This makes them overlook the many possible interactions across the input modalities and deems them unsafe for high-risk tasks requiring reliable uncertainty estimation.

Recognizing human actions in videos requires spatial and temporal understanding. Most existing action recognition models lack a balanced spatio-temporal understanding of videos.

Formally, DA-Ada introduces a Domain-Invariant Adapter (DIA) and Domain-Specific Adapter (DSA) to exploit domain-invariant and domain-specific knowledge, respectively, as shown in Figure 1(c).

Pre-trained large text-to-image models synthesize impressive images with an appropriate use of text prompts.

The heads are then concatenated to form the LoRA adapter.