language Processing tasks by...
Despite their success in a variety of NLP tasks, pre-trained language models, due to their heavy rel...
Deep neural models, in particular Transformer-based pre-trained language models, require a significa...
We propose a multilingual adversarial training model for determining whether a sentence contains an ...
This paper describes an approach to detect idiomaticity only from the contextualized representation ...
In this thesis, we are concerned with idiomatic expressions and how to handle them within NLP. Idiom...
Accurate assessment of the ability of embedding models to capture idiomaticity may require evaluatio...
This paper describes an experiment to evaluate the impact of idioms on Statis- tical Machine Transla...
An idiom is a multiword expression (MWE) whose meaning is non- compositional, i.e., the meaning of t...
Given the limited size of existing idiom corpora, we aim to enable progress in automatic idiom proce...
One of the most intriguing phenomena in human languages is the creation and use of idiomatic express...
Neural Machine Translation (NMT) has been widely used in recent years with significant improvements ...