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Paper Citation Record · LEDGER

Provably Robust Federated Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 2 inbound Pith citation observations for arXiv:2502.08123.

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

pith.paper-citation-record.v1
2502.08123 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T10:26:24.839782Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:08:50.598526Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T20:50:36.708183Z

Reference resolution

55 of 55 outbound references displayed

  • verified exact1
  • verified fuzzy50
  • unresolved4
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cebfa685-2b4d-4a1b-aa43-c138f51dbeb6 · outbound

This paper cites How to backdoor federated learning.

Provably Robust Federated Reinforcement Learning How to backdoor federated learning

Reference 1

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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.

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Observation 360a2e21-42ec-4501-bdba-3b8111aef215 · outbound

This paper cites Neuronlike adaptive elements that can solve difficult learning control problems.

Provably Robust Federated Reinforcement Learning Neuronlike adaptive elements that can solve difficult learning control problems

Reference 2

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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.

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Observation 30471b45-3e91-493e-85f0-962f9ba30b0f · outbound

This paper cites A little is enough: Circumvent- ing defenses for distributed learning.

Provably Robust Federated Reinforcement Learning A little is enough: Circumvent- ing defenses for distributed learning

Reference 3

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Source-reported events for the cited work

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Observation 216b2d19-75e7-4d7c-b62a-e667c137e742 · outbound

This paper cites Machine learning with adversaries: Byzantine tolerant gradient descent.

Provably Robust Federated Reinforcement Learning Machine learning with adversaries: Byzantine tolerant gradient descent

Reference 4

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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.

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Observation b6d17d28-ebca-4356-9262-7338f66ca4a0 · outbound

This paper cites Multi-agent reinforcement learning: An overview.

Provably Robust Federated Reinforcement Learning Multi-agent reinforcement learning: An overview

Reference 5

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Source-reported events for the cited work

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Observation ab9ccf64-38ca-4b41-b371-b82fffb0fe37 · outbound

This paper cites Density-based cluster- ing based on hierarchical density estimates.

Provably Robust Federated Reinforcement Learning Density-based cluster- ing based on hierarchical density estimates

Reference 6

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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.

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Observation 7c735e46-2c8c-4f11-8ca5-c954ca47ab0b · outbound

This paper cites Fltrust: Byzantine-robust federated learning via trust bootstrapping.

Provably Robust Federated Reinforcement Learning Fltrust: Byzantine-robust federated learning via trust bootstrapping

Reference 7

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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.

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Observation 06494eb4-bf6a-40ec-94f8-6fa2e03c9aa1 · outbound

This paper cites Provably secure federated learning against malicious clients.

Provably Robust Federated Reinforcement Learning Provably secure federated learning against malicious clients

Reference 8

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Source-reported events for the cited work

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

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Observation d59f0ff1-af04-4394-ac09-2d824817296f · outbound

This paper cites Distributed statistical machine learning in adversarial settings: Byzantine gradient descent.

Provably Robust Federated Reinforcement Learning Distributed statistical machine learning in adversarial settings: Byzantine gradient descent

Reference 9

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Observation bac5b9fd-6c5a-4896-bf7b-482215cae583 · outbound

This paper cites Geometric median in nearly linear time.

Provably Robust Federated Reinforcement Learning Geometric median in nearly linear time

Reference 10

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Observation e49f55d8-56cb-4f13-acae-34b84e4ceff4 · outbound

This paper cites Bench- marking deep reinforcement learning for continuous control.

Provably Robust Federated Reinforcement Learning Bench- marking deep reinforcement learning for continuous control

Reference 11

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Source-reported events for the cited work

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Observation f1c509d5-1fa6-4823-b667-5505d416ff5a · outbound

This paper cites Challenges of real-world reinforcement learning: definitions, benchmarks and analysis.

Provably Robust Federated Reinforcement Learning Challenges of real-world reinforcement learning: definitions, benchmarks and analysis

Reference 12

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Source-reported events for the cited work

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

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Observation 6acd176e-da6f-4d5b-888e-2ef934203cbf · outbound

This paper cites Fault-tolerant federated reinforcement learning with theoreti- cal guarantee.

Provably Robust Federated Reinforcement Learning Fault-tolerant federated reinforcement learning with theoreti- cal guarantee

Reference 13

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Source-reported events for the cited work

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

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Observation 22bb6c60-c2e9-4e2e-9273-2cf12555054a · outbound

This paper cites Local model poisoning attacks to byzantine-robust federated learning.

