Paper Citation Record · LEDGER

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning

As of 17 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2505.09959.

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

pith.paper-citation-record.v1
2505.09959 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:24:27.492445Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

39 of 39 outbound references displayed

verified exact2
verified fuzzy24
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fb793582-7c90-44c6-ba4b-cefc840b4989 · outbound

This paper cites Deep learning with differential privacy.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Deep learning with differential privacy

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.840092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b2c88f85-0f19-4a41-b6bc-0064c6acbd28 · outbound

This paper cites Mico: Im- proved representations via sampling-based state similarity for markov decision processes.Advances in Neural Infor- mation Processing Systems, 34:30113–30126,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Mico: Im- proved representations via sampling-based state similarity for markov decision processes.Advances in Neural Infor- mation Processing Systems, 34:30113–30126,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.831690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 925ec993-e123-487c-b484-97353381e7d4 · outbound

This paper cites Scalable methods for computing state similarity in deterministic markov deci- sion processes.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Scalable methods for computing state similarity in deterministic markov deci- sion processes

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.823189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3404f9bc-0019-4157-aed4-6e844df8d70b · outbound

This paper cites Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach.Advances in neural information processing sys- tems, 33:3557–3568,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach.Advances in neural information processing sys- tems, 33:3557–3568,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.797318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 85eccdc6-10df-49fe-b11d-e355a12f58c9 · outbound

This paper cites Fault-tolerant federated reinforcement learning with the- oretical guarantee.Advances in Neural Information Pro- cessing Systems, 34:1007–1021,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Fault-tolerant federated reinforcement learning with the- oretical guarantee.Advances in Neural Information Pro- cessing Systems, 34:1007–1021,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.788768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a52d40f5-14c9-4177-b11c-bfc75cee8221 · outbound

This paper cites FedHQL: Federated Heterogeneous Q-Learning.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning FedHQL: Federated Heterogeneous Q-Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.408187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61bb0f1f-f0ad-45d0-8dd7-1fec51f3060c · outbound

This paper cites Bisimulation metrics for continuous markov decision processes.SIAM Journal on Computing, 40(6):1662–1714,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Bisimulation metrics for continuous markov decision processes.SIAM Journal on Computing, 40(6):1662–1714,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.771238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f7cff97d-8b57-40f8-abed-4ee21c711b72 · outbound

This paper cites Federated reinforcement learn- ing with environment heterogeneity.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Federated reinforcement learn- ing with environment heterogeneity

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.762604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 595fc78b-51ef-4dfa-ad86-edbccd637b15 · outbound

This paper cites Towards robust bisimulation metric learning.Advances in Neural Infor- mation Processing Systems, 34:4764–4777,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Towards robust bisimulation metric learning.Advances in Neural Infor- mation Processing Systems, 34:4764–4777,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.753853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e09e6fdc-cb81-4da3-b975-76e750144b93 · outbound

This paper cites Think Locally, Act Globally: Federated Learning with Local and Global Representations.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Think Locally, Act Globally: Federated Learning with Local and Global Representations

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.432753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc61d14e-c245-4cfb-bd73-3d0b1e896e92 · outbound

This paper cites Policy-independent behavioral metric-based rep- resentation for deep reinforcement learning.Proceed- ings of the AAAI Conference on Artificial Intelligence, 37:8746–8754, 06.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Policy-independent behavioral metric-based rep- resentation for deep reinforcement learning.Proceed- ings of the AAAI Conference on Artificial Intelligence, 37:8746–8754, 06

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.745193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8d4e8b65-877a-4741-81b1-cd4efd3e7712 · outbound

This paper cites Threats to federated learning: A survey,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Threats to federated learning: A survey,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.736147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d8d3fea5-e89f-4063-9473-94179845fbaa · outbound

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

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Communication-efficient learning of deep networks from decentralized data

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.440142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc443d73-0799-4746-be1e-0105d8490d17 · outbound

This paper cites A survey on security and privacy of federated learning.Future Generation Computer Systems, 115:619–640,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning A survey on security and privacy of federated learning.Future Generation Computer Systems, 115:619–640,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.713626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3f50439a-5ed8-48d1-8a2d-4940325482df · outbound

This paper cites Privacy-preserving federated learning using homomorphic encryption.Applied Sciences, 12(2):734,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Privacy-preserving federated learning using homomorphic encryption.Applied Sciences, 12(2):734,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.704771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6363fb45-ca1f-463a-8dda-88b4ae2923f4 · outbound

This paper cites Federated Reinforcement Learning: Techniques, Applications, and Open Challenges.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Federated Reinforcement Learning: Techniques, Applications, and Open Challenges

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.449205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0240c8f0-44b7-488a-91d9-b241c909d240 · outbound

This paper cites Adaptive Federated Optimization.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Adaptive Federated Optimization

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.451522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d56bbf8-f5e4-4a1c-a511-7f5a4c4f6e22 · outbound

This paper cites Personalized federated learning with moreau en- velopes.Advances in neural information processing sys- tems, 33:21394–21405,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Personalized federated learning with moreau en- velopes.Advances in neural information processing sys- tems, 33:21394–21405,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.453799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e2aa028-0c49-4a01-bdeb-fcf866c17888 · outbound

