• Dense Homolog Retriever (DHR) employs a bi-encoder (ESM1b, first vector as fixed-length vector) architecture and a CLIP-like approach to train on homologous pairs with in-batch negatives
• Retrieve homologs by directly comparing these embeddings using a similarity metric (dot product) and JackHMMER to construct MSAs