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Pith Number

pith:FBOWBOYJ

pith:2025:FBOWBOYJIVPFO3PDJN4MJ77QSX
not attested not anchored not stored refs pending

Pangu Pro MoE: Mixture of Grouped Experts for Efficient Sparsity

Binfan Zheng, Can Chen, Dacheng Tao, Fangcheng Liu, Fei Mi, Hang Zhou, Hanting Chen, Hui Zang, Jinpeng Li, Kai Han, Peifeng Qin, Ruiming Tang, Wei Guo, Xianzhi Yu, Xiaojun Meng, Xiaosong Li, Xinghao Chen, Yaoyuan Wang, Yehui Tang, Youliang Yan, Yunhe Wang (and Other Contributors), Zhicheng Liu

arxiv:2505.21411 v2 · 2025-05-27 · cs.CL

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?
Add to your LaTeX paper 
\usepackage{pith}
\pithnumber{FBOWBOYJIVPFO3PDJN4MJ77QSX}

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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.

Cited by

8 papers in Pith

Rethinking the Role of Tensor Decompositions in Post-Training LLM Compression
Complete-muE: Optimal Hyperparameter Transfer and Scaling for MoE Models
NASiC: 3D NAND-based CAM-Selected Multibit CIM Architecture for Efficient On-Device Mixture-of-Experts LLM Inference
Intrinsic Fingerprint of LLMs: Continue Training is NOT All You Need to Steal A Model!
Hierarchical Mixture-of-Experts with Two-Stage Optimization
Receipt and verification
First computed 2026-07-05T11:10:59.073690Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

285d60bb09455e576de34b78c4fff095eb6a7f85f914ca3fe4e9c63f78fb83bc

Aliases

arxiv: 2505.21411 · arxiv_version: 2505.21411v2 · doi: 10.48550/arxiv.2505.21411 · pith_short_12: FBOWBOYJIVPF · pith_short_16: FBOWBOYJIVPFO3PD · pith_short_8: FBOWBOYJ
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/FBOWBOYJIVPFO3PDJN4MJ77QSX \
  | 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: 285d60bb09455e576de34b78c4fff095eb6a7f85f914ca3fe4e9c63f78fb83bc
Canonical record JSON 
{
  "metadata": {
    "abstract_canon_sha256": "1bfc9b1b3e7d0dbd8b43785676ab6e3b6adbcd71ede476d0b69fbdfab794eea2",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2025-05-27T16:40:21Z",
    "title_canon_sha256": "0ef3bfbd40623b7f1881271ddbb3c19288462e1894d30dad9da56fe823f66dda"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2505.21411",
    "kind": "arxiv",
    "version": 2
  }
}