Paper Citation Record · LEDGER

Engineering LaCAM$^\ast$: Towards Real-Time, Large-Scale, and Near-Optimal Multi-Agent Pathfinding

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2308.04292.

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

pith.paper-citation-record.v1
2308.04292 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:11:46.638292Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T07:56:47.639375Z

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 d71ced45-82c1-4c2a-a6f7-cd49bc46e2f4 · inbound

Multi-Agent Path Finding via Finite-Horizon Hierarchical Factorization cites this paper.

Multi-Agent Path Finding via Finite-Horizon Hierarchical Factorization Engineering LaCAM$^\ast$: Towards Real-Time, Large-Scale, and Near-Optimal Multi-Agent Pathfinding

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T22:11:46.638292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 216f7256-202c-4d89-acd6-02b3e60e034a · inbound

Adaptive-Horizon Conflict-Based Search for Closed-Loop Multi-Agent Path Finding cites this paper.

Adaptive-Horizon Conflict-Based Search for Closed-Loop Multi-Agent Path Finding Engineering LaCAM$^\ast$: Towards Real-Time, Large-Scale, and Near-Optimal Multi-Agent Pathfinding

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T00:03:08.688527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 065887bf-fd60-42ad-9f0c-cc74394b64f6 · inbound

CADENCE: Predicting Realized MAPF Execution Time Beyond Sum of Costs cites this paper.

CADENCE: Predicting Realized MAPF Execution Time Beyond Sum of Costs Engineering LaCAM$^\ast$: Towards Real-Time, Large-Scale, and Near-Optimal Multi-Agent Pathfinding

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:56:47.640846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5fccc8ec-0282-42db-af1f-29163fce26ad · inbound

CADENCE: Predicting Realized MAPF Execution Time Beyond Sum of Costs cites this paper.

CADENCE: Predicting Realized MAPF Execution Time Beyond Sum of Costs Engineering LaCAM$^\ast$: Towards Real-Time, Large-Scale, and Near-Optimal Multi-Agent Pathfinding

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T12:25:17.465435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d724bea3-2b0c-4cab-897a-a0c8864c8cce · inbound

PRIMAL3: Pathfinding via Reinforcement and Imitation Multi-Agent Learning - Leveraging LaCAM3 cites this paper.

PRIMAL3: Pathfinding via Reinforcement and Imitation Multi-Agent Learning - Leveraging LaCAM3 Engineering LaCAM$^\ast$: Towards Real-Time, Large-Scale, and Near-Optimal Multi-Agent Pathfinding

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T13:57:14.159318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4e44e33-172f-4543-adce-06f52626cef7 · inbound

Search-Aided Joint Agent-Environment Reinforcement Learning for Robust Lifelong Multi-Agent Path Finding with Rotations cites this paper.

Search-Aided Joint Agent-Environment Reinforcement Learning for Robust Lifelong Multi-Agent Path Finding with Rotations Engineering LaCAM$^\ast$: Towards Real-Time, Large-Scale, and Near-Optimal Multi-Agent Pathfinding

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-08T06:04:24.525421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.