4 citations · 4 across the 4 of their papers we have counts for
4 papers
BLK-Assist: A Methodological Framework for Artist-Led Co-Creation with Generative AI Models
Daniel Grimes, Rachel M. Harrison
This paper presents BLK-Assist, a modular framework for artist-specific fine-tuning of diffusion models using parameter-efficient methods. The system is implemented as a case study…
A Comparison of Large Language Model and Human Performance on Random Number Generation Tasks
Rachel M. Harrison
Random Number Generation Tasks (RNGTs) are used in psychology for examining how humans generate sequences devoid of predictable patterns. By adapting an existing human RNGT for an…
An Empirical Categorization of Prompting Techniques for Large Language Models: A Practitioner's Guide
Oluwole Fagbohun, Rachel M. Harrison, Anton Dereventsov
Due to rapid advancements in the development of Large Language Models (LLMs), programming these models with prompts has recently gained significant attention. However, the sheer nu…
Zero-Shot Recommendations with Pre-Trained Large Language Models for Multimodal Nudging
Rachel M. Harrison, Anton Dereventsov, Anton Bibin
We present a method for zero-shot recommendation of multimodal non-stationary content that leverages recent advancements in the field of generative AI. We propose rendering inputs…