Provably Robust Federated Reinforcement Learning Local model poisoning attacks to byzantine-robust federated learning

Reference 14

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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.

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Observation 14cb2c15-8cb4-4494-a626-62bd27f2f80c · outbound

This paper cites Aflguard: Byzantine-robust asynchronous federated learning.

Provably Robust Federated Reinforcement Learning Aflguard: Byzantine-robust asynchronous federated learning

Reference 15

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Source-reported events for the cited work

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Observation 1f5d09ed-f7f6-4c8f-a3d4-3bd6f7697d68 · outbound

This paper cites Do we really need to design new byzantine-robust aggregation rules? In NDSS, 2025.

Provably Robust Federated Reinforcement Learning Do we really need to design new byzantine-robust aggregation rules? In NDSS, 2025

Reference 16

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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.

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Observation 33604c9a-6f7b-470c-b1eb-f86b7ac24219 · outbound

This paper cites Byzantine-robust decentralized federated learning.

Provably Robust Federated Reinforcement Learning Byzantine-robust decentralized federated learning

Reference 17

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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.

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Observation 5e162cee-0bff-4245-a8ca-0c5883423def · outbound

This paper cites On the hardness of decentralized multi-agent policy evaluation under byzantine attacks.

Provably Robust Federated Reinforcement Learning On the hardness of decentralized multi-agent policy evaluation under byzantine attacks

Reference 18

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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.

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Observation b1c9548b-e83e-4553-bddc-ed591c735d21 · outbound

This paper cites Federated deep reinforcement learning based trajectory design for uav-assisted networks with mobile ground devices.

Provably Robust Federated Reinforcement Learning Federated deep reinforcement learning based trajectory design for uav-assisted networks with mobile ground devices

Reference 19

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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.

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Observation dcfb312c-59af-4f24-baf7-2d6329ca3f17 · outbound

This paper cites Federated reinforcement learning with environment heterogeneity.

Provably Robust Federated Reinforcement Learning Federated reinforcement learning with environment heterogeneity

Reference 20

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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.

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Observation 8a9ec420-2867-4b2a-96fe-acbaa50d3646 · outbound

This paper cites Fed- erated reinforcement learning: Linear speedup under markovian sampling.

Provably Robust Federated Reinforcement Learning Fed- erated reinforcement learning: Linear speedup under markovian sampling

Reference 21

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Observation 4cc4f2c2-1e08-4299-a859-81ab5c573d79 · outbound

This paper cites Reinforcement learning in robotics: A survey.

Provably Robust Federated Reinforcement Learning Reinforcement learning in robotics: A survey

Reference 22

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Observation c9b09069-57a7-4192-833e-94b69f5949de · outbound

This paper cites Less than a single pass: Stochastically controlled stochastic gradient.

Provably Robust Federated Reinforcement Learning Less than a single pass: Stochastically controlled stochastic gradient

Reference 23

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

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Observation 11c8d8b8-35e3-4759-a5c9-fe288a87d944 · outbound

This paper cites Federated transfer reinforcement learning for autonomous driving.

Provably Robust Federated Reinforcement Learning Federated transfer reinforcement learning for autonomous driving

Reference 24

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

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Observation 3bf4faba-27d4-46ce-b25e-e34458508bae · outbound

This paper cites On the robustness of cooperative multi-agent reinforcement learning.

Provably Robust Federated Reinforcement Learning On the robustness of cooperative multi-agent reinforcement learning

Reference 25

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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.

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Observation 163f3cc3-89dd-45f3-a990-3449fb10edc1 · outbound

This paper cites Lifelong federated reinforcement learning: a learning architecture for navigation in cloud robotic systems.

Provably Robust Federated Reinforcement Learning Lifelong federated reinforcement learning: a learning architecture for navigation in cloud robotic systems

Reference 26

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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.

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Observation 5569812f-1804-4c45-92a7-66674f342c6c · outbound

This paper cites Reinforcement learning for clinical decision support in critical care: comprehensive review.

Provably Robust Federated Reinforcement Learning Reinforcement learning for clinical decision support in critical care: comprehensive review

Reference 27

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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.

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Observation 95a7bb21-c045-42e7-abae-83d4479c8b22 · outbound

This paper cites Local Environment Poisoning Attacks on Federated Reinforcement Learning.

Provably Robust Federated Reinforcement Learning Local Environment Poisoning Attacks on Federated Reinforcement Learning

Reference 28

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local_arxiv, observed 2026-08-08T10:26:24.890506Z

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.

