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Paper Citation Record · LEDGER

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering

As of 19 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2504.21113.

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

pith.paper-citation-record.v1
2504.21113 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:18:52.656749Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

29 of 29 outbound references displayed

  • verified exact2
  • verified fuzzy19
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d61d2cfa-3f7f-4e8b-89f4-a6156543feb5 · outbound

This paper cites Multi-agent Coverage Control: From Discrete Assignments to Continuous Multi-agent Distribution Matching.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Multi-agent Coverage Control: From Discrete Assignments to Continuous Multi-agent Distribution Matching

Reference 1

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verified exact
local_arxiv, observed 2026-08-16T05:18:52.780632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation c6613a04-3e8b-4ff9-86dc-9b6cac301dd2 · outbound

This paper cites an unresolved cited work.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:18:53.946422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 111407e3-15d0-4694-93ed-89e43f3e72fd · outbound

This paper cites Coverage control for mobile sensing networks,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Coverage control for mobile sensing networks,

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-16T05:18:52.133093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:18:52.133093Z digest=sha256:ab0cfa4e515ddcb7d4582866f8011f264bcf295b62cdf65fcd7b99bdb6a90e94

Observation 1cbb808e-ea7f-48d1-81f4-65b9b9bd935a · outbound

This paper cites Statistical coverage control of mobile sensor networks,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Statistical coverage control of mobile sensor networks,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:18:53.924952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.137228Z digest=sha256:7da972c59ae1ed024d4c7268091519af99b996fdfe4c7073790c0041666720e3

Observation ca96a979-5a87-4038-bde7-a8e9583c63b8 · outbound

This paper cites Decentralized, adaptive cover- age control for networked robots,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Decentralized, adaptive cover- age control for networked robots,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:18:53.911445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.140996Z digest=sha256:0fca4bd27ef8ffae07db5826092216dc69a0550c63b73389396f580ab3eb2408

Observation cf8fea66-a367-4b43-a54e-e97544cffc54 · outbound

This paper cites A coverage algorithm for a class of non-convex regions,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering A coverage algorithm for a class of non-convex regions,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:18:53.865270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.144945Z digest=sha256:bdf83ff2b049ed1e4af0fd884b78e37ef32c8814e7db0589da5e0382e3839b45

Observation a3d999bc-b445-451e-a316-33c5d6ea6c79 · outbound

This paper cites Distributed collaborative coverage-control schemes for non-convex domains,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Distributed collaborative coverage-control schemes for non-convex domains,

Reference 7

Resolution
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raw_fallback, observed 2026-08-16T05:18:53.834894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.148965Z digest=sha256:6f895a95825d3cb35057c7ec439a4ffc0e5e1f97dda594f596fdfd7e28e815c4

Observation 7e580475-52c9-4664-b0dc-a2b666dc02e3 · outbound

This paper cites Multi-robot coverage and ex- ploration on riemannian manifolds with boundaries,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Multi-robot coverage and ex- ploration on riemannian manifolds with boundaries,

Reference 8

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raw_fallback, observed 2026-08-16T05:18:53.821749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.152711Z digest=sha256:66a99dd15ecc57f49ad9e5ac6a540f3c5cd70fa391e19af566ebe50f55778c74

Observation add5674f-d7c8-4cfa-a3f7-c8d778f8a697 · outbound

This paper cites V oronoi-based multi-robot autonomous exploration in unknown environments via deep reinforcement learning,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering V oronoi-based multi-robot autonomous exploration in unknown environments via deep reinforcement learning,

Reference 9

Resolution
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raw_fallback, observed 2026-08-16T05:18:53.808091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.156261Z digest=sha256:b86fa0aa76b1c959150277766bf7517420e211b47ff01863d34219cb008b6514

Observation 9854a88a-c91a-4f0a-94da-0ac6b11243dc · outbound

This paper cites Distributed multirobot coverage control of nonconvex environments with guarantees,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Distributed multirobot coverage control of nonconvex environments with guarantees,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:18:53.793856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 38c240e2-f841-4354-b8aa-a29e1e5a476a · outbound

