Open-World Multimodal Understanding and Generation with Efficiently Finetuned Foundation Models
Abstract
With the astonishing ability of different pretrained foundation models (e.g., large language models (LLMs), vision-language models, diffusion models), today’s AI research and development tendency has been revolutionized. In this talk, I will answer two questions: Q1: How can we efficiently train or fine-tune foundation models? Q2: How can we build strong open-world multimodal understanding and generation models with these pretrained foundation models?
Cite
Text
Chen. "Open-World Multimodal Understanding and Generation with Efficiently Finetuned Foundation Models." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I27.35101Markdown
[Chen. "Open-World Multimodal Understanding and Generation with Efficiently Finetuned Foundation Models." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/chen2025aaai-open/) doi:10.1609/AAAI.V39I27.35101BibTeX
@inproceedings{chen2025aaai-open,
title = {{Open-World Multimodal Understanding and Generation with Efficiently Finetuned Foundation Models}},
author = {Chen, Long},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2025},
pages = {28706},
doi = {10.1609/AAAI.V39I27.35101},
url = {https://mlanthology.org/aaai/2025/chen2025aaai-open/}
}