collaborators

5 papers

cs.CL2024

Incremental and Data-Efficient Concept Formation to Support Masked Word Prediction

Xin Lian, Nishant Baglodi, Christopher J. MacLellan

This paper introduces Cobweb4L, a novel approach for efficient language model learning that supports masked word prediction. The approach builds on Cobweb, an incremental system th…

cs.LG2024

Incremental Concept Formation over Visual Images Without Catastrophic Forgetting

Nicki Barari, Xin Lian, Christopher J. MacLellan

Deep neural networks have excelled in machine learning, particularly in vision tasks, however, they often suffer from catastrophic forgetting when learning new tasks sequentially.…

cs.HC2024

Improving Interface Design in Interactive Task Learning for Hierarchical Tasks based on a Qualitative Study

Jieyu Zhou, Christopher MacLellan

Interactive Task Learning (ITL) systems acquire task knowledge from human instructions in natural language interaction. The interaction design of ITL agents for hierarchical tasks…

cs.LG2024

Cobweb: An Incremental and Hierarchical Model of Human-Like Category Learning

Xin Lian, Sashank Varma, Christopher J. MacLellan

Cobweb, a human-like category learning system, differs from most cognitive science models in incrementally constructing hierarchically organized tree-like structures guided by the…

cs.HC2024

VAL: Interactive Task Learning with GPT Dialog Parsing

Lane Lawley, Christopher J. MacLellan

Machine learning often requires millions of examples to produce static, black-box models. In contrast, interactive task learning (ITL) emphasizes incremental knowledge acquisition…