activity
20242026
collaborators

6 papers

cs.HC2026

Language as a Material Interface for Creative LLM Interaction

Jon McCormack, Tace McNamara, Chen Wang +1

Although directive prompting is the predominant way to interact with Large Language Models (LLMs), many creative practices rely on language that is open-ended, associative, phonaes…

cs.MM2026

MIDI-LLaMA: An Instruction-Following Multimodal LLM for Symbolic Music Understanding

Meng Yang, Jon McCormack, Maria Teresa Llano +2

Recent advances in multimodal large language models (MLLM) for audio music have demonstrated strong capabilities in music understanding, yet symbolic music, a fundamental represent…

cs.HC2025

Supporting Creative Ownership through Deep Learning-Based Music Variation

Stephen James Krol, Maria Teresa Llano, Jon McCormack

This paper investigates the importance of personal ownership in musical AI design, examining how practising musicians can maintain creative control over the compositional process.…

cs.SD2025

Exploring the Feasibility of LLMs for Automated Music Emotion Annotation

Meng Yang, Jon McCormack, Maria Teresa Llano +1

Current approaches to music emotion annotation remain heavily reliant on manual labelling, a process that imposes significant resource and labour burdens, severely limiting the sca…

cs.HC2025

Do Conversational Interfaces Limit Creativity? Exploring Visual Graph Systems for Creative Writing

Abhinav Sood, Maria Teresa Llano, Jon McCormack

We present a graphical, node-based system through which users can visually chain generative AI models for creative tasks. Research in the area of chaining LLMs has found that while…

cs.HC2024

Design Considerations for Automatic Musical Soundscapes of Visual Art for People with Blindness or Low Vision

Stephen James Krol, Maria Teresa Llano, Matthew Butler +1

Music has been identified as a promising medium to enhance the accessibility and experience of visual art for people who are blind or have low vision (BLV). However, composing musi…