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Paper Citation Record · LEDGER

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

As of 15 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 2026-08-15T06:32:42.880941+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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:54.533861Z digest=sha256:02d1ba616c89542864b27b6874bcb677bae9b2366e54925b41098fe927afd166

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:54.595568Z digest=sha256:4a91657f948338c8a6826567e4e24fa83d4e59abe2e913f438594a5e4a144d3d

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:54.692592Z digest=sha256:8ff818efea562f04c89189b92c25aea6a2bbec5c5e2df5ca54f9a51b976225ab

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:54.787154Z digest=sha256:891cf862876b81814890e15f900d95c424d6306b097e014cc794bc12c2fc3d10

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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raw_fallback, observed 2026-08-06T20:11:03.413512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:54.878740Z digest=sha256:5c0a178a93a9d96da0683421ed6d61bfc5065dfc295250184a2275fed8464f3e

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:54.949577Z digest=sha256:dec30bda35c76da2b41006e5168fcceafe0060f9d0250bf2cf6b5103658635db

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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:55.021949Z digest=sha256:fdc7ced55ba23fa0801183eeb978a3718e194917527e7173b699b77b4b679fe1

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

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:55.088839Z digest=sha256:d71459082685bc55fda07b6163767a0ff223de0ed347333f13eb15e8414dd29b

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

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:55.169911Z digest=sha256:1196aeefee2756646fbe36827ecb1411217dbcc2d5748540babbd2b95c186826

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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:55.247820Z digest=sha256:c9900dda580fb571332e5d0e9c446666a1e046703f94f8c9443e98c1d3aa3a91

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:10:55.322851Z digest=sha256:8af981a3bff53e55025a5681ae36f1d8589ed7b7e757a0e1b4d7ad908516dd76

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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:55.368968Z digest=sha256:c1c5bbcf3e50e1078a601c801a8749d26902c303257581a0f4f6e9eb66488bab

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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:55.433398Z digest=sha256:de2546a02ada3c66fb211b5ae2cc7d88897ee2c50a33dfd4dc0cd9c6d4bd2b1f

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:55.503624Z digest=sha256:366a94c8223d08680a815ea9f38be37ccc6c4e0d04fdf69c488a6f8367aabc63

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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raw_fallback, observed 2026-08-06T20:11:03.295547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:55.583144Z digest=sha256:a591b00cb4097d0ff9fe1b7defc7f240e12a2381aa2fd7174a216b9b9f566b4e

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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:55.662322Z digest=sha256:2c4403301e43eb84327d1c6c27b75a48f7092f7f3b9347923e1568aa94040c09

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:10:55.711188Z digest=sha256:57e6f409eac63a920cae11b463d4aee087d8d6d5f092f41ebc06f17659da6479

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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:55.752847Z digest=sha256:ead71d9f59adefce9817c559c41ea8fc80aef4c599a8c1bf8f6f2ce8c9490915

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:55.820749Z digest=sha256:4f6c75f610fa5db740f0c4609bb548d3dac5210a9268573f4a488747322867dc

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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raw_fallback, observed 2026-08-06T20:11:03.251113Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:55.870023Z digest=sha256:870eb1fa49edbea74e4abf5b357204484743d48094b7ff529aedabaf067e0a9f

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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raw_fallback, observed 2026-08-06T20:11:03.240298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:55.943030Z digest=sha256:85103218aa310de469b12603904664b7529041183f2b9075dd42a57e070c9ebf

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:56.008461Z digest=sha256:950e88773f79fe16f41e9848e8c915e7f1083b45cac6d33a895e93e3806a0101

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:10:56.075810Z digest=sha256:a26e854f364f352eeca76e4b8a5cf643f3a33b7c244676c19bbc3d5a2f8088f3

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:56.129715Z digest=sha256:b73ee2d9a493eacc7c26d55f1514793eaad36d26b6f55d27581a7680fd421bc3

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:56.170429Z digest=sha256:79f57fbdb1ded9eba047c6f9ffbcf34279c7b5c2b228d5bed4be38dc8d4a27cf

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:56.252726Z digest=sha256:d5b82bcb8ded2015e61538c295dea8f2e6364eb61302f798c63e3615f6201477

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:56.341387Z digest=sha256:138d6fc14713c25d52ab54cba6ff8e6a9a2c2025f50aaaca94f7d881393f7408

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:56.393617Z digest=sha256:e0cb9ccc5d8cee6f7fce589f87a47a6d0239e293b08fed4750f7e50411ca185f

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:56.485358Z digest=sha256:8d36f2b16963f3fcc23621f39423f8aa87d53f13b8512b15ca51a907bb8e5ee1

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:56.573116Z digest=sha256:fd8fbfa7cd437c48acdb2756b8a2b9ff94c10ec7c778943b0ee53f064047a811

