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Paper Citation Record · LEDGER

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning

As of 7 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2507.03973.

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

pith.paper-citation-record.v1
2507.03973 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:10:59.966903Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

62 of 62 outbound references displayed

  • verified exact3
  • verified fuzzy50
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 993d0ab3-31b8-4909-adcb-ee3ecdc1e6cc · outbound

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

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Communication-efficient learning of deep networks from decentralized data,

Reference 1

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raw_fallback, observed 2026-08-06T20:11:03.459893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:54.533861Z digest=sha256:13688d1fc27a8cea9b2827bbe3a0f7054ecd6b86547e195f17f97fb0ea886b14

Observation c1c4aeaf-22de-43f5-b8c6-f6d32e380f06 · outbound

This paper cites Federated learning for the Internet of Things: Applications, challenges, and opportunities,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Federated learning for the Internet of Things: Applications, challenges, and opportunities,

Reference 2

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raw_fallback, observed 2026-08-06T20:11:03.448167Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:54.595568Z digest=sha256:948f14cae3c096529a3fde71fce9e7d11f4e270e3eec2889adf4be7259a4e5ee

Observation 1e6ee25c-cae0-4341-aea9-097e416315ec · outbound

This paper cites Confederated learning: Federated learning with decentralized edge servers,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Confederated learning: Federated learning with decentralized edge servers,

Reference 3

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raw_fallback, observed 2026-08-06T20:11:03.436919Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:54.692592Z digest=sha256:969d9cfe1c8275edeb99518f0e8a90c891f94500f6a996bec5d0ff8814627056

Observation 59654741-e401-425a-92bc-0b53ec26cf30 · outbound

This paper cites A survey on federated learning,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning A survey on federated learning,

Reference 4

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raw_fallback, observed 2026-08-06T20:11:03.424847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:54.787154Z digest=sha256:8f637b66c3243d1e35f8ff22c25e39ef7e36f61d15118f44a9782ae7066f7fad

Observation be144260-4682-4f14-9eb7-22b7af74628f · outbound

This paper cites Heterogeneous feder- ated learning: State-of-the-art and research challenges,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Heterogeneous feder- ated learning: State-of-the-art and research challenges,

Reference 5

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:54.878740Z digest=sha256:107e5b9152d4ce1c46788e4c18beda3b0f35f0ff97b10d178fbc02bcca4fa501

Observation 6f99b6ca-d81c-487f-93f5-7a0f9f3f7bfb · outbound

This paper cites FedPD: A federated learning framework with adaptivity to Non-IID data,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning FedPD: A federated learning framework with adaptivity to Non-IID data,

Reference 6

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raw_fallback, observed 2026-08-06T20:11:03.399154Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:54.949577Z digest=sha256:1d4b2ae150e81cc49bab4645d53ad5b0b7ff93b3364392afb5b6cbafe1a3e121

Observation 09a99ebc-465a-43cd-ad98-ac2553936df4 · outbound

This paper cites Towards personalized federated learning,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Towards personalized federated learning,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:55.021949Z digest=sha256:ae85a1ff17ec91c8e0fcb18edb176b7c1e2ee40ec0fdc234e52c2120e39fb9f6

Observation 26ed460c-8cf2-470a-9d23-ba754f4d6a96 · outbound

This paper cites Byzantine-robust and communication-efficient personalized federated learning,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Byzantine-robust and communication-efficient personalized federated learning,

Reference 8

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raw_fallback, observed 2026-08-06T20:11:03.367570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:55.088839Z digest=sha256:81b1818a1adff9d74482b1c1a5ad6f272f13e0a457ba9b70867fa5e0bb5169ee

Observation 4819e27b-9065-448e-9009-d2f525cd02c4 · outbound

This paper cites Adaptive model pruning and personalization for federated learning over wireless networks,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Adaptive model pruning and personalization for federated learning over wireless networks,

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.353527Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:55.169911Z digest=sha256:0fbeed3393d71a7ea6de1e76fc2c6ba120c43e76b99a9f5f77df5c87e9ce7c8b

Observation 4b6fefa9-01b3-4b69-b1a5-19af753314d4 · outbound

This paper cites Personalized federated learning towards communication efficiency, robustness and fairness,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Personalized federated learning towards communication efficiency, robustness and fairness,

Reference 10

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raw_fallback, observed 2026-08-06T20:11:03.341505Z

