pith:DOC2W33D
From Tokens to Concepts: Leveraging SAE for SPLADE
Replacing the token vocabulary in SPLADE with semantic concepts from Sparse Auto-Encoders yields comparable retrieval performance with improved efficiency.
arxiv:2604.21511 v2 · 2026-04-23 · cs.IR · cs.CL
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Claims
Our experiments demonstrate that SAE-SPLADE achieves retrieval performance comparable to SPLADE on both in-domain and out-of-domain tasks while offering improved efficiency.
That the SAE-learned latent concepts form a drop-in replacement for the original token vocabulary without losing retrieval-critical information and that the two training regimes remain compatible.
SAE-SPLADE substitutes SPLADE's backbone vocabulary with SAE-derived semantic concepts and matches standard SPLADE performance with better efficiency on in- and out-of-domain tasks.
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| First computed | 2026-06-02T02:04:17.954944Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/DOC2W33DYIXD2HMVKQ2JH6URI4 \
| jq -c '.canonical_record' \
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Canonical record JSON
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