Pith Number

pith:FHVLPDNC

pith:2026:FHVLPDNCIN33SLNV6TTWR6Z3NI

not attested not anchored not stored refs resolved

Position: Agentic AI System Is a Foreseeable Pathway to AGI

Jun Wang, Junwei Liao, Muning Wen, Shuai Li, Weinan Zhang

Agentic AI systems using DAG topologies achieve exponentially superior generalization and sample efficiency compared to monolithic models.

arxiv:2605.12966 v1 · 2026-05-13 · cs.AI

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{FHVLPDNCIN33SLNV6TTWR6Z3NI}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

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

We demonstrate that Agentic AI achieves exponentially superior generalization and sample efficiency.

C2weakest assumption

The optimization constraints of monolithic learners are fundamentally more limiting than those of agentic DAG systems, without specified independent benchmarks or derivations in the abstract.

C3one line summary

Agentic AI systems with DAG topologies are claimed to deliver exponentially superior generalization and sample efficiency compared to monolithic scaling for achieving AGI.

References

90 extracted · 90 resolved · 2 Pith anchors

[1] Langley , title = 2000

[2] T. M. Mitchell. The Need for Biases in Learning Generalizations. 1980 1980

[3] M. J. Kearns , title =

[4] Machine Learning: An Artificial Intelligence Approach, Vol. I. 1983 1983

[5] R. O. Duda and P. E. Hart and D. G. Stork. Pattern Classification. 2000 2000

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-18T03:09:09.060835Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

29eab78da24377b92db5f4e768fb3b6a13eafcc4e4dc4aadaac31b542a6c86bd

Aliases

arxiv: 2605.12966 · arxiv_version: 2605.12966v1 · doi: 10.48550/arxiv.2605.12966 · pith_short_12: FHVLPDNCIN33 · pith_short_16: FHVLPDNCIN33SLNV · pith_short_8: FHVLPDNC

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/FHVLPDNCIN33SLNV6TTWR6Z3NI \
  | 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: 29eab78da24377b92db5f4e768fb3b6a13eafcc4e4dc4aadaac31b542a6c86bd

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "79a4fb9cb9a6408db3443dc5c08d682f783f75f810f25b657e39efb819d476da",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2026-05-13T04:00:43Z",
    "title_canon_sha256": "51797ea718d72263ede974335a3602d2a4fab62839eb1fdb07eef5d17c84fa07"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.12966",
    "kind": "arxiv",
    "version": 1
  }
}