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source=pdf_text observed=2026-08-06T20:10:55.247820Z digest=sha256:cca9f487faf922b9011a37645a0abd5bae2510fa006e5ef15b9a0414a970d5a5

Observation 377dd350-ed6f-4551-88e9-f996b0ef425c · outbound

This paper cites Communication-efficient design for quantized decentralized federated learning,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Communication-efficient design for quantized decentralized federated learning,

Reference 11

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:10:55.322851Z digest=sha256:5d97ec19975707f3aca633d7d82c84d7fecc53e2f3a1770ad308a94936dd08e3

Observation c776c5aa-152e-45ed-870a-f52a7f5832fa · outbound

This paper cites FLASH: Federated Learning-Based LLMs for Advanced Query Processing in Social Networks through RAG.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning FLASH: Federated Learning-Based LLMs for Advanced Query Processing in Social Networks through RAG

Reference 12

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local_arxiv, observed 2026-08-06T20:11:00.570927Z

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source=pdf_text observed=2026-08-06T20:10:55.368968Z digest=sha256:ccd348ad74a54ad0ea4427d917c69f91b19597fcc814bf97420acf40346cca82

Observation 474a43e3-41a0-4c28-8b83-99a0f3037f2d · outbound

This paper cites A survey of trustworthy federated learning: Issues, solutions, and challenges,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning A survey of trustworthy federated learning: Issues, solutions, and challenges,

Reference 13

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raw_fallback, observed 2026-08-06T20:11:03.320718Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:55.433398Z digest=sha256:e5e06d2696dfaaa4d3133d306b73b51d5d37b838a8ef297e7fa06d2d2e5c1b33

Observation 5cd67306-11e3-4dc8-afda-1e8b53be149b · outbound

This paper cites An experimental study of Byzantine- robust aggregation schemes in federated learning,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning An experimental study of Byzantine- robust aggregation schemes in federated learning,

Reference 14

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raw_fallback, observed 2026-08-06T20:11:03.307245Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:55.503624Z digest=sha256:d7a94eea31a96ad322328a23ca08229b3cb8ee08d97ca6091adebe024eda71ba

Observation 141bd45f-cdb5-4718-a947-d0eef873210c · outbound

This paper cites A comprehensive survey of privacy- preserving federated learning: A taxonomy, review, and future direc- tions,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning A comprehensive survey of privacy- preserving federated learning: A taxonomy, review, and future direc- tions,

Reference 15

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:55.583144Z digest=sha256:b8412e02a148d12b7645ff9f978db7dae51f4e007f81f53d604cf9b66bda9a8d

Observation 8f64aee9-5a1d-4303-8ef6-fa6a4dd68889 · outbound

This paper cites signSGD: Compressed optimisation for non-convex problems,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning signSGD: Compressed optimisation for non-convex problems,

Reference 16

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source=pdf_text observed=2026-08-06T20:10:55.662322Z digest=sha256:66ccbddadd3776c16459e02b3d99d1d90a79251db748490b96e6fb76172419ee

Observation 36a113d1-a4ec-448b-9ac2-eba98b3de409 · outbound

This paper cites signSGD with Majority Vote is Communication Efficient And Fault Tolerant.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning signSGD with Majority Vote is Communication Efficient And Fault Tolerant

Reference 17

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source=pdf_text observed=2026-08-06T20:10:55.711188Z digest=sha256:7440c51a7af03fa6be98c4b159937f0123e40421f5a0d5789a0bc262fc8f50c2

Observation 8e3a937e-a246-4927-8470-9066270d666e · outbound

This paper cites Distributed training with heterogeneous data: bridging median- and mean-based algorithms,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Distributed training with heterogeneous data: bridging median- and mean-based algorithms,

Reference 18

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raw_fallback, observed 2026-08-06T20:11:03.273582Z

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source=pdf_text observed=2026-08-06T20:10:55.752847Z digest=sha256:fc43ce1f0cf7f09309fa8d39c4f2a8384c496c793b95387e8080ffbfe0c95830

Observation 15618c20-38fd-42bc-b163-8a8f410a6b19 · outbound

This paper cites Sign-based gradient descent with heterogeneous data: Convergence and Byzantine resilience,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Sign-based gradient descent with heterogeneous data: Convergence and Byzantine resilience,

