pith:JO2OSSKH
Large Language Model as Token Compressor and Decompressor
An off-the-shelf LLM can be fine-tuned with LoRA to compress long texts into adaptive sequences of Z-tokens while preserving reconstruction and task performance.
arxiv:2603.25340 v2 · 2026-03-26 · cs.CL
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Claims
an off-the-shelf LLM can be adapted into a discrete, variable-length token compressor and decompressor for long-context processing
that fine-tuning with LoRA on the self-expressive autoencoding objective will produce Z-tokens that preserve enough information for both faithful reconstruction and downstream task performance without requiring extensive post-hoc adjustments
A pretrained LLM is adapted via LoRA fine-tuning into a content-adaptive compressor that maps long texts to compact variable-length Z-token sequences while preserving reconstruction quality and downstream performance.
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| First computed | 2026-05-18T03:09:22.531461Z |
|---|---|
| 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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· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JO2OSSKHNSUX3EPGK72F2A7S2B \
| jq -c '.canonical_record' \
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# expect: 4bb4e949476ca97d91e657f45d03f2d06a74156ef7ae405b0b812d0b1b2d5b9c
Canonical record JSON
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