ARCLIGHT: Automated Clustering and Curriculum Learning Guided by Human Training
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Authors
McCusker, Jamie
Santos, Henrique
Singh, Rishi
Rashid, Sabbir
Sanders, Abraham
Roessling, Grace
Guo, Hongji
Biswas, Bashirul
McGuinness, Deborah L.
Strzalkowski, Tomek
Issue Date
2024-11-11
Type
Language
Keywords
Alternative Title
Abstract
ARCLIGHT is an AI fusion system that leverages Large Language Models, perception learning, knowledge graphs, and human guidance to describe high-level concept instances with lower-level attributes and affordances. By combining structured models and unsupervised exploration, ARCLIGHT discovers attributes and affordances in both known and unknown objects, entities, or activities. This enables automated novelty detection, curation of a symbolic knowledge graph, and a dialogue agent that asks discriminating questions. The system’s perception component utilizes Bayesian models to recognize unknown and novel concepts, flag regions of high epistemic uncertainty, and update the knowledge graph based on user interactions. ARCLIGHT can potentially improve human-machine collaboration and advance artificial intelligence in various fields.
Description
Full Citation
McCusker, J., Santos, H., Singh, R., Rashid, S., Sanders, A., Roessling, G., Guo, H., Biswas, B., McGuinness, D.L., Strzalkowski, T., Ji, Q., Miller, J. 2024. ARCLIGHT: Automated Clustering and Curriculum Learning Guided by Human Training. In 23rd International Semantic Web Conference (ISWC) Special Session on LLMs - Harmonising Generative AI and Semantic Web Technologies: Opportunities, challenges, and benchmarks.
Publisher
23rd International Semantic Web Conference (ISWC) Special Session on LLMs - Harmonising Generative AI and Semantic Web Technologies: Opportunities, challenges, and benchmarks