Reference 19

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raw_fallback, observed 2026-08-06T20:11:03.262387Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:55.820749Z digest=sha256:203f94071a3820c41e75c09de5a8beaa1ce28c0a33e8eef12c2cbf1b66dbfce4

Observation 9835f748-50d8-4c25-9c2c-d1df812bd609 · outbound

This paper cites z-SignFedAvg: a unified stochastic sign-based compression for federated learning,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning z-SignFedAvg: a unified stochastic sign-based compression for federated learning,

Reference 20

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source=pdf_text observed=2026-08-06T20:10:55.870023Z digest=sha256:2dab995648ab2a3cdaea8cec8acee800ae943e100a67ae28672b9ae69b57547b

Observation 721e3009-e5e0-478e-90fa-8678015c5e92 · outbound

This paper cites S 3GD-MV: Sparse-SignSGD with majority vote for communication-efficient distributed learning,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning S 3GD-MV: Sparse-SignSGD with majority vote for communication-efficient distributed learning,

Reference 21

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:55.943030Z digest=sha256:0b7cbc6223c75d1ee01b58b19cf8bf7952d7e5885abe2032c204b082eb356228

Observation b3b1607b-9981-4238-8d67-05ece76eea8b · outbound

This paper cites Federated optimization in heterogeneous networks,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Federated optimization in heterogeneous networks,

Reference 22

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raw_fallback, observed 2026-08-06T20:11:03.230343Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:56.008461Z digest=sha256:a766afa314bebffd8bdcb00a352c748b5bf63666e2cc60aa51ceebbfbbed57ad

Observation 03eac1a6-31db-4051-a066-b3480d059c08 · outbound

This paper cites Federated Learning: Strategies for Improving Communication Efficiency.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Federated Learning: Strategies for Improving Communication Efficiency

Reference 23

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no resolver link, observed 2026-08-06T20:10:56.075810Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:10:56.075810Z digest=sha256:790aaf9a4dacf62da1498ad6e9e1af2225fb8843e45ac578a41e82218616fb50

Observation 66e55aca-81fe-4647-b28c-09b2f86d421e · outbound

This paper cites QSGD: Communication-efficient SGD via gradient quantization and encoding,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning QSGD: Communication-efficient SGD via gradient quantization and encoding,

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.219880Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:56.129715Z digest=sha256:982394777effa4e312e8064c75a9b2febb0451f3722488c0c82a5f998e9b7655

Observation cf2d074b-f0c1-4bc9-a16f-934f2d016a59 · outbound

This paper cites UVeQFed: Universal vector quantization for federated learning,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning UVeQFed: Universal vector quantization for federated learning,

Reference 25

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raw_fallback, observed 2026-08-06T20:11:03.209228Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:56.170429Z digest=sha256:3809f5aea586a0dc920d554237afec8ba2fd7e003b28b0e6cfd70abfdd47b2cb

Observation eedf6339-a524-4c49-b692-adaf0bd346ed · outbound

This paper cites Adaptive gradient quantization for data-parallel SGD,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Adaptive gradient quantization for data-parallel SGD,

Reference 26

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raw_fallback, observed 2026-08-06T20:11:03.199392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:56.252726Z digest=sha256:660bc6b1e57aa23651004ecb39fd7e09fb666e7705484ae10769002841f63ac3

Observation 3c1ed7b3-3958-473a-a5f8-d6cc4f36f877 · outbound

This paper cites Communication-efficient federated learning with adaptive quantiza- tion,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Communication-efficient federated learning with adaptive quantiza- tion,

Reference 27

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raw_fallback, observed 2026-08-06T20:11:03.188676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:56.341387Z digest=sha256:bd470704e2a3ec5781d7e16fea6a7f5a1b9a89253b9bb5e9efb782c5ad18e358

Observation c178f8d0-8b2d-4c59-bb91-0b96b450a43e · outbound

This paper cites FedFQ: Federated Learning with Fine-Grained Quantization.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning FedFQ: Federated Learning with Fine-Grained Quantization

Reference 28

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local_arxiv, observed 2026-08-06T20:11:00.389558Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:56.393617Z digest=sha256:7a1a3ffcf2debc33fb43ddf628460c9203d5b6b2fbc947333ae56f7e5179273e

Observation dd41c9e3-0f0e-42fd-a548-ada942409148 · outbound

This paper cites Distributed deep reinforcement learning based gradient quantization for federated learning enabled vehicle edge computing,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Distributed deep reinforcement learning based gradient quantization for federated learning enabled vehicle edge computing,

