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At 1400x cheaper, I know I'm sticking to embeddings (dense, sparse, multi-vector), plus hybrid (incl. bm25) and rerankers. Perhaps I'd even …
At 1400x cheaper, I know I'm sticking to embeddings (dense, sparse, multi-vector), plus hybrid (incl. bm25) and rerankers. Perhaps I'd even use listwise cross-encoders, they seem interesting. can LLMs
At 1400x cheaper, I know I'm sticking to embeddings (dense, sparse, multi-vector), plus hybrid (incl. bm25) and rerankers. Perhaps I'd even use listwise cross-encoders, they seem interesting. can LLMs replace embedding models? in a new work "embedder's dilemma" we find LLMs now beat embedding models -- but at much higher cost. when to choose which?... 📜 https://arxiv.org/abs/2608.12875
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Source: Jeremy Howard (X) | 2026-08-21