222 citations · 227 across the 3 of their papers we have counts for
4 papers
Fusion of Domain-Adapted Vision and Language Models for Medical Visual Question Answering
Cuong Nhat Ha, Shima Asaadi, Sanjeev Kumar Karn +3
Vision-language models, while effective in general domains and showing strong performance in diverse multi-modal applications like visual question-answering (VQA), struggle to main…
shs-nlp at RadSum23: Domain-Adaptive Pre-training of Instruction-tuned LLMs for Radiology Report Impression Generation
Sanjeev Kumar Karn, Rikhiya Ghosh, Kusuma P +1
Instruction-tuned generative Large language models (LLMs) like ChatGPT and Bloomz possess excellent generalization abilities, but they face limitations in understanding radiology r…
RadLing: Towards Efficient Radiology Report Understanding
Rikhiya Ghosh, Sanjeev Kumar Karn, Manuela Daniela Danu +3
Most natural language tasks in the radiology domain use language models pre-trained on biomedical corpus. There are few pretrained language models trained specifically for radiolog…
Neural Paraphrase Generation with Stacked Residual LSTM Networks
Aaditya Prakash, Sadid A. Hasan, Kathy Lee +4
In this paper, we propose a novel neural approach for paraphrase generation. Conventional para- phrase generation methods either leverage hand-written rules and thesauri-based alig…