Reference 29

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raw_fallback, observed 2026-08-06T20:11:03.177238Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:56.485358Z digest=sha256:decac34e527240d0751050f3f126329484e26cd358ce1522337656ca7041d6b4

Observation 2969dbb4-26e3-4d7b-ba02-841de7ecff2e · outbound

This paper cites Joint accuracy and latency optimization for quantized federated learning in vehicular networks,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Joint accuracy and latency optimization for quantized federated learning in vehicular networks,

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.164061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:56.573116Z digest=sha256:9b9367a7edc6dbb2472d7c6305c7d99deb383befbf8412e9cc75cb6e4167e663

Observation dbdf19c3-7cf0-4cd8-9de1-f3c753f630d6 · outbound

This paper cites The algorithmic foundations of differential privacy,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning The algorithmic foundations of differential privacy,

Reference 31

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raw_fallback, observed 2026-08-06T20:11:03.152368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:56.656474Z digest=sha256:8a2700ccfbb14d9f13d265144cb4ebfb675cb0041b4f19e18082c33393a951e5

Observation 3f23b934-92c2-474d-a608-5a995191eade · outbound

This paper cites A survey on security and privacy of federated learning,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning A survey on security and privacy of federated learning,

Reference 32

Resolution
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raw_fallback, observed 2026-08-06T20:11:03.138838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:56.770901Z digest=sha256:83f7543e93efc936e1b5ee98a16567aaaa95b24458aa93457f073e70d13e66cb

Observation 7d0775e9-3344-4ff9-908a-bf159ae6e391 · outbound

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

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 33

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no resolver link, observed 2026-08-06T20:10:56.871054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:10:56.871054Z digest=sha256:fef301626a2f46c12daa173ede9f689b7a5a0006057a3a9773b30e2ef2f8f572

Observation 2fcd9125-ea0e-4bce-99d2-5decc0d7ee5b · outbound

This paper cites cpSGD: communication-efficient and differentially-private distributed SGD,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning cpSGD: communication-efficient and differentially-private distributed SGD,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.127670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:56.974900Z digest=sha256:ed6e2bd9707f3a9a33ef8c81614d8a278575409c7ddb3b84959b5b65ea688a03

Observation 584252c9-5e26-49be-8edb-5be0288a20f4 · outbound

This paper cites The Skellam mechanism for differentially private federated learning,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning The Skellam mechanism for differentially private federated learning,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.116049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:57.058426Z digest=sha256:9f2a0d086d614ef44b8ddf26c96ef773c8cf5ad9d3249123f1b61a35c53c3098

Observation 89da891c-ee5f-4be9-ad1e-ef8c72f02ac1 · outbound

This paper cites The distributed discrete Gaussian mechanism for federated learning with secure aggregation,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning The distributed discrete Gaussian mechanism for federated learning with secure aggregation,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.103513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:57.110423Z digest=sha256:6840df8440a51c5c542245716b33c6521604eef989a021e40336f0dc677e1661

Observation e0ab9fc4-0ff2-4054-9768-2f1054222e22 · outbound

This paper cites Privacy for Free: Communication-Efficient Learning with Differential Privacy Using Sketches.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Privacy for Free: Communication-Efficient Learning with Differential Privacy Using Sketches

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T20:10:57.232378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:10:57.232378Z digest=sha256:3ac68f64ca087c14e8190f60fa4c55aee6fac5ede4dc14c9ed7e00ffd54300b9

Observation f9009b94-b4e4-4548-b4f5-b974ad5ed36a · outbound

This paper cites Joint privacy en- hancement and quantization in federated learning,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Joint privacy en- hancement and quantization in federated learning,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.091411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:57.298586Z digest=sha256:cb65535b6d889fcf70fd993c995417dca76805a79687fb851291f5d08b0d04fd

Observation c68631fb-2acb-4b8d-9d42-750d7da28d27 · outbound

This paper cites Randomized Quantization is All You Need for Differential Privacy in Federated Learning.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Randomized Quantization is All You Need for Differential Privacy in Federated Learning

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T20:10:57.412445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:10:57.412445Z digest=sha256:4529f49293a05557f661267fd07985178ba1d0f466a8cc2ab80f265000ecff7a

