Pith Number

pith:3FNQX4UG

pith:2026:3FNQX4UGHYN2U6UZIODRHBPZTA

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From Schema to Signal: Retrieval-Augmented Modeling for Relational Data Analytics

Beng Chin Ooi, Changshuo Liu, Lingze Zeng, Shaofeng Cai, Yuncheng Wu, Zhongle Xie

RAM improves predictions on relational databases by augmenting schema graphs with semantic signals from tuple attributes via random walks and retrieval.

arxiv:2605.14464 v1 · 2026-05-14 · cs.DB

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\pithnumber{3FNQX4UGHYN2U6UZIODRHBPZTA}

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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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

Extensive experiments on five real-world relational databases demonstrate that RAM consistently outperforms existing baselines in diverse prediction tasks, establishing a state-of-the-art for relational data analytics.

C2weakest assumption

That random-walk documents built from tuple attributes plus off-the-shelf IR relevance scores reliably surface semantically meaningful intra- and inter-table connections without introducing substantial noise or spurious correlations that degrade downstream learning.

C3one line summary

RAM augments relational graph models with attribute-semantic retrieval via random-walk documents and two contrastive augmentations (ATRA, ETRA) to achieve state-of-the-art results on five real-world databases.

References

47 extracted · 47 resolved · 5 Pith anchors

[1] Event Recommendation Engine Challenge 2013

[2] Stack Exchange Data Dump 2014

[3] Avito Context Ad Clicks 2015

[4] AACT Clinical Trials.gove 2016

[5] Sercan Ö Arik and Tomas Pfister. 2021. Tabnet: Attentive interpretable tabular learning. InProceedings of the AAAI conference on artificial intelligence. AAAI Press, Palo Alto, California USA, 6679–66 2021

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-17T23:39:06.743562Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d95b0bf2863e1baa7a9943871385f9980dae89f35b12d258db5ea9c7d025a3f7

Aliases

arxiv: 2605.14464 · arxiv_version: 2605.14464v1 · doi: 10.48550/arxiv.2605.14464 · pith_short_12: 3FNQX4UGHYN2 · pith_short_16: 3FNQX4UGHYN2U6UZ · pith_short_8: 3FNQX4UG

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/3FNQX4UGHYN2U6UZIODRHBPZTA \
  | 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: d95b0bf2863e1baa7a9943871385f9980dae89f35b12d258db5ea9c7d025a3f7

Canonical record JSON

{
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    "abstract_canon_sha256": "53ede7d1db1bfced8ee54bcc07d586269ccfc55593f348327f3de21c9b818515",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.DB",
    "submitted_at": "2026-05-14T06:59:32Z",
    "title_canon_sha256": "e6426a98ed3310a0afb148fe2450671cd93a18088c01049b92d7a2674287c321"
  },
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  "source": {
    "id": "2605.14464",
    "kind": "arxiv",
    "version": 1
  }
}