This paper cites Adaptive centroidal voronoi tessellation with agent dropout and reinsertion for multi-agent non-convex area coverage,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Adaptive centroidal voronoi tessellation with agent dropout and reinsertion for multi-agent non-convex area coverage,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:18:53.780199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.163430Z digest=sha256:d18b6de566040b5ecab5e9078ea7badefd86df91acf2d8a367e907c8d544d2f1

Observation dca3349e-98bd-4d61-84f7-3f5597ac8a3d · outbound

This paper cites Approximating k-median via pseudo- approximation,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Approximating k-median via pseudo- approximation,

Reference 12

Resolution
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raw_fallback, observed 2026-08-16T05:18:53.764521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.166487Z digest=sha256:bbbf9a0bb5f14df83526b58191884ee937badd6e7ef26391f37bea6478cf1080

Observation 0b45827e-2b4a-490b-ad21-8765f3b395a6 · outbound

This paper cites Re- silient coverage: Exploring the local-to-global trade-off,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Re- silient coverage: Exploring the local-to-global trade-off,

Reference 13

Resolution
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raw_fallback, observed 2026-08-16T05:18:53.749880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.171195Z digest=sha256:3d7fb3a650523e69c00f54e051a5a20251703db19f7f1ff3344db11d1e8b3c71

Observation 023c82e1-25ad-4ea6-921c-da57fb9e38e2 · outbound

This paper cites Exploiting submodularity to quantify near-optimality in multi-agent coverage problems,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Exploiting submodularity to quantify near-optimality in multi-agent coverage problems,

Reference 14

Resolution
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no resolver link, observed 2026-08-16T05:18:52.254911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:18:52.254911Z digest=sha256:0fbc5abc67315b6dcc37fc51816d3c8c07ab1a62edbafed03b53a25ee596dd08

Observation ed937bad-73d0-4b73-9bf9-8fbccfc2b192 · outbound

This paper cites Near-optimal sensor placements in Gaussian processes: Theory, efficient algorithms and empirical stud- ies,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Near-optimal sensor placements in Gaussian processes: Theory, efficient algorithms and empirical stud- ies,

Reference 15

Resolution
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raw_fallback, observed 2026-08-16T05:18:53.730289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.353583Z digest=sha256:94fc4c377495318c5b7a6a81368168bf8431815a9abbeac09aeae42b4c68ceab

Observation 8155be26-c468-4905-9c64-b22068a139b0 · outbound

This paper cites Submodular Maximization Subject to Uniform and Partition Matroids: From Theory to Practical Applications and Distributed Solutions.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Submodular Maximization Subject to Uniform and Partition Matroids: From Theory to Practical Applications and Distributed Solutions

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-16T05:18:52.436982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:18:52.436982Z digest=sha256:7c87e0b406537b4a63ee46db1fcacb38fa7a1a237f818a1abab64befa90301be

Observation 44f84e2b-8098-4723-b07c-3c612b41c743 · outbound

This paper cites Submodular optimization for coupled task allocation and intermittent deployment problems,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Submodular optimization for coupled task allocation and intermittent deployment problems,

Reference 17

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raw_fallback, observed 2026-08-16T05:18:53.716500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.504612Z digest=sha256:81ec000f2dbca912a2a7ac5159a603548415ca9b0d8d959b8fa6d4c38706efba

Observation 7ed7d076-6b31-429d-be41-dc317b246859 · outbound

This paper cites Resource-aware distributed submodular max- imization: A paradigm for multi-robot decision-making,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Resource-aware distributed submodular max- imization: A paradigm for multi-robot decision-making,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:18:53.662961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.608012Z digest=sha256:bc7ef22a69dd072c2b46721d25ef526757d505cf349889dd31ced032067d088c

Observation 49025ace-9957-4649-8095-c8baf91621d0 · outbound

This paper cites Distributed strategy selection: A sub- modular set function maximization approach,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Distributed strategy selection: A sub- modular set function maximization approach,

