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Paper Citation Record · LEDGER

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning

As of 10 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2506.20916.

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

pith.paper-citation-record.v1
2506.20916 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:43:46.090270Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy10
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9c80103e-90f4-47a6-9624-87db88854dd5 · outbound

This paper cites Continuous control with deep reinforcement learning.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning Continuous control with deep reinforcement learning

Reference 1

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no resolver link, observed 2026-08-06T22:43:46.018969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6d6decf6-217d-43b5-8722-5f399efde803 · outbound

This paper cites Mastering the game of go without human knowledge,.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning Mastering the game of go without human knowledge,

Reference 2

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Observation cc09d7b3-be51-4fb7-901f-2b8781b037d8 · outbound

This paper cites Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,

Reference 3

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Observation ca914356-fbe8-4a50-8408-9267a0ba8249 · outbound

This paper cites Human-level control through deep reinforcement learning,.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning Human-level control through deep reinforcement learning,

Reference 4

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Observation 93580e8b-1109-481e-ad71-4ef7772328bb · outbound

This paper cites Deep reinforcement learning control for radar detection and tracking in congested spectral environments,.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning Deep reinforcement learning control for radar detection and tracking in congested spectral environments,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-06T22:43:46.303864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 2a3121c7-fe37-4cac-a004-399474ffdb6d · outbound

This paper cites Scene-adaptive radar tracking with deep reinforcement learning,.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning Scene-adaptive radar tracking with deep reinforcement learning,

Reference 6

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raw_fallback, observed 2026-08-06T22:43:46.289267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 3f57dd2c-5a1c-4921-b0ea-8f454a7b5f01 · outbound

This paper cites Quality of service based radar resource management using deep reinforcement learning,.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning Quality of service based radar resource management using deep reinforcement learning,

Reference 7

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raw_fallback, observed 2026-08-06T22:43:46.274383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:43:46.049010Z digest=sha256:b818afb72afcbb991a6dd29dfcf51da056b9ec416b511fdccf32144ab46d3746

Observation 98ae1892-087e-4236-8f0c-a2c41b8d63d6 · outbound

This paper cites Time budget management in multifunction radars using reinforcement learning,.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning Time budget management in multifunction radars using reinforcement learning,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation defd670c-5392-4a5e-941c-671871ba21be · outbound

This paper cites Resource allocation for multi-target radar tracking via constrained deep reinforcement learning,.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning Resource allocation for multi-target radar tracking via constrained deep reinforcement learning,

Reference 9

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raw_fallback, observed 2026-08-06T22:43:46.246095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:43:46.057844Z digest=sha256:c4e278d1fbd3ab8076a895b14d0a72e0c4b07edc96e6be141a1a3095e1271b08

Observation a8ba763c-38b6-4a91-a1bb-58aa3cf16a93 · outbound

This paper cites Learning- based cognitive radar resource management for scanning and multi- target tracking,.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning Learning- based cognitive radar resource management for scanning and multi- target tracking,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ab0cd2ca-d719-41c8-a971-6f5cf242c275 · outbound

This paper cites Explainable artificial intelligence (xai): Concepts, taxonomies, opportu- nities and challenges toward responsible ai,.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning Explainable artificial intelligence (xai): Concepts, taxonomies, opportu- nities and challenges toward responsible ai,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation dfc8ed55-a619-4c74-927e-a8c7a5e2b2c8 · outbound

This paper cites Explainable machine learning in deployment,.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning Explainable machine learning in deployment,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 31ad1bff-b136-4634-815d-e9c2bb0a8f06 · outbound

This paper cites ” why should i trust you?.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning ” why should i trust you?

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 15599c2f-01d3-4370-b400-f5267bd6e20f · outbound

This paper cites A Unified Approach to Interpreting Model Predictions.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning A Unified Approach to Interpreting Model Predictions

Reference 14

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Observation 9ed5935f-35a4-4af1-88fe-f24e4f4377c0 · outbound

This paper cites Christoph, Interpretable machine learning: A guide for making black box models explainable.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning Christoph, Interpretable machine learning: A guide for making black box models explainable

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 4afe1379-a75d-4cec-85e8-42d8e2226bd5 · outbound

This paper cites A Modified Perturbed Sampling Method for Local Interpretable Model-agnostic Explanation.

Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning A Modified Perturbed Sampling Method for Local Interpretable Model-agnostic Explanation

Reference 16

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Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.