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Paper Citation Record · LEDGER

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments

As of 8 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2506.21129.

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

pith.paper-citation-record.v1
2506.21129 v2

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:43:22.518129Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:19:43.140620Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:19:43.298055Z

Reference resolution

52 of 52 outbound references displayed

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External citation measurements

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Outbound references

Observation 8fcf9345-d539-45c5-9b3c-d4f0255ff1f6 · outbound

This paper cites Uncovering drone intentions using control physics informed machine learning,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Uncovering drone intentions using control physics informed machine learning,

Reference 1

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Observation 7e6c6e6b-7d32-4bce-bc9b-31319bc7627d · outbound

This paper cites A survey on reinforcement learning in aviation applications,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments A survey on reinforcement learning in aviation applications,

Reference 2

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Observation eee01a92-9d70-470e-a143-add02b2ccf6b · outbound

This paper cites Ads-b vulnerabilities and a security solution with a timestamp,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Ads-b vulnerabilities and a security solution with a timestamp,

Reference 3

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Observation 2111450c-efe6-4632-95f2-02b6cc4f6f19 · outbound

This paper cites Detecting ads-b spoofing attacks using deep neural networks,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Detecting ads-b spoofing attacks using deep neural networks,

Reference 4

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Observation 5fc6cff3-82e7-4e60-b205-3bc3e80e9f28 · outbound

This paper cites Action robust reinforcement learning for air mobility deconfliction against conflict induced spoofing,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Action robust reinforcement learning for air mobility deconfliction against conflict induced spoofing,

Reference 5

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Observation 71844dbe-cc99-4631-95d3-75153d841441 · outbound

This paper cites Challenges and countermeasures for adversarial attacks on deep reinforcement learning,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Challenges and countermeasures for adversarial attacks on deep reinforcement learning,

Reference 6

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Observation d7d2f720-a48c-4a5c-9945-cddcca4d42a6 · outbound

This paper cites Ads-b jamming mitigation: A solution based on a multichannel receiver,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Ads-b jamming mitigation: A solution based on a multichannel receiver,

Reference 7

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Observation 72e083fd-b8aa-4fb3-8276-a77b27c37fec · outbound

This paper cites Distributionally robust model-based offline reinforcement learning with near-optimal sample com- plexity,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Distributionally robust model-based offline reinforcement learning with near-optimal sample com- plexity,

Reference 8

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Observation 5a325c60-78a5-4273-8a1a-74b6ac83c0ec · outbound

This paper cites Action robust rein- forcement learning and applications in continuous control,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Action robust rein- forcement learning and applications in continuous control,

Reference 9

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Observation af7004ab-9bf1-450b-9bdd-5f21476517a5 · outbound

This paper cites Autonomous option in- vention for continual hierarchical reinforcement learning and planning,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Autonomous option in- vention for continual hierarchical reinforcement learning and planning,

Reference 10

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Source-reported events for the cited work

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Observation 37e804bf-e3b3-47f9-9af0-8c91f47df8e5 · outbound

This paper cites Lifelong domain adaptation via consolidated internal distribution,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Lifelong domain adaptation via consolidated internal distribution,

Reference 11

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Observation 02480772-5c22-4426-a55d-df0d669b9c67 · outbound

This paper cites Curriculum reinforcement learning using optimal transport via gradual domain adaptation,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Curriculum reinforcement learning using optimal transport via gradual domain adaptation,

Reference 12

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Observation b9c5c8c6-b9e4-4515-8264-cd0249cc7bf6 · outbound

This paper cites Curriculum reinforcement learning from avoiding collisions to navigating among movable obstacles in diverse environments,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Curriculum reinforcement learning from avoiding collisions to navigating among movable obstacles in diverse environments,

Reference 13

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Observation 776ab13b-8957-4b54-b9e1-6226cb570a97 · outbound

This paper cites A sensor fusion-based gnss spoofing attack detection framework for autonomous vehicles,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments A sensor fusion-based gnss spoofing attack detection framework for autonomous vehicles,

Reference 14

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Observation 1da7a9ab-950b-4414-a3fd-73acdc67760c · outbound

This paper cites Gnss spoofing and detection,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Gnss spoofing and detection,

