Pith Number

pith:KOVPAO2N

pith:2026:KOVPAO2N5ERMBHZP4YL5I3L4UI

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Language-Induced Priors for Domain Adaptation

Jiayu Zhou, Qiyuan Chen, Raed Al Kontar

Language-induced priors from textual descriptions let domain adaptation match oracle performance when target data is scarce.

arxiv:2605.14301 v1 · 2026-05-14 · cs.LG · stat.ML

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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

We prove that the estimator roughly matches an oracle cold-start MSE under a correct prior, while remaining asymptotically consistent regardless of the quality of the LIP.

C2weakest assumption

The LLM-derived choice model accurately captures source relevance from textual descriptions; if this mapping is systematically biased, the early-stage guidance in the EM algorithm can degrade performance before data overrides it.

C3one line summary

Language-Induced Priors from LLMs guide source selection in cold-start domain adaptation through an EM algorithm, matching oracle MSE under a correct prior and remaining asymptotically consistent.

References

38 extracted · 38 resolved · 1 Pith anchors

[1] IEEE/CAA Journal of Automatica Sinica , volume= 2022

[2] Asymptotic Statistics , author=. 1998 , publisher= 1998

[3] 2013 International Conference on Machine Learning and Cybernetics , volume= 2013

[4] Advances in neural information processing systems , volume=

[5] Advances in neural information processing systems , volume=

Formal links

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Receipt and verification

First computed	2026-05-17T23:39:10.093765Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

53aaf03b4de922c09f2fe617d46d7ca21a3cfd1b2b80f3c833d8fbf0a1e3d70d

Aliases

arxiv: 2605.14301 · arxiv_version: 2605.14301v1 · doi: 10.48550/arxiv.2605.14301 · pith_short_12: KOVPAO2N5ERM · pith_short_16: KOVPAO2N5ERMBHZP · pith_short_8: KOVPAO2N

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/KOVPAO2N5ERMBHZP4YL5I3L4UI \
  | 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: 53aaf03b4de922c09f2fe617d46d7ca21a3cfd1b2b80f3c833d8fbf0a1e3d70d

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "1d0a48852d500965c63bf9a453e0da1ce8fa32d991ae8bb9c9bc1b91f990597e",
    "cross_cats_sorted": [
      "stat.ML"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-14T03:07:48Z",
    "title_canon_sha256": "b087d1cb81493fc05613a8cd0ecb5922ad5556792eeb179f17772047cb07f282"
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  "schema_version": "1.0",
  "source": {
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    "kind": "arxiv",
    "version": 1
  }
}