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Paper Citation Record · LEDGER

The Future of AI: Exploring the Potential of Large Concept Models

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2501.05487.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.05487 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-03T06:30:56.289259+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T20:15:46.454806Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T11:01:03.124223Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 708d9536-5477-485b-bf55-668721ef94b7 · inbound

Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning cites this paper.

Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning The Future of AI: Exploring the Potential of Large Concept Models

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:05:48.407449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T20:15:46.454806Z digest=sha256:930556a1ebc77fd6b7b2c1991f2d318fcf4324b312b01e8b9746cdc19cdae36a

Observation 7d418b03-24ac-4801-b380-1a5e67df5d7c · inbound

Comparative Analysis of Large Language Models in Healthcare cites this paper.

Comparative Analysis of Large Language Models in Healthcare The Future of AI: Exploring the Potential of Large Concept Models

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:16:07.894818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T15:33:59.591966Z digest=sha256:e7bc9c0e2d80187144c0a9680bebf88f839265c636639dfc7955a180b498d643

Observation e6b8bf1c-cc30-4faa-9413-18414f4a767c · inbound

AgenticVM: Agentic AI for Adaptive Software Vulnerability Management cites this paper.

AgenticVM: Agentic AI for Adaptive Software Vulnerability Management The Future of AI: Exploring the Potential of Large Concept Models

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:01:03.127519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T15:14:04.838666Z digest=sha256:70b0ab7d282ab17bbdcc58f234f588f05180efdc8bb37f050187b99050c29538