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Paper Citation Record · LEDGER

Privacy-Enhancing Paradigms within Federated Multi-Agent Systems

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.08175.

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

pith.paper-citation-record.v1
2503.08175 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:16:14.934008Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T15:26:34.303273Z

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 5f0234a9-d862-4db9-b19f-35bec049ef70 · inbound

Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration cites this paper.

Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration Privacy-Enhancing Paradigms within Federated Multi-Agent Systems

Reference 139

Resolution
unresolved
no resolver link, observed 2026-08-06T21:16:14.934008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:16:14.934008Z digest=sha256:398b06fd077439595325f25d71a06b9f57992871888b680b8b5f049ab03231e1

Observation b315ab5e-22c1-4176-a29c-c26c7c85a619 · inbound

Secure Multi-LLM Agentic AI and Agentification for Edge General Intelligence by Zero-Trust: A Survey cites this paper.

Secure Multi-LLM Agentic AI and Agentification for Edge General Intelligence by Zero-Trust: A Survey Privacy-Enhancing Paradigms within Federated Multi-Agent Systems

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:26:34.306682Z

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=pdf_text observed=2026-08-05T15:26:33.467897Z digest=sha256:a6111c550a3d7c9ad3e1433369d4ddf6aea0798458328159641e4580d2b48a5b