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Observation ad56f853-3420-4694-88a6-a33094c08f01 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data.

Provably Robust Federated Reinforcement Learning Communication-efficient learning of deep networks from decentralized data

Reference 29

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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.

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Observation 25e3fe30-0a45-4413-adae-45f20763de98 · outbound

This paper cites Geometric median and robust estimation in banach spaces.

Provably Robust Federated Reinforcement Learning Geometric median and robust estimation in banach spaces

Reference 30

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raw_fallback, observed 2026-08-08T10:26:25.166028Z

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.

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Observation 691baa47-9535-4e87-bd16-0964ca79ce0e · outbound

This paper cites Asynchronous methods for deep reinforcement learning.

Provably Robust Federated Reinforcement Learning Asynchronous methods for deep reinforcement learning

Reference 31

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raw_fallback, observed 2026-08-08T10:26:25.154276Z

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.

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Observation 9c13aa9e-b4c0-423d-9761-bb26d0ae7a0a · outbound

This paper cites Every vote counts: Ranking-based training of federated learning to resist poisoning attacks.

Provably Robust Federated Reinforcement Learning Every vote counts: Ranking-based training of federated learning to resist poisoning attacks

Reference 32

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raw_fallback, observed 2026-08-08T10:26:25.141800Z

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.

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Observation 58a1954c-f486-4715-b1b9-12ecf2304921 · outbound

This paper cites Massively Parallel Methods for Deep Reinforcement Learning.

Provably Robust Federated Reinforcement Learning Massively Parallel Methods for Deep Reinforcement Learning

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:26:24.747646Z digest=sha256:dcab57dc2b88cc0f6109e0ed472b0c032f79b5f000a95a0eed76c9e438b530f9

Observation 7b8b388c-93b5-4c26-aa47-3e39ab35056a · outbound

This paper cites Flame: Taming backdoors in federated learning.

Provably Robust Federated Reinforcement Learning Flame: Taming backdoors in federated learning

Reference 34

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raw_fallback, observed 2026-08-08T10:26:25.131300Z

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=2026-08-08T10:26:24.751726Z digest=sha256:f2125bf014d393a219da7db7ddd413a5f38576b6262cb503d376120ba402b657

Observation 60043a65-ef7d-4783-94c2-62dc7bdd554a · outbound

This paper cites Justinian’s gaavernor: Robust distributed learning with gradient aggregation agent.

Provably Robust Federated Reinforcement Learning Justinian’s gaavernor: Robust distributed learning with gradient aggregation agent

Reference 35

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raw_fallback, observed 2026-08-08T10:26:25.121014Z

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=2026-08-08T10:26:24.755764Z digest=sha256:18729a6edc5caf226d08d5696ab02438414fac77afecd4a336f65fc92236f833

Observation f7d32cd9-2190-44e1-8fa9-2a65a9207cc3 · outbound

This paper cites Detox: A redundancy-based framework for faster and more robust gradient aggregation.

Provably Robust Federated Reinforcement Learning Detox: A redundancy-based framework for faster and more robust gradient aggregation

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:25.110006Z

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=2026-08-08T10:26:24.759712Z digest=sha256:7e53ce2a07696654d8bc4c86c029199df5c43a2dc505ba0eb85b8259b7c21a74

Observation 5dccb675-45bc-4ed3-ba88-0ba95c2aa75d · outbound

This paper cites Deepsight: Mitigating backdoor attacks in federated learning through deep model inspection.

Provably Robust Federated Reinforcement Learning Deepsight: Mitigating backdoor attacks in federated learning through deep model inspection

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:25.096808Z

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=2026-08-08T10:26:24.763916Z digest=sha256:cf37de2930da783d40212ebf4341dca8c579987d4aaad5ee8fb8876324370b51

Observation 495b4c83-8f7d-4914-8891-3797ee6e46fd · outbound

This paper cites Manipulating the byzantine: Optimizing model poisoning attacks and defenses for federated learning.

Provably Robust Federated Reinforcement Learning Manipulating the byzantine: Optimizing model poisoning attacks and defenses for federated learning

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-08T10:26:24.767632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:26:24.767632Z digest=sha256:da0326be68e43aa847f6aa18d93e8ce0358b1fc4ca03464a96dda6f064ebf051

Observation 0def2e6d-97da-416d-8d2b-e71851fcab5b · outbound

This paper cites Reinforcement learning: An introduction.

