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Knowledge graph embedding: A survey from the perspective of representation spaces
Knowledge graph embedding (KGE) is an increasingly popular technique that aims to
represent entities and relations of knowledge graphs into low-dimensional semantic spaces …
represent entities and relations of knowledge graphs into low-dimensional semantic spaces …
Interpretability research of deep learning: A literature survey
B Xua, G Yang - Information Fusion, 2024 - Elsevier
Deep learning (DL) has been widely used in various fields. However, its black-box nature
limits people's understanding and trust in its decision-making process. Therefore, it becomes …
limits people's understanding and trust in its decision-making process. Therefore, it becomes …
[PDF][PDF] Retrieval-augmented generation for large language models: A survey
Y Gao, Y ** multi-goal conversational
recommender systems (MG-CRS) that can proactively attract users' interests and naturally …
recommender systems (MG-CRS) that can proactively attract users' interests and naturally …
All you may need for VQA are image captions
S Changpinyo, D Kukliansky, I Szpektor… - arxiv preprint arxiv …, 2022 - arxiv.org
Visual Question Answering (VQA) has benefited from increasingly sophisticated models, but
has not enjoyed the same level of engagement in terms of data creation. In this paper, we …
has not enjoyed the same level of engagement in terms of data creation. In this paper, we …
Process knowledge-infused ai: Toward user-level explainability, interpretability, and safety
AI has seen wide adoption for automating tasks in several domains. However, AI's use in
high-value, sensitive, or safety-critical applications such as self-management for …
high-value, sensitive, or safety-critical applications such as self-management for …
Building trustworthy NeuroSymbolic AI Systems: Consistency, reliability, explainability, and safety
Explainability and Safety engender trust. These require a model to exhibit consistency and
reliability. To achieve these, it is necessary to use and analyze data and knowledge with …
reliability. To achieve these, it is necessary to use and analyze data and knowledge with …
Proknow: Process knowledge for safety constrained and explainable question generation for mental health diagnostic assistance
Virtual Mental Health Assistants (VMHAs) are utilized in health care to provide patient
services such as counseling and suggestive care. They are not used for patient diagnostic …
services such as counseling and suggestive care. They are not used for patient diagnostic …
A review of the explainability and safety of conversational agents for mental health to identify avenues for improvement
Virtual Mental Health Assistants (VMHAs) continuously evolve to support the overloaded
global healthcare system, which receives approximately 60 million primary care visits and 6 …
global healthcare system, which receives approximately 60 million primary care visits and 6 …