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Paper Citation Record · LEDGER

Towards Foundation-model-based Multiagent System to Accelerate AI for Social Impact

As of 1 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.07880.

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

pith.paper-citation-record.v1
2412.07880 v2

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 2026-08-01T06:32:01.292127+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-03T14:58:02.786187Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T14:58:32.310891Z

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 cf678149-fbf1-44e4-8295-945efb934462 · inbound

Whose Good, Whose Place? The Moral Geography of Agentic AI for Social Good cites this paper.

Whose Good, Whose Place? The Moral Geography of Agentic AI for Social Good Towards Foundation-model-based Multiagent System to Accelerate AI for Social Impact

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:20:25.211621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

source=arxiv_source observed=2026-05-25T05:16:45.248284Z digest=sha256:ea2dc22898569b64fea6d2cf206c44d6c54765d99e92038a40f5f4999e02d1e4

Observation 9d4038e9-7029-498e-8181-a8793dbd327e · inbound

Safe and Adaptive Cloud Healing: Verifying LLM-Generated Recovery Plans with a Neural-Symbolic World Model cites this paper.

Safe and Adaptive Cloud Healing: Verifying LLM-Generated Recovery Plans with a Neural-Symbolic World Model Towards Foundation-model-based Multiagent System to Accelerate AI for Social Impact

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-07-03T14:58:32.312953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

source=pdf_text observed=2026-07-03T14:58:02.786187Z digest=sha256:fa592dec190521d7975c972538541b285119038d0ffc5ae77b29b591d32eb61e