Provably Robust Federated Reinforcement Learning Reinforcement learning: An introduction

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-08T10:26:24.771327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:26:24.771327Z digest=sha256:4ca8b66c3acdee6ec8df9e23bca1e459f282019cd42c17d5a14003deb6d1b89f

Observation 48ced4fc-64c8-4404-b67f-acb289e1501c · outbound

This paper cites Multi-agent reinforcement learning: Independent vs.

Provably Robust Federated Reinforcement Learning Multi-agent reinforcement learning: Independent vs

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:25.071023Z

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=2026-08-08T10:26:24.774981Z digest=sha256:deaf4aad4250fb0e53ce055959eadb6767e0697036d378202b14bbe5fc80a8db

Observation d4b9c40b-a84f-4523-b57c-a1c553820455 · outbound

This paper cites Mujoco: A physics engine for model-based control.

Provably Robust Federated Reinforcement Learning Mujoco: A physics engine for model-based control

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-08T10:26:24.778594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:26:24.778594Z digest=sha256:6c7fa89fc178d18f9d1b1e3668b3967cdc4e2377546860da688b8493002b2bb1

Observation 861ef455-35d0-4b4d-83c4-3d6acdd4490b · outbound

This paper cites Grandmaster level in starcraft ii using multi-agent reinforcement learning.

Provably Robust Federated Reinforcement Learning Grandmaster level in starcraft ii using multi-agent reinforcement learning

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:25.053305Z

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=2026-08-08T10:26:24.782355Z digest=sha256:8a0c093807b784c6f14eec173d2b0ede5b8628ed1ed5e0c0530493b55e028bb0

Observation abbf106d-6374-4200-8401-ac2479685a04 · outbound

This paper cites Attack of the tails: Yes, you really can backdoor federated learning.

Provably Robust Federated Reinforcement Learning Attack of the tails: Yes, you really can backdoor federated learning

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:25.041907Z

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=2026-08-08T10:26:24.786138Z digest=sha256:b511470725481f99a82e97655bb6974ff1c8ffaba7c5197c788595d843cb5ffa

Observation 2d76e1dd-8a10-4ca8-b49f-1fe3b4d2012f · outbound

This paper cites Federated deep reinforcement learning for internet of things with decentralized cooperative edge caching.

Provably Robust Federated Reinforcement Learning Federated deep reinforcement learning for internet of things with decentralized cooperative edge caching

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:25.030777Z

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=2026-08-08T10:26:24.790239Z digest=sha256:97f7c5cd05bd6ac8397b8ce18505165ad923293cc5420f39b03a692fbcf8f854

Observation 44ed3b38-4321-4c30-bf49-a5b05bd01139 · outbound

This paper cites Simple statistical gradient-following algorithms for connec- tionist reinforcement learning.

Provably Robust Federated Reinforcement Learning Simple statistical gradient-following algorithms for connec- tionist reinforcement learning

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:25.019030Z

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=2026-08-08T10:26:24.794783Z digest=sha256:9d52e5195a2103d17fbde41d6e2db801de60716afe674274aff33fc514426d7c

Observation d1fb210d-4cda-49f9-9bec-5dea1b03508a · outbound

This paper cites Dba: Distributed backdoor attacks against federated learning.

Provably Robust Federated Reinforcement Learning Dba: Distributed backdoor attacks against federated learning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:25.005755Z

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=2026-08-08T10:26:24.799779Z digest=sha256:c774e87c5bc1f4337496b3c87087df22f02e65d6ee149ccc5bca8236d4d4a525

Observation a2fe4fb3-bcdb-403a-a8c1-a773eee3bbd0 · outbound

This paper cites Zeno: Distributed stochastic gradient descent with suspicion-based fault-tolerance.

Provably Robust Federated Reinforcement Learning Zeno: Distributed stochastic gradient descent with suspicion-based fault-tolerance

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:24.993259Z

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=2026-08-08T10:26:24.804440Z digest=sha256:d99bedad46dd085716c70d079f09d4d3985d5113c8b231c1df9bc0e7bc42a045

Observation 78af5734-887b-4f8f-bc60-622aca01322d · outbound

This paper cites Fedredefense: Defending against model poisoning attacks for federated learning using model update reconstruction error.

