A survey on neural-symbolic learning systems
D Yu, B Yang, D Liu, H Wang, S Pan - Neural Networks, 2023 - Elsevier
In recent years, neural systems have demonstrated highly effective learning ability and
superior perception intelligence. However, they have been found to lack effective reasoning …
superior perception intelligence. However, they have been found to lack effective reasoning …
Is neuro-symbolic ai meeting its promises in natural language processing? a structured review
Abstract Advocates for Neuro-Symbolic Artificial Intelligence (NeSy) assert that combining
deep learning with symbolic reasoning will lead to stronger AI than either paradigm on its …
deep learning with symbolic reasoning will lead to stronger AI than either paradigm on its …
Zero-shot Classification using Hyperdimensional Computing
Classification based on Zero-shot Learning (ZSL) is the ability of a model to classify inputs
into novel classes on which the model has not previously seen any training examples …
into novel classes on which the model has not previously seen any training examples …
[PDF][PDF] Is Neuro-Symbolic AI Meeting its Promise in Natural Language Processing? A Structured
Advocates for Neuro-Symbolic Artificial Intelligence (NeSy) assert that combining deep
learning with symbolic reasoning will lead to stronger AI than either paradigm on its own. As …
learning with symbolic reasoning will lead to stronger AI than either paradigm on its own. As …
Every time I fire a conversational designer, the performance of the dialog system goes down
GA Xompero, M Mastromattei, S Salman… - arXiv preprint arXiv …, 2021 - arxiv.org
Incorporating explicit domain knowledge into neural-based task-oriented dialogue systems
is an effective way to reduce the need of large sets of annotated dialogues. In this paper, we …
is an effective way to reduce the need of large sets of annotated dialogues. In this paper, we …