Accelerating Inference in Retrieval-Augmented Generation Models for Long-Form Question Answering via Dynamic Token Pruning
Fusion-in-Decoder (FiD), a prominent retrieval-augmented generation model, has demonstrated outstanding performance in open-domain question answering by effectively leveraging multiple passages. However, processing multiple passages significantly increases computational costs at both encoder and dec...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
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| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/13/14/2231 |
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