How D2LLM and Codefuse‑CGE Are Redefining Search with Large Language Models
The article analyzes D2LLM’s teacher‑student bi‑encoder architecture and Codefuse‑CGE’s PMA‑enhanced code embedding, showing how both models surpass BERT dual encoders and LLM cross‑encoders in accuracy, efficiency, and storage cost across semantic and code search benchmarks.
