42 citations · 43 across the 9 of their papers we have counts for
9 papers
Contextualized Prompting For Stance Detection On Social Media
Tilman Beck, Shakib Yazdani, Simon Kruschinski +2
Stance detection on social media is challenging due to short, noisy, and context-dependent language. While large language models (LLMs) show zero-shot generalization, they are typi…
A Critical Study of Automatic Evaluation in Sign Language Translation
Shakib Yazdani, Yasser Hamidullah, Cristina España-Bonet +2
Automatic evaluation metrics are crucial for advancing sign language translation (SLT). Current SLT evaluation metrics, such as BLEU and ROUGE, are only text-based, and it remains…
Seeing, Signing, and Saying: A Vision-Language Model-Assisted Pipeline for Sign Language Data Acquisition and Curation from Social Media
Shakib Yazdani, Yasser Hamidullah, Cristina España-Bonet +1
Most existing sign language translation (SLT) datasets are limited in scale, lack multilingual coverage, and are costly to curate due to their reliance on expert annotation and con…
SONAR-SLT: Multilingual Sign Language Translation via Language-Agnostic Sentence Embedding Supervision
Yasser Hamidullah, Shakib Yazdani, Cennet Oguz +2
Sign language translation (SLT) is typically trained with text in a single spoken language, which limits scalability and cross-language generalization. Earlier approaches have repl…
Grounding or Guessing? Visual Signals for Detecting Hallucinations in Sign Language Translation
Yasser Hamidullah, Koel Dutta Chowdhury, Yusser Al Ghussin +4
Hallucination, where models generate fluent text unsupported by visual evidence, remains a major flaw in vision-language models and is particularly critical in sign language transl…
Parameter Efficient Continual Learning with Dynamic Low-Rank Adaptation
Prashant Shivaram Bhat, Shakib Yazdani, Elahe Arani +1
Catastrophic forgetting has remained a critical challenge for deep neural networks in Continual Learning (CL) as it undermines consolidated knowledge when learning new tasks. Param…
COVID CT-Net: Predicting Covid-19 From Chest CT Images Using Attentional Convolutional Network
Shakib Yazdani, Shervin Minaee, Rahele Kafieh +2
The novel corona-virus disease (COVID-19) pandemic has caused a major outbreak in more than 200 countries around the world, leading to a severe impact on the health and life of man…
COVID TV-UNet: Segmenting COVID-19 Chest CT Images Using Connectivity Imposed U-Net
Narges Saeedizadeh, Shervin Minaee, Rahele Kafieh +2
The novel corona-virus disease (COVID-19) pandemic has caused a major outbreak in more than 200 countries around the world, leading to a severe impact on the health and life of man…
Deep-COVID: Predicting COVID-19 From Chest X-Ray Images Using Deep Transfer Learning
Shervin Minaee, Rahele Kafieh, Milan Sonka +2
The COVID-19 pandemic is causing a major outbreak in more than 150 countries around the world, having a severe impact on the health and life of many people globally. One of the cru…