Pith Number

pith:ZWOLAJ4C

pith:2026:ZWOLAJ4CZXT4QN3T3BSSIDBGFC

not attested not anchored not stored refs resolved

Rethinking Efficient Graph Coarsening via a Non-Selfishness Principle

Bin Lu, Chenghu Zhou, Kun Zhang, Meng Jin, Shengbo Chen, Xinbing Wang, Xu Bai

A non-selfishness principle enables linear-memory graph coarsening with near-linear runtime.

arxiv:2605.13021 v1 · 2026-05-13 · cs.LG · cs.AI

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\usepackage{pith}
\pithnumber{ZWOLAJ4CZXT4QN3T3BSSIDBGFC}

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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

NOPE achieves linear memory consumption and near-linear computational complexity in the number of nodes; NOPE* reduces O(δ · d) interference evaluation to O(d) based on the local isotropy assumption and yields 1.8-10× speedup while producing coarsened graphs that support comparable or superior learning performance.

C2weakest assumption

The local isotropy assumption invoked to simplify interference evaluation from O(δ · d) to O(d) for high-degree nodes.

C3one line summary

NOPE coarsens graphs via neighborhood interference rather than selfish pairwise matching to reach linear memory and near-linear time, with NOPE* variant delivering 1.8-10x speedups and comparable or better learning results than full graphs or LLM reasoning.

References

15 extracted · 15 resolved · 1 Pith anchors

[1] raph- skeleton: 1% nodes are sufficient to represent billion- scale graph 2024

[2] Graph coarsening via convolution match- ing for scalable graph neural network training 2024

[3] Query preserving graph compression 2012

[4] Taglas: An atlas of text-attributed graph datasets in the era of large graph and language models.arXiv preprint arXiv:2406.14683,

[5] Harnessing explanations: Llm-to-lm interpreter for enhanced text-attributed graph representation learning 2024

Receipt and verification

First computed	2026-05-18T03:09:00.029228Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

cd9cb02782cde7c83773d865240c2628a41ba2f4e5d7dc70f9285801809864b7

Aliases

arxiv: 2605.13021 · arxiv_version: 2605.13021v1 · doi: 10.48550/arxiv.2605.13021 · pith_short_12: ZWOLAJ4CZXT4 · pith_short_16: ZWOLAJ4CZXT4QN3T · pith_short_8: ZWOLAJ4C

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/ZWOLAJ4CZXT4QN3T3BSSIDBGFC \
  | 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: cd9cb02782cde7c83773d865240c2628a41ba2f4e5d7dc70f9285801809864b7

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "fe6a930ed2bc435a18aa90737d8739fa6e5467504bd9399eaf808540f7401410",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-13T05:24:35Z",
    "title_canon_sha256": "b24fa0e421af66cb838fbef494b483a887782c507aea5bbce0855b49a79edb13"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13021",
    "kind": "arxiv",
    "version": 1
  }
}