Observation d7b538e7-40fb-4019-80c1-73f8638f6ab2 · outbound

This paper cites vqSGD: Vector quantized stochastic gradient descent,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning vqSGD: Vector quantized stochastic gradient descent,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.075851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:57.530261Z digest=sha256:14c0d71636326f1774adafd6865d7c32a1dbf4f4e985bcec66996f864b941b30

Observation 1644fa9c-582f-4384-bed4-eb7a15257e1f · outbound

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

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Machine learning with adversaries: Byzantine tolerant gradient descent,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.062390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:57.637789Z digest=sha256:38b250876c25eb301fe9b05c3de303e7d1dae110714424c332a038fb0eb181a4

Observation aed3f6a9-c627-446b-a196-33919dc51759 · outbound

This paper cites The hidden vulner- ability of distributed learning in Byzantium,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning The hidden vulner- ability of distributed learning in Byzantium,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.049993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:57.757035Z digest=sha256:994f9fc5a92c7b3b15d0d0931393ba47dd3addb01b68eea3e4fc8534309a9313

Observation dd049cb7-9c45-49e2-bf34-5a9a0e8122fd · outbound

This paper cites FABA: an algorithm for fast aggregation against Byzantine attacks in distributed neural networks,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning FABA: an algorithm for fast aggregation against Byzantine attacks in distributed neural networks,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.040191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:57.810904Z digest=sha256:6b2047ce5dd76a2c484d19a012214530d01c04a3f9dd4f2c96162c0b458b8bbe

Observation 2151e563-b5f5-4293-bf40-37429bd6bba6 · outbound

This paper cites Byzantine-robust dis- tributed learning: Towards optimal statistical rates,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Byzantine-robust dis- tributed learning: Towards optimal statistical rates,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.030304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:57.925576Z digest=sha256:c87d2dfdcb2c5cc100d57d65674640262c2f4ba0cf3e3e7f690b8a625ab65024

Observation 1741777a-8b67-4a0f-9d55-46b1ef1b3e4d · outbound

This paper cites Robust aggregation for federated learning,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Robust aggregation for federated learning,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.019714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:58.009559Z digest=sha256:dc82f739244ff8a5e0196852903b8be29ebc98af02105f71979b693d0955c938

Observation 3bf1e52e-eb09-4f63-a5f4-edb0e5e7cd4e · outbound

This paper cites DRACO: Byzantine-resilient distributed training via redundant gradients,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning DRACO: Byzantine-resilient distributed training via redundant gradients,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:03.009734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:58.121618Z digest=sha256:cf7e357bcff99ddeccf01d6ceef86881008903529072baedbcfacf675b724f92

Observation 27017c96-fb38-4e7b-becc-94ae02052161 · outbound

This paper cites DETOX: a redundancy-based framework for faster and more robust gradient aggregation,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning DETOX: a redundancy-based framework for faster and more robust gradient aggregation,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:02.998201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:58.279625Z digest=sha256:b591d324970c50ea290c8cfa1b89e7d76722b039996fa377a643b69669d4ad52

Observation 47004a6c-e9cf-426c-ab4a-a6fc8283e435 · outbound

This paper cites Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T20:10:58.404804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:10:58.404804Z digest=sha256:d80d481f4c36a237b862ba7d736dccddec775e2bc04cd5b1f40cbe67db149c68

Observation 03f665a7-8fae-4030-b12f-c9f7cd59254c · outbound

This paper cites Byzantine-robust learning on heterogeneous data via gradient splitting,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Byzantine-robust learning on heterogeneous data via gradient splitting,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:02.973694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:58.499102Z digest=sha256:86cb3f83210d4f3207e066d10268931348f9715e8b4bf895ad822678aa7d53e4

Observation 1be11789-7020-4fce-ae59-2a906597f22e · outbound

This paper cites Shielding federated learning: Robust aggregation with adaptive client selection,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Shielding federated learning: Robust aggregation with adaptive client selection,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:02.857707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:58.599805Z digest=sha256:db2738fae1b1f203b9ad75d178345ab8bcbca9c6d02cd300008e58dad89aabf9

Observation f28693af-3414-49bd-b57a-64526f69acc0 · outbound

This paper cites Learning from history for Byzantine robust optimization,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Learning from history for Byzantine robust optimization,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:02.606928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:58.689872Z digest=sha256:6d55848bc15809683188d7dfc3cde5d31ad575cdd5964a2d8f2bce73f20a20b7

