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Paper Citation Record · LEDGER

Safe Multi-Agent Reinforcement Learning through Decentralized Multiple Control Barrier Functions

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2103.12553.

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

pith.paper-citation-record.v1
2103.12553 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 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T05:56:54.996304Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T05:59:40.956989Z

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 34d66364-9b05-48ce-a457-7590bdd0120d · inbound

A Review On Safe Reinforcement Learning Using Lyapunov and Barrier Functions cites this paper.

A Review On Safe Reinforcement Learning Using Lyapunov and Barrier Functions Safe Multi-Agent Reinforcement Learning through Decentralized Multiple Control Barrier Functions

Reference 98

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:41:53.795429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-18T22:37:32.388931Z digest=sha256:25979df737712877b6909aa1f0662964ede424e94d57c5f0cfc13ccc15e3935a

Observation 180f265f-488c-4e2f-90e3-7dee3fbc36ad · inbound

Distributed Direct Preference Optimization cites this paper.

Distributed Direct Preference Optimization Safe Multi-Agent Reinforcement Learning through Decentralized Multiple Control Barrier Functions

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:59:40.959144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-21T05:56:54.996304Z digest=sha256:f8746faea55aab6e216c7912178ff29f339bab5830608ea7ff4c852185b6723c