Provably Robust Federated Reinforcement Learning Fedredefense: Defending against model poisoning attacks for federated learning using model update reconstruction error

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:24.982204Z

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=2026-08-08T10:26:24.809031Z digest=sha256:32ba25441e673cabfcd5ba377dc1b5fbdce40fc3e8b907a631e7694c69a16340

Observation 02c77d6f-eded-40f9-91e3-1f1e9cbed201 · outbound

This paper cites Byzantine- robust distributed learning: Towards optimal statistical rates.

Provably Robust Federated Reinforcement Learning Byzantine- robust distributed learning: Towards optimal statistical rates

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:24.971086Z

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=2026-08-08T10:26:24.813216Z digest=sha256:94ae8cab04dbb2c2f0cc295be9cdd42931b82ce068ba856f25adef63a6d23553

Observation f0e26d69-7024-4d3b-840c-0c693e46411b · outbound

This paper cites Poisoning federated recommender systems with fake users.

Provably Robust Federated Reinforcement Learning Poisoning federated recommender systems with fake users

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:24.959983Z

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=2026-08-08T10:26:24.817681Z digest=sha256:03a09fbc15e061b42a560d8a981425ff40ccad615b08def50cae4be68df8fc2b

Observation 3a99c968-37f6-4ba5-a8de-0b59e4f657e7 · outbound

This paper cites Federated reinforcement learning for generalizable motion planning.

Provably Robust Federated Reinforcement Learning Federated reinforcement learning for generalizable motion planning

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:24.947659Z

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=2026-08-08T10:26:24.822607Z digest=sha256:9af4747b96d6b6df3e3b9a196322dec54c197a2545ef1a03e9620c62da3a968f

Observation d69129b8-70f5-471d-8f7d-702d5079de6d · outbound

This paper cites Fully decentralized multi-agent reinforcement learning with networked agents.

Provably Robust Federated Reinforcement Learning Fully decentralized multi-agent reinforcement learning with networked agents

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:24.936871Z

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=2026-08-08T10:26:24.827745Z digest=sha256:f763f62ca7e49cfbcdf500c704b325d82f903dbb38f2e76fbc48368475a9f650

Observation add09c4b-a998-4461-ad90-57a7a35a4ea8 · outbound

This paper cites Adaptive reward- poisoning attacks against reinforcement learning.

Provably Robust Federated Reinforcement Learning Adaptive reward- poisoning attacks against reinforcement learning

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:24.926001Z

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=2026-08-08T10:26:24.831876Z digest=sha256:9496a1813c92bae6f2d6c83ee9084ca5e3e90e931689c0009d3608cee25adb42

Observation 5c8533a3-eeeb-4069-bf0e-018aa96242c4 · outbound

This paper cites Fldetector: Defending federated learning against model poisoning attacks via detecting malicious clients.

Provably Robust Federated Reinforcement Learning Fldetector: Defending federated learning against model poisoning attacks via detecting malicious clients

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:24.915193Z

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=2026-08-08T10:26:24.835965Z digest=sha256:cd095b748354e65b31bd718e235f73fc21155f50e70306e64d83954462b21551

Observation 73a1cbae-100c-41b3-a1fb-1b3ed66bb966 · outbound

This paper cites Poisoning attacks on federated learning-based wireless traffic prediction.

Provably Robust Federated Reinforcement Learning Poisoning attacks on federated learning-based wireless traffic prediction

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:26:24.903981Z

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=2026-08-08T10:26:24.839782Z digest=sha256:1f11e90faffc5a9896b8dca97b128c556a02a438274e0dfd91ef2b5ba9ee3fb2

Pith citing papers

Observation 1562e15c-6ee6-4560-83b0-290f3d01cf64 · inbound

Beyond Prediction: Reinforcement Learning as the Defining Leap in Healthcare AI cites this paper.

Beyond Prediction: Reinforcement Learning as the Defining Leap in Healthcare AI Provably Robust Federated Reinforcement Learning

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-05T15:08:50.598526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:08:50.598526Z digest=sha256:12633aa800be5da8e39a502e37c5a4ef6ede249b5262a0e2221c576bb762fd3d

Observation b63d69a2-087a-4d24-aa67-7ae6a0f84747 · inbound

ARM: Discovering Agentic Reasoning Modules for Generalizable Multi-Agent Systems cites this paper.

ARM: Discovering Agentic Reasoning Modules for Generalizable Multi-Agent Systems Provably Robust Federated Reinforcement Learning

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-21T20:50:36.710159Z

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=2026-05-21T20:47:24.114157Z digest=sha256:f1e454954f6d77214451af3c5be497111a430ff93065e23718fdbae39d857de8