1 results about "Explicit model" patented technology

The application provides a kind of test time self-adaptive method and device based on sparse supervision explicit modeling field variable, comprising: first, for the setting that test stage only contains untagged stream data, the exclusive field representation of each sample is explicitly constructed;Then, the dense and continuous multimodal features are extracted using a visual-language pre-training model, and the field parameter of each sample is parameterized as a learnable distribution variable;Then, a momentum-updated sparse field library is designed, which provides structured prior for the field variable through decoupling supervision mechanism;On this basis, the learned explicit field clues are injected into the downstream model, and efficient adaptation can be achieved by using only the basic entropy minimization criterion without relying on complex online optimization strategy;Finally, through the system experiment verification on multiple standard robustness benchmarks, by introducing explicit and structured field representation mechanism, the application reveals that the key of robust adaptation does not come from complex adaptation algorithm.