This paper cites Federated learning from pre-trained models: A contrastive learning ap- proach.Advances in neural information processing sys- tems, 35:19332–19344,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Federated learning from pre-trained models: A contrastive learning ap- proach.Advances in neural information processing sys- tems, 35:19332–19344,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.691228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 28d3b84a-01e5-4c4c-83cf-59ae7ac7035f · outbound

This paper cites Differentiated Federated Reinforcement Learning Based Traffic Offloading on Space-Air-Ground Integrated Networks.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Differentiated Federated Reinforcement Learning Based Traffic Offloading on Space-Air-Ground Integrated Networks

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:24:27.556140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f4924f5c-39ff-4c37-8aa1-a33671b683b7 · outbound

This paper cites DeepMind Control Suite.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning DeepMind Control Suite

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.462645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e514469a-9efe-431a-9042-ce1815ef656c · outbound

This paper cites A hybrid approach to privacy-preserving feder- ated learning.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning A hybrid approach to privacy-preserving feder- ated learning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.682710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3a99dc7e-4a42-42e8-985d-d868e6b6c761 · outbound

This paper cites Turbosvm-fl: Boost- ing federated learning through svm aggregation for lazy clients.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Turbosvm-fl: Boost- ing federated learning through svm aggregation for lazy clients

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.666299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 49aed078-ddc7-42b7-9de5-14a9594c55af · outbound

This paper cites Learning Invariant Representations for Reinforcement Learning without Reconstruction.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Learning Invariant Representations for Reinforcement Learning without Reconstruction

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.477890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40d31800-c655-4806-b852-e16465c0b531 · outbound

This paper cites No free lunch theorem for se- curity and utility in federated learning.ACM Transactions on Intelligent Systems and Technology, 14(1):1–35,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning No free lunch theorem for se- curity and utility in federated learning.ACM Transactions on Intelligent Systems and Technology, 14(1):1–35,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.649910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6e8c9a09-d682-4127-8315-8e8fc9c22d42 · outbound

This paper cites Federated unsupervised representation learning.Frontiers of Information Technol- ogy & Electronic Engineering, 24(8):1181–1193,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Federated unsupervised representation learning.Frontiers of Information Technol- ogy & Electronic Engineering, 24(8):1181–1193,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.641483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 548f71d0-aef0-4f75-836c-d356227e7da8 · outbound

This paper cites Federated Learning with Non-IID Data.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Federated Learning with Non-IID Data

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.486600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82467fec-e257-4f6d-a384-8e9565ed8702 · outbound

This paper cites Deep leakage from gradients,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Deep leakage from gradients,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.632880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d07fc6b2-b736-4bc4-8022-dbb74da43b10 · outbound

This paper cites Federated Deep Reinforcement Learning.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Federated Deep Reinforcement Learning

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.492445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dd7e283-a87c-4e6b-abb7-3e75c8e75c55 · outbound

This paper cites Differentially Private Federated Learning: A Client Level Perspective.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.418740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2667947a-954b-4298-82c3-e299e98c758e · outbound

This paper cites Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.263005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6c2b979-84c2-4440-ad01-d087f7ae4739 · outbound

This paper cites Aby3: A mixed protocol framework for machine learning.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Aby3: A mixed protocol framework for machine learning

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.722332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4e00b73f-371a-43c5-be00-5ddc7ae020f4 · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Soft Actor-Critic Algorithms and Applications

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.423280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a395b782-7eb5-44d9-94d9-f1406e680ebf · outbound

This paper cites Optimizing federated learning on non- iid data with reinforcement learning.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Optimizing federated learning on non- iid data with reinforcement learning

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.674797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e08d189d-c095-428a-8ef2-f5e839400c8b · outbound

This paper cites Learn- ing representations via a robust behavioral metric for deep reinforcement learning.Advances in Neural Information Processing Systems, 35:36654–36666,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Learn- ing representations via a robust behavioral metric for deep reinforcement learning.Advances in Neural Information Processing Systems, 35:36654–36666,

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.814769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c9604ca5-4444-4e33-a118-5baa0849c3f3 · outbound

This paper cites Multi-Task Federated Reinforcement Learning with Adversaries.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Multi-Task Federated Reinforcement Learning with Adversaries

Reference 2021

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:24:27.615399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9f8ebf99-d166-4723-80a9-cdb99ac1be64 · outbound

This paper cites Exploiting shared repre- sentations for personalized federated learning.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Exploiting shared repre- sentations for personalized federated learning

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.806141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1a567423-fbab-4c77-bb77-02f17500b032 · outbound

This paper cites Pri- vacy preserving machine learning with homomorphic en- cryption and federated learning.Future Internet, 13(4):94,.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Pri- vacy preserving machine learning with homomorphic en- cryption and federated learning.Future Internet, 13(4):94,

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.779793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4b6a98b9-3101-4ed6-a561-a86f56d9efba · outbound

This paper cites Federated learning with dif- ferential privacy: Algorithms and performance analysis.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Federated learning with dif- ferential privacy: Algorithms and performance analysis

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:24:27.658206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.