Reference 15

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Observation 6bfcd492-68a3-4aeb-b1fb-9dae67d6417d · outbound

This paper cites Robust deep reinforcement learning against adversarial perturbations on state observations,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Robust deep reinforcement learning against adversarial perturbations on state observations,

Reference 16

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Observation 263e70bf-c8b2-4b3f-9672-e1618624132c · outbound

This paper cites Distributionally robust reinforcement learning with interactive data collec- tion: Fundamental hardness and near-optimal algorithms,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Distributionally robust reinforcement learning with interactive data collec- tion: Fundamental hardness and near-optimal algorithms,

Reference 17

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Observation 8cf0190a-a9d3-4fbc-a189-eba549eeb9df · outbound

This paper cites Near-optimal distributionally robust reinforce- ment learning with general L_p norms,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Near-optimal distributionally robust reinforce- ment learning with general L_p norms,

Reference 18

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Observation 940fb9ef-7bd2-488a-9734-56f4a17082f1 · outbound

This paper cites On corruption- robustness in performative reinforcement learning,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments On corruption- robustness in performative reinforcement learning,

Reference 19

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Observation c998814c-d655-44f4-827a-86464159e506 · outbound

This paper cites On reinforcement learning and distribution matching for fine-tuning language models with no catastrophic forgetting,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments On reinforcement learning and distribution matching for fine-tuning language models with no catastrophic forgetting,

Reference 20

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Observation f01260ad-e014-4c90-834b-a3fc64f065f6 · outbound

This paper cites Rethinking the Foundations for Continual Reinforcement Learning.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Rethinking the Foundations for Continual Reinforcement Learning

Reference 21

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Observation 865c0329-67d8-40a0-84a7-93c48ea51c58 · outbound

This paper cites Progressive Neural Networks.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Progressive Neural Networks

Reference 22

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Observation 3b13650d-3777-4b4a-942d-3d98b1263ca4 · outbound

This paper cites Towards continual reinforcement learning: A review and perspectives,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Towards continual reinforcement learning: A review and perspectives,

Reference 23

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This paper cites Rostami, Transfer learning through embedding spaces.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Rostami, Transfer learning through embedding spaces

Reference 24

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This paper cites Forget me not: Reducing catastrophic forgetting for domain adaptation in reading comprehension,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Forget me not: Reducing catastrophic forgetting for domain adaptation in reading comprehension,

Reference 25

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This paper cites Self-Composing Policies for Scalable Continual Reinforcement Learning.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Self-Composing Policies for Scalable Continual Reinforcement Learning

Reference 26

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Observation a38846cd-8c2e-4d78-9829-1cf3d7eeba13 · outbound

This paper cites On the benefit of optimal transport for curriculum reinforcement learning,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments On the benefit of optimal transport for curriculum reinforcement learning,

Reference 27

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Observation ff7267d1-dbc6-4abd-b356-74e6db26581a · outbound

This paper cites Unsupervised domain adap- tation by backpropagation,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Unsupervised domain adap- tation by backpropagation,

Reference 28

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Observation a01ea48b-643b-41b8-a1d0-7c231d0eb50d · outbound

This paper cites Generate to adapt: Aligning domains using generative adversarial networks,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Generate to adapt: Aligning domains using generative adversarial networks,

Reference 29

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Observation d12cb73d-bf69-446c-876a-d8c3d6e090cf · outbound

This paper cites Conditional ad- versarial domain adaptation,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Conditional ad- versarial domain adaptation,

Reference 30

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Observation 902e8a8b-7079-478d-a0ad-cd1d5a679c29 · outbound

This paper cites Domain adaptation in reinforcement learning via latent unified state representation,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Domain adaptation in reinforcement learning via latent unified state representation,

Reference 31

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Observation 12ee0933-538d-48dc-916d-81df5ef8780b · outbound

This paper cites Adaptive interfered fluid dy- namic system algorithm based on deep reinforcement learning framework,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Adaptive interfered fluid dy- namic system algorithm based on deep reinforcement learning framework,

Reference 32

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Observation 4b7b5c6f-f21a-4b46-9e70-c65da24e0d58 · outbound