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:56.656474Z digest=sha256:533c6953eeba499f49ac667845955d394386e8fc23835bf3316ff2835414dad6

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

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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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:56.770901Z digest=sha256:a03c5252204adc78c1847ddb3c988b080bd6b5e4cf89d16c4757984292cce1bc

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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unresolved
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=sha256:8b5561f42418e6209b6673674a83d766d576ffedfbdf82b466409ac72ae2962c

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:56.974900Z digest=sha256:18e7ddac2d8073392b48010e162eeb3ed112e2d0aef03bb2b07573502dd7e906

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:57.058426Z digest=sha256:c2ea9736e1f5412b6fccaa17480b232d67eba610026e5a38de11d7714bfc878d

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:57.110423Z digest=sha256:809d9cbee95b32f837bc16ee15afcfbbddc967993b92c886f2f5b9acafbd82aa

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=sha256:3e874027fb2ac4ec6db8c16d3e6a829d432bb9c08aa906c956a7600c9bae3c8b

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:57.298586Z digest=sha256:2a9cf41fccbd7c4c662a85fb57ec24f3478bb2cc59cede5facb0cff960b43646

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:f660d50fb7af3f3efda4d7c7ae9f9735f0734260034cdcf7d35125d68a86c949

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:57.530261Z digest=sha256:62abfbcd14da0be2272271fad962c4c75eb6847c64e6e5dd2acb9ac2a596914f

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:57.637789Z digest=sha256:426d4bd878199f8b3d110bfc7cf000f83bbcc6a897c34344431117d1c9df1ad5

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:57.757035Z digest=sha256:84056ec46469a498c2bc87662ea13d958f4890656b7f14a90becb9adc466296d

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:57.810904Z digest=sha256:79224e053bd757c5e22cbd313d0c815c04bd962120feebd6c5caeb0069b7f150

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:57.925576Z digest=sha256:f971e7c1369f283e3f3c5f05f517089e633bea595adeb13540baf90926d5ddd2

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:58.009559Z digest=sha256:66aafc332da4a8b37e6e133228258a0bbb8fb0db12ca15111bd8daf40eb484fa

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:58.121618Z digest=sha256:bbeb7d2dfd32d1479acca97cb1f78078acccafb7bf73e55bce185b4bc7367300

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:58.279625Z digest=sha256:745539f10149167f0f33a142255f60c052289c497c9a58f4e9bf2d6c43c1eb6f

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=sha256:0f67ca21f534a01f68f9aa516cd6a21ab3746998d7d1b220ebf2cd7d8a171a44

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:58.499102Z digest=sha256:3d2eaefc9f9d5d7f938a91cbda9c20f11c55b2580d2c08dfb8d43fd199efebfb

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:58.599805Z digest=sha256:38dffa83614192887cd7e4e161fd83bbcc85e70cbd9d766f6d63872496052ece

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:58.689872Z digest=sha256:68e5dbcc578769227bb016ada613eeb071742492cf5a7e75a1d639fd58f6f214

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:58.830671Z digest=sha256:b3f0482e6799b2ae89701f4236aa2cec6d168d5928fedc0e4659d095307b6945

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:58.917613Z digest=sha256:0c3626dd557f6ad981544d9da0506e99d2b157d08a5a5573bc5d7d2b4e9152dd

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:59.046534Z digest=sha256:0af86f9323999fe103be8d05989a16e071bbc745ffff6a7bddc191ad0c392927

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:59.150706Z digest=sha256:92dd14bbaf48c1d8157eae335af5f69c3cab419e7f9d76ee523bfd8e9f29906b

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:59.266514Z digest=sha256:6bfc558eddd77ef53a0523a7c40d373e228d2b46229d8792b35b3a8de65ad798

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:59.391233Z digest=sha256:0102e1446f9fc66e6b257c641770eff8014d722988ec5310229fa281845bacee

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:59.514306Z digest=sha256:a6c25db9f833c3b240a96ae5ec295df636d9f6dfc6fadf71749272a5af0be54b

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:59.622025Z digest=sha256:9e97b0a8efcda9dd982ea2256470fa92ba0f7c269bd7627aaf338c74df1f32b2

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:59.751241Z digest=sha256:a9286121451a11b4e13a5bcb6c615ceb045bb109e4a569d33c372b13df9ff950

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:59.853155Z digest=sha256:eac2f9b80c08a7392c6f5491246a1886c23018f446e6a59a4c5b1c2483d05450

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T20:10:59.966903Z digest=sha256:a2b8d6d6b90a67550cbf1915c0c9427e704eb52c21bf2851ecbc17f544fdc22c

Pith citing papers

No inbound Pith citation observations are available.