Multimodal Personalization is a personalization approach that integrates and adapts to individual user characteristics by dynamically coordinating multiple modes of interaction—such as visual, auditory, textual, and behavioral modalities—within a unified design framework.
29
Publications
1K
Citations
118
Authors
39
Institutions
Publications per year
2017–2026
17
Parents
Publications
29
DreamBooth3D: Subject-Driven Text-to-3D Generation
Amit Raj, Srinivas Kaza, Ben Poole et al. · 2023 · 145 citations
MMRec: Simplifying Multimodal Recommendation
VIP5: Towards Multimodal Foundation Models for Recommendation
Shijie Geng, Juntao Tan, Shuchang Liu et al. · 2023 · 44 citations · Full text
1–5 of 29
Authors
118
- HC
2
h-index
- DJ
2
h-index
- PO
2
h-index
- KM
1
h-index
- NR
1
h-index
1–5 of 118
Institutions
39
Chinese University of Hong Kong
Hong Kong, Hong Kong
2 h-index
2 publications
36 citations
Newcastle University
Newcastle upon Tyne, United Kingdom
2 h-index
8 publications
123 citations
California Institute of Technology
Pasadena, United States
1 h-index
10 publications
1.9K citations
Google (United States)
Mountain View, United States
1 h-index
12 publications
1.7K citations
Rutgers, The State University of New Jersey
New Brunswick, United States
1 h-index
5 publications
220 citations
Nokia (Finland)
Espoo, Finland
1 h-index
3 publications
30 citations
Baidu (China)
Beijing, China
1 h-index
1 publications
25 citations
Laboratoire d'Informatique en Images et Systèmes d'Information
Villeurbanne, France
1 h-index
4 publications
48 citations
1–8 of 39
Venues
- Social Science Computer Review
SSCR · 1 publications · 21 citations
1
h-index
- New Media & Society
1 publications · 34 citations
1
h-index
- Science Advances
1 publications · 195 citations
1
h-index
- Information Sciences
1 publications · 25 citations
1
h-index
- ACM Transactions on Multimedia Computing Communications and Applications
TOMCCAP · 1 publications · 11 citations
1
h-index
1–5