This paper cites Sense and avoid considerations for safe suas operations in urban environments,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Sense and avoid considerations for safe suas operations in urban environments,

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-06T22:43:26.172563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:20.805296Z digest=sha256:b4e770865bfa4dc866273cfc2a8fce6831d90a4a8e0c609fad2550213e203ad4

Observation 20449be4-cc04-460d-877c-464d8249579b · outbound

This paper cites Industrial uav-based unsupervised domain adaptive crack recognitions: From database towards real-site infrastructural inspections,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Industrial uav-based unsupervised domain adaptive crack recognitions: From database towards real-site infrastructural inspections,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:25.982571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:20.879348Z digest=sha256:2296c641f77d5de047cbb060af6aa0fc47ea1b532c5e2a216405ff1ee31093b0

Observation d9bba989-7bef-4dac-a4db-c6ee9c196338 · outbound

This paper cites Decentralized autonomous navigation of a uav network for road traffic monitoring,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Decentralized autonomous navigation of a uav network for road traffic monitoring,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:25.809495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:20.957140Z digest=sha256:2ca33af6a1c7acd93e63cef8a5a4ec1adb23e1d475bfb707a2cdc5932088d2cd

Observation d41ea8c7-c5ab-498e-ae9b-0e816081083a · outbound

This paper cites Robust reinforcement learning via adversarial training with langevin dynamics,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Robust reinforcement learning via adversarial training with langevin dynamics,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:25.610212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:21.045240Z digest=sha256:2d809111590ebf55d59e6d133e779807926f773b804349804dda1bd7f2ee5e55

Observation 53513fa1-ab73-4a27-818e-0c47e45312ff · outbound

This paper cites Finding mixed nash equilibria of generative adversarial networks,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Finding mixed nash equilibria of generative adversarial networks,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:25.368811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:21.135319Z digest=sha256:6f9a3290b9144d8fcb714c8fef085dea7bb6f92e489eb8cdae93318730eccede

Observation 25f3cc57-2343-4d91-b9a7-97a1bf2e1563 · outbound

This paper cites Towards evaluating the robustness of neural networks,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Towards evaluating the robustness of neural networks,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:25.220895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:21.222088Z digest=sha256:19005a91e04c8acea93f4e15e6d0fd52e3adb162abb6bb5b9a71457634ef60cc

Observation d1dfda6b-7ef1-4ea6-9de3-41607f63a936 · outbound

This paper cites A dirichlet process mixture of robust task models for scalable lifelong reinforcement learning,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments A dirichlet process mixture of robust task models for scalable lifelong reinforcement learning,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:24.988828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:21.298248Z digest=sha256:216a49663850ac66c026c21198c7386fbc256d7c34504e761f4f170c45950f68

Observation c4bfebf8-40bb-4455-9175-d5ebe2c7e3ac · outbound

This paper cites Bisimulation metrics for continuous markov decision processes,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Bisimulation metrics for continuous markov decision processes,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:24.801212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:21.363583Z digest=sha256:faec2481f3e99423e9a212f01c7d350b56d89f30117590e4f6b7e6c4c52c51dc

Observation 148f2606-96ed-49e7-9e66-0df1a62307d0 · outbound

This paper cites Scalable methods for computing state similarity in deterministic markov decision processes,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Scalable methods for computing state similarity in deterministic markov decision processes,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:24.639416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:21.429617Z digest=sha256:ccb694293c0ff32b0e939715297b33f38a9f5d1362619808a59339d404ee2d5e

Observation 095b3342-c6c5-4064-afb6-3b91b89e4bfa · outbound

This paper cites Wasserstein gan with quadratic transport cost,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Wasserstein gan with quadratic transport cost,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:24.463683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:21.507181Z digest=sha256:61924165f91339888b620ca7937c44aa57f0bcacbf2f9a7952093ac431923cd1

Observation cd0d902a-1959-43dd-8875-21250eb8ee5e · outbound

This paper cites Distributionally robust learning,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Distributionally robust learning,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:24.317424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:21.597252Z digest=sha256:eb755e5492a5f36ee40eb1db3f0cf30a04efb35b3dc9a1e05ccc0def65541018

