no code implementations • 16 Apr 2024 • Ubaid Azam, Imran Razzak, Shelly Vishwakarma, Hakim Hacid, Dell Zhang, Shoaib Jameel
The growing capabilities of AI raise questions about their trustworthiness in healthcare, particularly due to opaque decision-making and limited data availability.
no code implementations • 16 Apr 2024 • Ubaid Azam, Imran Razzak, Shelly Vishwakarma, Hakim Hacid, Dell Zhang, Shoaib Jameel
Predicting legal judgments with reliable confidence is paramount for responsible legal AI applications.
no code implementations • 8 Jan 2024 • Abdullah Alsuhaibani, Hamad Zogan, Imran Razzak, Shoaib Jameel, Guandong Xu
Although some approaches have attempted to address this problem through single-stage clustering as an intermediate training step coupled with a pre-trained language model, which generates pseudo-labels to improve classification, these methods are often error-prone due to the limitations of the clustering algorithms.
no code implementations • 11 Jan 2023 • Mozhgan Talebpour, Alba Garcia Seco de Herrera, Shoaib Jameel
Contextualised word vectors obtained via pre-trained language models encode a variety of knowledge that has already been exploited in applications.
no code implementations • 14 Jan 2022 • Sujit Roy, Gnaneswara Rao Gorle, Vishal Gaur, Haider Raza, Shoaib Jameel
As a result, there has been a steep rise in developing computational methods to predict a user engagement score that is indicative of some form of possible user engagement, i. e., to what level a user would tend to engage with the content.
no code implementations • 2 Dec 2021 • Kun Yan, Chenbin Zhang, Jun Hou, Ping Wang, Zied Bouraoui, Shoaib Jameel, Steven Schockaert
A key feature of the multi-label setting is that images often have multiple labels, which typically refer to different regions of the image.
1 code implementation • UK Workshop on Computational Intelligence 2021 • Elena Barry, Shoaib Jameel, Haider Raza
For example, the use of the clown emoji Open image in a new window to signify someone is making a fool of themself, or the collective spamming of the snake emoji Open image in a new window to “cancel” someone, both show seemingly innocent emojis being used as clear forms of aggression online.
Cultural Vocal Bursts Intensity Prediction Sentiment Analysis
no code implementations • 23 May 2021 • Hamad Zogan, Imran Razzak, Shoaib Jameel, Guandong Xu
Twitter is currently a popular online social media platform which allows users to share their user-generated content.
no code implementations • 21 May 2021 • Kun Yan, Zied Bouraoui, Ping Wang, Shoaib Jameel, Steven Schockaert
While the use of class names has already been explored in previous work, our approach differs in two key aspects.
no code implementations • 1 Feb 2021 • Kun Yan, Zied Bouraoui, Ping Wang, Shoaib Jameel, Steven Schockaert
The aim of few-shot learning (FSL) is to learn how to recognize image categories from a small number of training examples.
no code implementations • COLING 2020 • Zihao Fu, Lidong Bing, Wai Lam, Shoaib Jameel
Recently, many KB-to-text generation tasks have been proposed to bridge the gap between knowledge bases and natural language by directly converting a group of knowledge base triples into human-readable sentences.
no code implementations • 3 Jul 2020 • Hamad Zogan, Imran Razzak, Xianzhi Wang, Shoaib Jameel, Guandong Xu
Model interpretability has become important to engenders appropriate user trust by providing the insight into the model prediction.
no code implementations • ACL 2019 • Shoaib Jameel, Steven Schockaert
To this end, our model relies on the assumption that context word vectors are drawn from a mixture of von Mises-Fisher (vMF) distributions, where the parameters of this mixture distribution are jointly optimized with the word vectors.
no code implementations • COLING 2018 • Zied Bouraoui, Shoaib Jameel, Steven Schockaert
Given a set of instances of some relation, the relation induction task is to predict which other word pairs are likely to be related in the same way.
no code implementations • ACL 2018 • Shoaib Jameel, Zied Bouraoui, Steven Schockaert
Word embedding models such as GloVe rely on co-occurrence statistics to learn vector representations of word meaning.
no code implementations • 14 Nov 2017 • Shoaib Jameel, Zied Bouraoui, Steven Schockaert
Word embedding models such as GloVe rely on co-occurrence statistics from a large corpus to learn vector representations of word meaning.
no code implementations • 21 Aug 2017 • Zied Bouraoui, Shoaib Jameel, Steven Schockaert
Word embeddings have been found to capture a surprisingly rich amount of syntactic and semantic knowledge.
no code implementations • CONLL 2017 • Shoaib Jameel, Steven Schockaert
Although region representations of word meaning offer a natural alternative to word vectors, only few methods have been proposed that can effectively learn word regions.
no code implementations • 21 Jun 2017 • Bei Shi, Wai Lam, Shoaib Jameel, Steven Schockaert, Kwun Ping Lai
Word embedding models such as Skip-gram learn a vector-space representation for each word, based on the local word collocation patterns that are observed in a text corpus.
no code implementations • COLING 2016 • Shoaib Jameel, Steven Schockaert
We propose a new word embedding model, inspired by GloVe, which is formulated as a feasible least squares optimization problem.
no code implementations • 18 Feb 2016 • Shoaib Jameel, Steven Schockaert
Conceptual spaces are geometric representations of conceptual knowledge, in which entities correspond to points, natural properties correspond to convex regions, and the dimensions of the space correspond to salient features.