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Paper Citation Record · LEDGER

Towards an AI/ML-driven SMO Framework in O-RAN: Scenarios, Solutions, and Challenges

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2409.05092.

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

pith.paper-citation-record.v1
2409.05092 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:28:13.325770Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a48079ef-896c-49d3-9204-06c367f1232a · inbound

SANNet: A Semantic-Aware Agentic AI Networking Framework for Multi-Agent Cross-Layer Coordination cites this paper.

SANNet: A Semantic-Aware Agentic AI Networking Framework for Multi-Agent Cross-Layer Coordination Towards an AI/ML-driven SMO Framework in O-RAN: Scenarios, Solutions, and Challenges

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T14:28:13.325770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:28:13.325770Z digest=sha256:8e70ead9504151175716c0510ac55541473115b03b18420237bd09e965a97f20

Observation 426fc02c-03c7-4324-acd4-fe947f25e588 · inbound

MaLV-OS: Rethinking the Operating System Architecture for Machine Learning in Virtualized Clouds cites this paper.

MaLV-OS: Rethinking the Operating System Architecture for Machine Learning in Virtualized Clouds Towards an AI/ML-driven SMO Framework in O-RAN: Scenarios, Solutions, and Challenges

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T04:17:29.885170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:17:29.885170Z digest=sha256:6edf989f878672a9d6a4f5f7fe442000da242b58339f8dcc0674668d16f75478

Observation c60f97ad-082e-448e-acad-3199cb23d88c · inbound

SED Fitting of Globular Clusters in NGC 4874: Masses and Metallicities cites this paper.

SED Fitting of Globular Clusters in NGC 4874: Masses and Metallicities Towards an AI/ML-driven SMO Framework in O-RAN: Scenarios, Solutions, and Challenges

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T04:15:06.015982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:15:06.015982Z digest=sha256:9d28e0d472ebb9db34c9a91b6651f727ec876a948be7dd5b56d12d505231fc1a

Observation 9210f192-3e89-4b77-b30e-12c04cb93251 · inbound

ACCoRD: Actor-Critic Conflict Resolution with Deep learning for O-RAN xApps cites this paper.

ACCoRD: Actor-Critic Conflict Resolution with Deep learning for O-RAN xApps Towards an AI/ML-driven SMO Framework in O-RAN: Scenarios, Solutions, and Challenges

Reference 110

Resolution
verified exact
arxiv_id, observed 2026-05-22T02:20:55.873701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-22T02:16:37.897274Z digest=sha256:9cf8828a38a263b6c9530ffefdce72a58282031dda4d8eb908df2120bb8bc4bf