fix caml stuff and add things to last sec

materialandmethods.typ

@@ -392,7 +392,7 @@ If the pre-trained model lacks relevant information for the task, SgVA-CLIP migh
 This might be a no-go for anomaly detection tasks because the images in such tasks are often very task-specific and not covered by general pre-trained models.
 Also, fine-tuning the model can require considerable computational resources, which might be a limitation in some cases.~#cite(<peng2023sgvaclipsemanticguidedvisualadapting>)
 
-=== TRIDENT (Transductive Decoupled Variational Inference for Few-Shot Classification)
+=== TRIDENT (Transductive Decoupled Variational Inference for Few-Shot Classification) <TRIDENT>
 // https://arxiv.org/pdf/2208.10559v1
 // https://arxiv.org/abs/2208.10559v1
 
@@ -406,7 +406,7 @@ This feature extractor dynamically aligns features from both the support and the
 This model is specifically designed for few-shot classification tasks but might also work well for anomaly detection.
 Its ability to isolate critical features while droping irellevant context aligns with requirements needed for anomaly detection.
 
-=== SOT (Self-Optimal-Transport Feature Transform)
+=== SOT (Self-Optimal-Transport Feature Transform) <SOT>
 // https://arxiv.org/pdf/2204.03065v1
 // https://arxiv.org/abs/2204.03065v1