| Autor: |
Leonhardt, Jurek, Müller, Henrik, Rudra, Koustav, Khosla, Megha, Anand, Abhijit, Anand, Avishek |
| Zdroj: |
ACM Transactions on Information Systems; Sep2024, Vol. 42 Issue 5, p1-34, 34p |
| Abstrakt: |
The article focuses on addressing the inefficiency of dual-encoder-based dense retrieval models in information retrieval (IR) by proposing Fast-Forward indexes, which leverage semantic matching capabilities for efficient re-ranking. By enhancing computational efficiency and optimizing memory footprint, Fast-Forward indexes achieve low latency and competitive results in IR tasks without requiring hardware acceleration like GPUs. |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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