DART is a cross-modal foundation model that delivers rope damage classification, severity regression, and few-shot recognition from a single frozen representation trained on 4270 images across 14 damage classes.
M3-jepa: Multimodal alignment via multi-gate moe based on the joint-embedding predictive architecture
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2representative citing papers
A literature survey that categorizes how Mixture-of-Experts architectures address multimodal learning challenges and identifies open research gaps.
citing papers explorer
-
DART: A Vision-Language Foundation Model for Comprehensive Rope Condition Monitoring
DART is a cross-modal foundation model that delivers rope damage classification, severity regression, and few-shot recognition from a single frozen representation trained on 4270 images across 14 damage classes.
-
Tackling Multimodal Learning Challenges with Mixture-of-Expert: A Survey
A literature survey that categorizes how Mixture-of-Experts architectures address multimodal learning challenges and identifies open research gaps.