Pith Number

pith:MWMWF35W

pith:2026:MWMWF35W6EB7PUGEM7D64EVO2J

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RAT+: Train Dense, Infer Sparse -- Recurrence Augmented Attention for Dilated Inference

Caglar Gulcehre, Xiuying Wei

RAT+ lets one densely pretrained model switch to dilated sparse attention at inference with only short adaptation.

arxiv:2602.18196 v4 · 2026-02-20 · cs.LG

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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

A single RAT+ model is pretrained densely once and can then be flexibly switched at inference time to dilated attention (optionally with local windows) or hybrid layer/head compositions, requiring only a short 1B-token resolution adaptation rather than retraining separate sparse models.

C2weakest assumption

That adding full-sequence recurrence and active recurrence learning during dense pretraining creates representations that transfer to dilated sparse patterns with only short adaptation and limited accuracy loss.

C3one line summary

RAT+ pretrains a single dense recurrent-augmented attention model that supports flexible dilated sparse inference after short adaptation, matching dense accuracy at moderate dilation and losing only 1-3 points at high dilation.

Receipt and verification

First computed	2026-05-21T01:05:16.476570Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

659962efb6f103f7d0c467c7ee12aed24291f1daa1f6c17cfa39ee8081e6df52

Aliases

arxiv: 2602.18196 · arxiv_version: 2602.18196v4 · doi: 10.48550/arxiv.2602.18196 · pith_short_12: MWMWF35W6EB7 · pith_short_16: MWMWF35W6EB7PUGE · pith_short_8: MWMWF35W

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/MWMWF35W6EB7PUGEM7D64EVO2J \
  | 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: 659962efb6f103f7d0c467c7ee12aed24291f1daa1f6c17cfa39ee8081e6df52

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "0e8deeea39032e68e54efa8dcbc3038a25f3c084329d43f21b6c526445c12029",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-02-20T13:09:49Z",
    "title_canon_sha256": "62e201d3d163f9d7ceb6c2b5c7300780dfead246ea2ecf0c91a821de8f2a5ffb"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2602.18196",
    "kind": "arxiv",
    "version": 4
  }
}