Model that scores a query and a passage together in one forward pass.
这两项技术尚未记录可对比的属性。
由上述差异按固定规则生成，不是模型生成的。
Choose Cross-Encoder if…
已记录的属性中，没有任何一项显示它更有优势。
Choose Bi-Encoder if…
已记录的属性中，没有任何一项显示它更有优势。
页面保持可访问，但在积累足够的带来源细节之前不纳入搜索索引（PRD SEO-08）。
concept · Techniques
A cross-encoder concatenates the query and one candidate passage and runs them through the model together, producing a relevance score for that pair. It solves the problem that independent embeddings cannot represent how a specific query relates to a specific passage. It exists as the accurate but expensive half of retrieval: accurate enough to reorder a shortlist, too slow to search a corpus with.
concept · Techniques
A bi-encoder encodes the query and each passage independently into vectors, and relevance is their similarity. It solves the problem that a cross-encoder must run once per candidate, which is impossible against a large collection. It exists as the half of retrieval that can be precomputed and indexed, at the cost of losing the interaction between query and passage.
