RoDE: Linear Rectified Mixture of Diverse Experts for Food Large Multi-Modal Models.
Pengkun Jiao|Xinlan Wu|Bin Zhu|Jingjing Chen|Chong-Wah Ngo|Yu-Gang Jiang
| Anthology ID: | DBLP:conf/mir/JiaoWZCNJ26 |
|---|---|
| Volume: | Proceedings of the 2026 International Conference on Multimedia Retrieval, ICMR 2026, Amsterdam, The Netherlands, June 16-19, 2026 |
| Year: | 2026 |
| Venue: | International Conference on Multimedia Retrieval (ICMR) |
| Publisher: | ACM |
| Pages: | 2457-2466 |
| URL: | https://doi.org/10.1145/3805622.3810616 |
| DOI: | https://doi.org/10.1145/3805622.3810616 |
| DBLP: | conf/mir/JiaoWZCNJ26 |
| BibTeX: |
@inproceedings{jiao-2026-rode,
author = {Pengkun Jiao and
Xinlan Wu and
Bin Zhu and
Jingjing Chen and
Chong-Wah Ngo and
Yu-Gang Jiang},
editor = {Stevan Rudinac and
Zi Huang and
Marcel Worring and
Lucia Vadicamo and
Xirong Li and
Pascal Mettes and
Lizi Liao},
title = {{RoDE: Linear Rectified Mixture of Diverse Experts for Food Large Multi-Modal Models}},
booktitle = {{Proceedings of the 2026 International Conference on Multimedia Retrieval, ICMR 2026, Amsterdam, The Netherlands, June 16-19, 2026}},
pages = {2457--2466},
publisher = {ACM},
year = {2026},
url = {https://doi.org/10.1145/3805622.3810616},
doi = {https://doi.org/10.1145/3805622.3810616}
}