5 papers
No Transformer Beats Six Covariates: Long-Horizon Prediction of Depressive Symptoms from Childhood Essays
Daniel Kua, Emrul Hasan, John-Jose Nunez +1
Natural language processing (NLP) models can detect depression-related language in text written near the time symptoms are measured, but whether pretrained transformers can predict…
Contrastive Learning for Aspect Representation towards Explainable Recommendation
Emrul Hasan, Chen Ding
In this work, we propose a novel recommendation model, CLARER (Contrastive Learning for Aspect Representation towards Explainable Recommendation) that integrates aspect features le…
ViLBias: Detecting and Reasoning about Bias in Multimodal Content
Shaina Raza, Caesar Saleh, Azib Farooq +11
Detecting bias in multimodal news requires models that reason over text--image pairs, not just classify text. In response, we present ViLBias, a VQA-style benchmark and framework f…
Review-based Recommender Systems: A Survey of Approaches, Challenges and Future Perspectives
Emrul Hasan, Mizanur Rahman, Chen Ding +2
Recommender systems play a pivotal role in helping users navigate an overwhelming selection of products and services. On online platforms, users have the opportunity to share feedb…
TMU at TREC Clinical Trials Track 2023
Aritra Kumar Lahiri, Emrul Hasan, Qinmin Vivian Hu +1
This paper describes Toronto Metropolitan University's participation in the TREC Clinical Trials Track for 2023. As part of the tasks, we utilize advanced natural language processi…