565 citations · 834 across the 31 of their papers we have counts for
7 papers · 2 filters
A Multimodal Framework for the Detection of Hateful Memes
Phillip Lippe, Nithin Holla, Shantanu Chandra +4
An increasingly common expression of online hate speech is multimodal in nature and comes in the form of memes. Designing systems to automatically detect hateful content is of para…
Cross-neutralising: Probing for joint encoding of linguistic information in multilingual models
Rochelle Choenni, Ekaterina Shutova
Multilingual sentence encoders are widely used to transfer NLP models across languages. The success of this transfer is, however, dependent on the model's ability to encode the pat…
What does it mean to be language-agnostic? Probing multilingual sentence encoders for typological properties
Rochelle Choenni, Ekaterina Shutova
Multilingual sentence encoders have seen much success in cross-lingual model transfer for downstream NLP tasks. Yet, we know relatively little about the properties of individual la…
Meta-Learning with Sparse Experience Replay for Lifelong Language Learning
Nithin Holla, Pushkar Mishra, Helen Yannakoudakis +1
Lifelong learning requires models that can continuously learn from sequential streams of data without suffering catastrophic forgetting due to shifts in data distributions. Deep le…
Graph-based Modeling of Online Communities for Fake News Detection
Shantanu Chandra, Pushkar Mishra, Helen Yannakoudakis +3
Over the past few years, there has been a substantial effort towards automated detection of fake news on social media platforms. Existing research has modeled the structure, style,…
Joint Modelling of Emotion and Abusive Language Detection
Santhosh Rajamanickam, Pushkar Mishra, Helen Yannakoudakis +1
The rise of online communication platforms has been accompanied by some undesirable effects, such as the proliferation of aggressive and abusive behaviour online. Aiming to tackle…
Learning to Learn to Disambiguate: Meta-Learning for Few-Shot Word Sense Disambiguation
Nithin Holla, Pushkar Mishra, Helen Yannakoudakis +1
The success of deep learning methods hinges on the availability of large training datasets annotated for the task of interest. In contrast to human intelligence, these methods lack…