4 papers
KNOW: A Real-World Ontology for Knowledge Capture with Large Language Models
Arto Bendiken
We present KNOW--the Knowledge Navigator Ontology for the World--the first ontology designed to capture everyday knowledge to augment large language models (LLMs) in real-world gen…
Prompt-Time Ontology-Driven Symbolic Knowledge Capture with Large Language Models
Tolga Çöplü, Arto Bendiken, Andrii Skomorokhov +2
In applications such as personal assistants, large language models (LLMs) must consider the user's personal information and preferences. However, LLMs lack the inherent ability to…
Prompt-Time Symbolic Knowledge Capture with Large Language Models
Tolga Çöplü, Arto Bendiken, Andrii Skomorokhov +3
Augmenting large language models (LLMs) with user-specific knowledge is crucial for real-world applications, such as personal AI assistants. However, LLMs inherently lack mechanism…
A Performance Evaluation of a Quantized Large Language Model on Various Smartphones
Tolga Çöplü, Marc Loedi, Arto Bendiken +3
This paper explores the feasibility and performance of on-device large language model (LLM) inference on various Apple iPhone models. Amidst the rapid evolution of generative AI, o…