Reference 19

Resolution
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no resolver link, observed 2026-08-16T05:18:52.611881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:18:52.611881Z digest=sha256:f12f055322f913945364941be3a047eedb1e91d579adcfd693898f98c1d6c742

Observation 070e734c-1152-478f-a419-d8452f43f24d · outbound

This paper cites Inverse submodular maximization with application to human-in-the-loop multi-robot multi-objective coverage control,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Inverse submodular maximization with application to human-in-the-loop multi-robot multi-objective coverage control,

Reference 20

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verified exact
raw_fallback, observed 2026-08-16T05:18:52.750608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.616296Z digest=sha256:2bfb5f29e6f717d077eacb4d70b52b44efcf8d834b377983f210c92c28db3c25

Observation 6bf20d1c-898a-442f-a25f-00103e39c43d · outbound

This paper cites Kaufman and P.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Kaufman and P

Reference 21

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raw_fallback, observed 2026-08-16T05:18:53.409069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.621843Z digest=sha256:683300606635dddaaedbeefa6370869bff40d49eaef9696a1b06b477ec9ee80a

Observation 1617adf0-80d1-4fa4-a78a-62808a193308 · outbound

This paper cites Streaming submodular maximization: Massive data summarization on the fly,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Streaming submodular maximization: Massive data summarization on the fly,

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-16T05:18:53.308107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.626407Z digest=sha256:301887566d6c9c65e5ebac9dcb80337a0c305e31d57f92ae0888a0cafc521135

Observation 2c4c446a-de67-462e-9068-85659984f58f · outbound

This paper cites De Berg, Computational geometry: algorithms and applications.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering De Berg, Computational geometry: algorithms and applications

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-16T05:18:52.630258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:18:52.630258Z digest=sha256:352d3a00a6104390b61fe7accfc244efd6a0b623d8c0f86ec79e8bffab498c35

Observation 99ed447b-5d08-4fe1-9b04-636a64b6a3e7 · outbound

This paper cites Informed rrt*: Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Informed rrt*: Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:18:53.288993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.633806Z digest=sha256:d4599d4912d87b823d2c231a02dbb39c478281656b31a9bfab2bd8737b4a9592

Observation 241365d8-e3c8-421e-84c5-9909268d608a · outbound

This paper cites An algorithm for planning collision- free paths among polyhedral obstacles,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering An algorithm for planning collision- free paths among polyhedral obstacles,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:18:53.276580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.638198Z digest=sha256:eb853f5cedd05a35b07381b87e8cedca2912a3ba0b57988cf0349cd9eafafb84

Observation 028e6cfd-595d-4791-a631-cc922fa6ce68 · outbound

This paper cites an unresolved cited work.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:18:53.263928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.643178Z digest=sha256:32eb06febda6455b96cdb6e1912e4ad3c7321be50d6aca91acf92fef7354e3da

Observation abeaddb4-641f-423f-ab11-996080193580 · outbound

This paper cites Sampling-based algorithms for optimal motion planning,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Sampling-based algorithms for optimal motion planning,

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-16T05:18:52.648139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:18:52.648139Z digest=sha256:004a00249b9b2a2148f9927fed203b160f981065914df4dc42cd1768b0010873

Observation 66307038-2273-45c7-8798-477ccb072ffb · outbound

This paper cites Gaussian process-based traversability analysis for terrain mapless navigation,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Gaussian process-based traversability analysis for terrain mapless navigation,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:18:53.117480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.652656Z digest=sha256:d3f641a7931bf4dc8f52565a7f3e503588a554e0f57c835b23881ba56d7ca71b

Observation dda26044-a420-44af-8bbc-15cd514ffab5 · outbound

This paper cites Budgeted nonparametric learning from data streams,.

NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering Budgeted nonparametric learning from data streams,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:18:52.830487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:18:52.656749Z digest=sha256:58d9ed91f3e7f291c0d283a3af49c8c690e3a0bb130e5adda946c511835de516

Pith citing papers

No inbound Pith citation observations are available.