9 citations · 11 across the 6 of their papers we have counts for
6 papers
Spurious Correlations and Beyond: Understanding and Mitigating Shortcut Learning in SDOH Extraction with Large Language Models
Fardin Ahsan Sakib, Ziwei Zhu, Karen Trister Grace +2
Social determinants of health (SDOH) extraction from clinical text is critical for downstream healthcare analytics. Although large language models (LLMs) have shown promise, they m…
MASON-NLP at eRisk 2023: Deep Learning-Based Detection of Depression Symptoms from Social Media Texts
Fardin Ahsan Sakib, Ahnaf Atef Choudhury, Ozlem Uzuner
Depression is a mental health disorder that has a profound impact on people's lives. Recent research suggests that signs of depression can be detected in the way individuals commun…
Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti
Fardin Ahsan Sakib, A H M Rezaul Karim, Saadat Hasan Khan +1
As voice assistants cement their place in our technologically advanced society, there remains a need to cater to the diverse linguistic landscape, including colloquial forms of low…
To token or not to token: A Comparative Study of Text Representations for Cross-Lingual Transfer
Md Mushfiqur Rahman, Fardin Ahsan Sakib, Fahim Faisal +1
Choosing an appropriate tokenization scheme is often a bottleneck in low-resource cross-lingual transfer. To understand the downstream implications of text representation choices,…
Extending the Frontier of ChatGPT: Code Generation and Debugging
Fardin Ahsan Sakib, Saadat Hasan Khan, A. H. M. Rezaul Karim
Large-scale language models (LLMs) have emerged as a groundbreaking innovation in the realm of question-answering and conversational agents. These models, leveraging different deep…
Predicting User-specific Future Activities using LSTM-based Multi-label Classification
Mohammad Sabik Irbaz, Fardin Ahsan Sakib, Lutfun Nahar Lota
User-specific future activity prediction in the healthcare domain based on previous activities can drastically improve the services provided by the nurses. It is challenging becaus…