Search Results for author:
Found 6 papers, 6 papers with code
Two eyes, Two views, and finally, One summary! Towards Multi-modal Multi-tasking Knowledge-Infused Medical Dialogue Summarization
We often summarize a multi-party conversation in two stages: chunking with homogeneous units and summarizing the chunks.
Towards Knowledge-Infused Automated Disease Diagnosis Assistant
In the next stage, the conversation and knowledge graph embeddings are infused together and fed to a deep neural network for disease identification.
An EcoSage Assistant: Towards Building A Multimodal Plant Care Dialogue Assistant
In recent times, there has been an increasing awareness about imminent environmental challenges, resulting in people showing a stronger dedication to taking care of the environment and nurturing green life.
Yes, this is what I was looking for! Towards Multi-modal Medical Consultation Concern Summary Generation
Over the past few years, the use of the Internet for healthcare-related tasks has grown by leaps and bounds, posing a challenge in effectively managing and processing information to ensure its efficient utilization.
Experience and Evidence are the eyes of an excellent summarizer! Towards Knowledge Infused Multi-modal Clinical Conversation Summarization
We propose a knowledge-infused, multi-modal, multi-tasking medical domain identification and clinical conversation summary generation (MM-CliConSummation) framework.
Hi Model, generating 'nice' instead of 'good' is not as bad as generating 'rice'! Towards Context and Semantic Infused Dialogue Generation Loss Function and Evaluation Metric
We found that the dialogue generation models trained with SemTextualLogueloss attained superior performance compared to the traditional cross-entropy loss function.
