Causalqa: a causal framework for question answering
Neural networks have proven their success in various fundamental applications such as object detection, image segmentation, image and text generation and several NLP tasks. That said, neural networks are black-box function approximators with good approximation capability described by the universal a...
Saved in:
Main Author: | Dutta, Angshuk |
---|---|
Other Authors: | Joty Shafiq Rayhan |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/156616 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
A Question answering system to answer procedural and causal questions in medicine
by: Daella, Paula Angelica, et al.
Published: (2011) -
Towards a hierarchical framework for predicting the best answer in a question answering system
by: Chua, Alton Yeow Kuan, et al.
Published: (2009) -
Debiasing visual question and answering with answer preference
by: Zhang, Xinye
Published: (2020) -
Visual questioning and answering
by: Ong, Zavier Jian Le
Published: (2024) -
Intelligent question and answering system
by: Chan, Krylicia Cai Yan
Published: (2017)