Pith Number

pith:M7LQKF3N

pith:2026:M7LQKF3NPAOBGIVK7FBGNA3JSQ

not attested not anchored not stored refs pending

Preserving Foundational Capabilities in Flow-Matching VLAs through Conservative SFT

Fuxian Huang, Haoran Zhang, Qi Zhang, Shaopeng Zhai, Tianyi Zhang

ConSFT preserves pre-trained capabilities in flow-matching VLAs by scaling learning signals to model confidence during fine-tuning.

arxiv:2605.08879 v2 · 2026-05-09 · cs.RO

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\usepackage{pith}
\pithnumber{M7LQKF3NPAOBGIVK7FBGNA3JSQ}

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Record completeness

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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

The method outperforms vanilla SFT in capability retention by an average absolute margin of over 20%, matching the efficacy of data-heavy Experience Replay in a prior-data-free regime.

C2weakest assumption

That dynamically scaling learning signals based on model confidence effectively bounds intrinsic parameter disruption risk and secures both target convergence and prior capability retention without introducing new failure modes or limiting necessary adaptation.

C3one line summary

ConSFT prevents catastrophic forgetting in fine-tuning flow-matching VLAs by dynamically scaling gradients based on model confidence, retaining over 20% more pre-trained capability than standard SFT without prior data or reference networks.

Receipt and verification

First computed	2026-05-20T01:05:16.180327Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

67d705176d781c1322aaf942668369942bd007edb13abc41477feb2956d4361c

Aliases

arxiv: 2605.08879 · arxiv_version: 2605.08879v2 · doi: 10.48550/arxiv.2605.08879 · pith_short_12: M7LQKF3NPAOB · pith_short_16: M7LQKF3NPAOBGIVK · pith_short_8: M7LQKF3N

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/M7LQKF3NPAOBGIVK7FBGNA3JSQ \
  | 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: 67d705176d781c1322aaf942668369942bd007edb13abc41477feb2956d4361c

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "c69278ea19f1bb98ffe8f9e7c40c0ec650dbcd746b7299449bd7e919e49c780e",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-09T10:59:03Z",
    "title_canon_sha256": "c53e7388114353dc17753acb434f7799b4563abced5c0edd7c6d3f6742166908"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.08879",
    "kind": "arxiv",
    "version": 2
  }
}