14 citations · 27 across the 4 of their papers we have counts for
5 papers
Named Clinical Entity Recognition Benchmark
Wadood M Abdul, Marco AF Pimentel, Muhammad Umar Salman +6
This technical report introduces a Named Clinical Entity Recognition Benchmark for evaluating language models in healthcare, addressing the crucial natural language processing (NLP…
MEDIC: Comprehensive Evaluation of Leading Indicators for LLM Safety and Utility in Clinical Applications
Praveenkumar Kanithi, Clément Christophe, Marco AF Pimentel +8
While Large Language Models (LLMs) achieve superhuman performance on standardized medical licensing exams, these static benchmarks have become saturated and increasingly disconnect…
Med42 -- Evaluating Fine-Tuning Strategies for Medical LLMs: Full-Parameter vs. Parameter-Efficient Approaches
Clément Christophe, Praveen K Kanithi, Prateek Munjal +13
This study presents a comprehensive analysis and comparison of two predominant fine-tuning methodologies - full-parameter fine-tuning and parameter-efficient tuning - within the co…
Synthesizing the Unseen for Zero-shot Object Detection
Nasir Hayat, Munawar Hayat, Shafin Rahman +3
The existing zero-shot detection approaches project visual features to the semantic domain for seen objects, hoping to map unseen objects to their corresponding semantics during in…
Towards Robust and Reproducible Active Learning Using Neural Networks
Prateek Munjal, Nasir Hayat, Munawar Hayat +2
Active learning (AL) is a promising ML paradigm that has the potential to parse through large unlabeled data and help reduce annotation cost in domains where labeling data can be p…