Paper Citation Record · LEDGER

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS

As of 14 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2607.05957.

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

pith.paper-citation-record.v1
2607.05957 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-08T20:23:09.706524Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

18 of 18 outbound references displayed

verified exact2
verified fuzzy16
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 07c481c7-f993-4d3a-9568-f79b5ebfe5b7 · outbound

This paper cites Multi-robot system for autonomous cooperative counter-uas missions: Design, integration, and field testing,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Multi-robot system for autonomous cooperative counter-uas missions: Design, integration, and field testing,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.422112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 588f8f93-d186-4f97-92fd-2b428c5a7e5f · outbound

This paper cites A review of counter-uas technologies for cooperative defensive teams of drones,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS A review of counter-uas technologies for cooperative defensive teams of drones,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.406923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b190241e-7288-4fe9-9c8f-1021ed21c8a8 · outbound

This paper cites Hartley and A.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Hartley and A

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.398667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9d23d4d4-15da-49e4-ae7a-917733c8f3ef · outbound

This paper cites Pampc: Perception- aware model predictive control for quadrotors,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Pampc: Perception- aware model predictive control for quadrotors,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.419859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 46c4ef69-1ea4-4188-b3a3-a063b0761be1 · outbound

This paper cites Multi-agent reinforcement learning based drone guidance for n-view triangulation,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Multi-agent reinforcement learning based drone guidance for n-view triangulation,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.426397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 723004a2-bc9e-4fd3-a126-b18d7887b141 · outbound

This paper cites Rainbow delay compensation: A multi-agent reinforcement learning framework for mitigating observation delays,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Rainbow delay compensation: A multi-agent reinforcement learning framework for mitigating observation delays,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.424019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 138e4cb8-ef35-400a-9cd8-4713636b2303 · outbound

This paper cites Addressing signal delay in deep reinforcement learning,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Addressing signal delay in deep reinforcement learning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.430746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4bfda48d-8756-4bcb-82e4-9905a4f141db · outbound

This paper cites Asymmetric DQN for partially observable reinforcement learning,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Asymmetric DQN for partially observable reinforcement learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.428798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cdfc1afb-5b81-4afd-afd2-d7f573c46dc1 · outbound

This paper cites Swarm-based counter uav defense system,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Swarm-based counter uav defense system,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.414816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 48861734-23a1-4a24-af4c-53b86b534464 · outbound

This paper cites On onboard lidar-based flying object detection,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS On onboard lidar-based flying object detection,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.401261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation aee93390-ed57-4bd1-98a0-5a9304d4e78a · outbound

This paper cites NOVA: Navigation via Object-Centric Visual Autonomy for High-Speed Target Tracking in Unstructured GPS-Denied Environments.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS NOVA: Navigation via Object-Centric Visual Autonomy for High-Speed Target Tracking in Unstructured GPS-Denied Environments

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-07-08T20:25:37.255893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 73bb782e-60c2-4fd3-b942-8bd06a3c4373 · outbound

This paper cites Error modeling in stereo navigation,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Error modeling in stereo navigation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.405067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 700d710a-68ff-4484-877a-36e5926a8145 · outbound

This paper cites Propagation of uncertainty through stereo triangulation,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Propagation of uncertainty through stereo triangulation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.402953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ebb927cc-9a3c-41a7-b87c-7a2217253e9a · outbound

This paper cites Robust Uncertainty-Aware Multiview Triangulation.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Robust Uncertainty-Aware Multiview Triangulation

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-07-08T20:25:37.252994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 28b63e3d-0596-4d24-8538-eba65311e0ad · outbound

This paper cites Deep reinforcement learning for aoi minimization in uav-aided data collection for wsn and iot applications: A survey,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Deep reinforcement learning for aoi minimization in uav-aided data collection for wsn and iot applications: A survey,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.417298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2daa5ae6-c74b-4f50-ad2c-5980eaf86829 · outbound

This paper cites Real-time status: How often should one update?.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Real-time status: How often should one update?

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.410782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 43365685-8c33-4558-9a8c-d40a159bbe4b · outbound

This paper cites Age of correlated information-optimal dynamic policy scheduling for sus- tainable green iot devices: A multi-agent deep reinforcement learning approach,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS Age of correlated information-optimal dynamic policy scheduling for sus- tainable green iot devices: A multi-agent deep reinforcement learning approach,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.412749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a9350c02-e1c6-4331-91d3-7cce86edb94c · outbound

This paper cites The surprising effectiveness of ppo in cooperative, multi- agent games,.

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS The surprising effectiveness of ppo in cooperative, multi- agent games,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.408749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.