2 papers
cs.CL2024
Exploring Language Model Generalization in Low-Resource Extractive QA
Saptarshi Sengupta, Wenpeng Yin, Preslav Nakov +2
In this paper, we investigate Extractive Question Answering (EQA) with Large Language Models (LLMs) under domain drift, i.e., can LLMs generalize to domains that require specific k…
cs.CL2024
TOP-Training: Target-Oriented Pretraining for Medical Extractive Question Answering
Saptarshi Sengupta, Connor Heaton, Shreya Ghosh +3
We study extractive question-answering in the medical domain (Medical-EQA). This problem has two main challenges: (i) domain specificity, as most AI models lack necessary domain kn…