Observation 68274246-795d-496f-81b6-eb7ae77ad053 · outbound

This paper cites On the gener- alization gap in reparameterizable reinforcement learning,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments On the gener- alization gap in reparameterizable reinforcement learning,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:24.143220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:21.698155Z digest=sha256:6a99438cd47b6861f2acae2c8492352c5d55f13e5019a7ce7da701850e109109

Observation e5de0d8a-c91f-4109-91d7-9b3a50cee501 · outbound

This paper cites Real-Time Bayesian Detection of Drift-Evasive GNSS Spoofing in Reinforcement Learning Based UAV Deconfliction.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Real-Time Bayesian Detection of Drift-Evasive GNSS Spoofing in Reinforcement Learning Based UAV Deconfliction

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:43:22.839924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:21.785430Z digest=sha256:f6d62fc0aae38e7d163d2bcf8a5f1c2865aa8372951e00266bfb77bd1f102d3e

Observation 4802a790-c89e-45b4-bf93-03a61219bb5e · outbound

This paper cites Gnss jamming and spoofing threats in uav navigation: Countermeasure status and challenges,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Gnss jamming and spoofing threats in uav navigation: Countermeasure status and challenges,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:23.992131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:21.850012Z digest=sha256:ddb0db4e316ff86e8c7cc6368a49073e24454ca278e181ecfd5b6de33e363157

Observation 1e9f2b70-9347-45af-bace-37db6e002831 · outbound

This paper cites A uav path planning method in three-dimensional urban airspace based on safe reinforcement learning,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments A uav path planning method in three-dimensional urban airspace based on safe reinforcement learning,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:23.810720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:21.956202Z digest=sha256:664193c50ea78d648429c800865717ae3aa2c1a1c07c9dddea46adb400b546bd

Observation b3f2f769-8632-4c87-8c3a-ef61067270d2 · outbound

This paper cites Meta policy switching for resilient uav navigation in adversarial airspace,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Meta policy switching for resilient uav navigation in adversarial airspace,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:23.601311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:22.060173Z digest=sha256:eaa52cc5901fed088b81c7a0e207420ee0cba5c7e96befe566d1e3d99a08094a

Observation 24f97ba9-00ab-415d-85b3-6352320714c6 · outbound

This paper cites Adaptively Preconditioned Stochastic Gradient Langevin Dynamics.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Adaptively Preconditioned Stochastic Gradient Langevin Dynamics

Reference 49

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:43:22.677293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:22.222134Z digest=sha256:c0e4814e70cf639a31d874b2a2e80d3f2dbc949603d1737f4fbe23a2a00961ca

Observation 19e72d0e-69f0-4329-95be-83e51179181e · outbound

This paper cites Adaptive gradient methods with dynamic bound of learning rate,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Adaptive gradient methods with dynamic bound of learning rate,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:23.356121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:22.315445Z digest=sha256:2610d723c224231e8af03b309a960a85bbc1ff8eace510857861283d24def3ff

Observation 600a51fc-faa0-4f9e-b86b-cf2bbb356f08 · outbound

This paper cites A sufficient condition for convergences of adam and rmsprop,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments A sufficient condition for convergences of adam and rmsprop,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:23.136803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:22.405093Z digest=sha256:237637e9d23620235a62d72af4d095a1568b08de5365dcc769f6a4f2e0441c0a

Observation 0b3dab03-d21a-4d3a-a679-0802848ee16f · outbound

This paper cites Benchmarking deep reinforcement learning for continuous control,.

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments Benchmarking deep reinforcement learning for continuous control,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:22.969827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:43:22.518129Z digest=sha256:359c66a5f32ea294750cc3be5f80e1b2e3c1e51055e62061786011448c1708ef

Pith citing papers

Observation d8cb2a31-e0bb-4b49-a175-d4997502a458 · inbound

Real-Time Bayesian Detection of Drift-Evasive GNSS Spoofing in Reinforcement Learning Based UAV Deconfliction cites this paper.

Real-Time Bayesian Detection of Drift-Evasive GNSS Spoofing in Reinforcement Learning Based UAV Deconfliction Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:19:43.382028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:19:43.140620Z digest=sha256:16e690f5e039c6a9dfb8afdb9a738ebe7dec58b83c47a10ba757667e403e5bac