Equation 4 · Adapters, Native Pretraining, and Unified Tokens: The Main Multimodal Architectures, Compared

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\theta_{\text{vision}}

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\theta_{\text{vision}}

Symbol theta_vision

thet $a_v$ ision is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.

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subscript

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This is the formal shape of “freeze the backbones”: the gradient update is masked to zero everywhere except the bridge parameters $\theta_{\text{bridge}}$ , so | $\theta_{\text{bridge}}$ | — a few hundred million parameters in BLIP-2’s case, dramatically fewer than either tower — is the entire quantity being optimised, and $\theta_{\text{vision}}$ and $\theta_{\text{LM}}$ contribute a forward pass but never a gradient.

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