Pith Number

pith:2S6NTSNW

pith:2026:2S6NTSNWQHHKBUUHZG4Z4DTZIH

not attested not anchored not stored refs pending

Learning in the Fisher Subspace: A Guided Initialization for LoRA Fine-Tuning

Hung-Yu Kao, Ying-Jia Lin, Zhi-Quan Feng

Using Fisher curvature from downstream data to initialize LoRA subspaces improves fine-tuning performance over weight-only methods.

arxiv:2605.01046 v3 · 2026-05-01 · cs.LG

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\usepackage{pith}
\pithnumber{2S6NTSNWQHHKBUUHZG4Z4DTZIH}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Empirical results across diverse tasks and modalities demonstrate that data-aware initialization consistently and significantly improves downstream performance over existing approaches.

C2weakest assumption

That the curvature information induced by the downstream data distribution accurately identifies parameter directions whose perturbations most influence model predictions on the target objective.

C3one line summary

Fisher information from target data provides a better criterion than weight geometry for choosing LoRA subspaces, yielding consistent performance gains on downstream tasks.

Receipt and verification

First computed	2026-05-28T00:05:15.211835Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d4bcd9c9b681cea0d287c9b99e0e7941c44117f5d574d3b87a011793317aa04e

Aliases

arxiv: 2605.01046 · arxiv_version: 2605.01046v3 · doi: 10.48550/arxiv.2605.01046 · pith_short_12: 2S6NTSNWQHHK · pith_short_16: 2S6NTSNWQHHKBUUH · pith_short_8: 2S6NTSNW

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/2S6NTSNWQHHKBUUHZG4Z4DTZIH \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: d4bcd9c9b681cea0d287c9b99e0e7941c44117f5d574d3b87a011793317aa04e

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "8f6c5a4e907da9540ed1f1c0d05b1ee17aaa2c86cde169671a699ebe5d5535c9",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-01T19:20:25Z",
    "title_canon_sha256": "8455f47f3b3d9eb693aaa048a1d58d4bca23a47090c0e4f76cd76b736325e538"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.01046",
    "kind": "arxiv",
    "version": 3
  }
}