Observation 6eca968e-da75-4a7c-ada7-91f14968c5cb · outbound

This paper cites RSA: Byzantine- robust stochastic aggregation methods for distributed learning from heterogeneous datasets,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning RSA: Byzantine- robust stochastic aggregation methods for distributed learning from heterogeneous datasets,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:02.277415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:58.830671Z digest=sha256:1df0e78a4e7db472c0776cb9577290c5a9e7dff08adb23b1e9b856578e34ddec

Observation b6d6fa56-ff21-4123-8966-abae3e3211ff · outbound

This paper cites Federated Two-stage Learning with Sign-based Voting.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Federated Two-stage Learning with Sign-based Voting

Reference 53

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:11:00.151557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:58.917613Z digest=sha256:049d8c9ff5675c606448e80a9eee219f4502c3636201b7c68edd0e6bb1c97822

Observation ded8ca80-560c-4d0f-aa92-45a267b3dcb7 · outbound

This paper cites Stochastic sign descent methods: New algorithms and better theory,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Stochastic sign descent methods: New algorithms and better theory,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:02.047980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:59.046534Z digest=sha256:d74b2b6cf007bfb095734780d7d5441136b7a3047d2e4fb9e63f080d205bfa0f

Observation 548a11e9-87af-45c0-b21d-8ec5d8af2ec5 · outbound

This paper cites Bridging differential privacy and Byzantine- robustness via model aggregation,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Bridging differential privacy and Byzantine- robustness via model aggregation,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:01.900715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:59.150706Z digest=sha256:7eb60c580d603d721c2e350b845b7300ca339f081d41a6b4207bcc75c207f7f2

Observation be129ca0-9510-4990-a1f2-76a5ff5eedd2 · outbound

This paper cites Federated learning with ℓ1 regularization,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Federated learning with ℓ1 regularization,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:01.745093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:59.266514Z digest=sha256:2450884c3b28fcec7331fa3b6122d418b672b07122c7c9f16f2705f53ec63440

Observation 4547000c-bd3b-4034-b740-f71d22e73986 · outbound

This paper cites Mag- nitude matters: Fixing signSGD through magnitude-aware sparsification and error feedback in the presence of data heterogeneity,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Mag- nitude matters: Fixing signSGD through magnitude-aware sparsification and error feedback in the presence of data heterogeneity,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:01.570083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:59.391233Z digest=sha256:54eb46701a5591c1e63bb0ddb4c96968296fbdbf8d73a93426c15c6bcb6d3e03

Observation 06249ae1-99a1-479b-ad62-1cbada1d15bd · outbound

This paper cites Rate distortion for model compression:From theory to practice,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Rate distortion for model compression:From theory to practice,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:01.384890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:59.514306Z digest=sha256:251af95823e2a5aa1280ebf90afbbc4a55d23eecec74d17a4143508dfc269a70

Observation 46bf3896-3c3a-408a-9c70-8f1b220a81be · outbound

This paper cites Deep learning with differential privacy,.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Deep learning with differential privacy,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:01.205254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:59.622025Z digest=sha256:5cff93bb2607ac5d1adb46d8a5b29f583ef4706cf760da56d64742ce194cee57

Observation cc8423fa-00f9-4a14-9847-4f7140634fe8 · outbound

This paper cites an unresolved cited work.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:11:01.029203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:59.751241Z digest=sha256:902383c4b809ebebd6bcb720bfb3958b641526875cf0a7474942785d03e3b3f5

Observation cf401d66-ee1a-4ec3-881f-34574705555c · outbound

This paper cites an unresolved cited work.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:11:00.884882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:59.853155Z digest=sha256:f56d4e0992c3c98ce9a6fc6c0a01a8e616361e4c61b381bdace130717482a0a9

Observation 5a9041d9-175a-4bd7-8f56-d6649638e360 · outbound

This paper cites 1 M 2 MX m=1 I {cm i = 1} + X i∈B I {zm i > cm i } − X i∈B I {zm i < cm i } ! − M ! bi #2 − θi 2 = E.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning 1 M 2 MX m=1 I {cm i = 1} + X i∈B I {zm i > cm i } − X i∈B I {zm i < cm i } ! − M ! bi #2 − θi 2 = E

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:11:00.724217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:10:59.966903Z digest=sha256:559129c73b4e048f63d003985bcdf29d8da93e3f3d62398a517e744f211dd984

Pith citing papers

No inbound Pith citation observations are available.