Dynamic Concept Guidance (DCG), a
framework for web-scale multimodal learning that
dynamically selects and applies concept guidance
through embedding cosine similarity. Unlike cu-
rated dataset approaches, DCG operates on het-
erogeneous web-crawled data, adapting in real-time
to varying modality combinations and quality lev-
els. My method enables robust learning from noisy
web data by providing explicit conceptual objectives.
The framework demonstrates superior adaptability to
real-world data distributions while maintaining inter-
pretability through dynamic concept activation pat-
terns.