ML Anthology

Finetuning LLMs for Automatic Concept to TTI Prompt Generation (Student Abstract)

Jeremy Rutter, Maneesh Reddy Chamakura, Justin Delgado, Gene Louis Kim
AAAI 2024 pp. 23637-23639
doi:10.1609/AAAI.V38I21.30505 /aaai/2024/rutter2024aaai-finetuning/

Abstract

Our work explores bridging the gap between large language models and text-to-image models to create a tool for quickly and easily generating high quality images from a given concept. In our experiments we successfully improved image quality with only a preliminary utilization of the available resources for finetuning.

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Cite

Text

Rutter et al. "Finetuning LLMs for Automatic Concept to TTI Prompt Generation (Student Abstract)." AAAI Conference on Artificial Intelligence, 2024. doi:10.1609/AAAI.V38I21.30505

Markdown

[Rutter et al. "Finetuning LLMs for Automatic Concept to TTI Prompt Generation (Student Abstract)." AAAI Conference on Artificial Intelligence, 2024.](https://mlanthology.org/aaai/2024/rutter2024aaai-finetuning/) doi:10.1609/AAAI.V38I21.30505

BibTeX

@inproceedings{rutter2024aaai-finetuning,
  title     = {{Finetuning LLMs for Automatic Concept to TTI Prompt Generation (Student Abstract)}},
  author    = {Rutter, Jeremy and Chamakura, Maneesh Reddy and Delgado, Justin and Kim, Gene Louis},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2024},
  pages     = {23637-23639},
  doi       = {10.1609/AAAI.V38I21.30505},
  url       = {https://mlanthology.org/aaai/2024/rutter2024aaai-finetuning/}
}