Paper Citation Record · LEDGER

MaxModShift: Model Privacy via Designed Shifts

As of 16 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2608.09328.

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

pith.paper-citation-record.v1
2608.09328 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:29:47.951014Z

measured 22 of 22 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

22 of 22 outbound references displayed

verified exact2
verified fuzzy16
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1d1329e3-621a-49a1-9c9a-101de6cb8438 · outbound

This paper cites Advances and open problems in federated learning,.

MaxModShift: Model Privacy via Designed Shifts Advances and open problems in federated learning,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.223569Z

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.

Observation b8388b5a-735b-4c54-81bd-8663100b9abf · outbound

This paper cites Pri vacy- preserving aggregation in federated learning: A survey,.

MaxModShift: Model Privacy via Designed Shifts Pri vacy- preserving aggregation in federated learning: A survey,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.213210Z

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.

Observation d944b24f-0e8a-44bd-b722-956b3aaaf54e · outbound

This paper cites Practical secure aggregation for privacy-preserving machine learning,.

MaxModShift: Model Privacy via Designed Shifts Practical secure aggregation for privacy-preserving machine learning,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.203835Z

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.

Observation a57b46e5-380e-4b43-a69b-f03471af9108 · outbound

This paper cites FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning.

MaxModShift: Model Privacy via Designed Shifts FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T19:29:47.896570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13c7b41c-b6cb-423f-8ddb-8e050a78373c · outbound

This paper cites Deep learning with differential pr ivacy,.

MaxModShift: Model Privacy via Designed Shifts Deep learning with differential pr ivacy,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T19:29:47.900050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1f8bd65-b2c2-43b1-b0d1-20363a793148 · outbound

This paper cites Ap prox- imating functions with approximate privacy for applicatio ns in signal estimation and learning,.

MaxModShift: Model Privacy via Designed Shifts Ap prox- imating functions with approximate privacy for applicatio ns in signal estimation and learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.185987Z

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.

Observation 16a8ad8d-9cc5-4b98-a951-eb3ba2be3e58 · outbound

This paper cites Privﬂ: Practical privacy-preser ving federated regressions on high-dimensional data over mobile networks ,.

MaxModShift: Model Privacy via Designed Shifts Privﬂ: Practical privacy-preser ving federated regressions on high-dimensional data over mobile networks ,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.175484Z

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.

Observation 993c310c-8e35-4fff-a1ee-9bad4e782b3e · outbound

This paper cites An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning.

MaxModShift: Model Privacy via Designed Shifts An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:29:48.007793Z

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.

Observation 456829d1-b446-4b04-bbc1-57aa3785848a · outbound

This paper cites On Model Protection in Federated Learning against Eavesdropping Attacks.

MaxModShift: Model Privacy via Designed Shifts On Model Protection in Federated Learning against Eavesdropping Attacks

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:29:47.988201Z

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.

Observation b915efcf-1dd1-4d77-aa2e-5cb13e1e19e6 · outbound

This paper cites Channel state information-free loc ation-privacy enhancement: Fake path injection,.

MaxModShift: Model Privacy via Designed Shifts Channel state information-free loc ation-privacy enhancement: Fake path injection,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.165770Z

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.

Observation 111e4847-a908-4dfc-844c-0b9e0b6ce6c2 · outbound

This paper cites Channel state information-free location-privac y enhancement: Delay-angle information spooﬁng,.

MaxModShift: Model Privacy via Designed Shifts Channel state information-free location-privac y enhancement: Delay-angle information spooﬁng,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.155053Z

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.

Observation 76383f90-8225-46b9-af27-4d659e5872d9 · outbound

This paper cites Optimized parameter design for channel state info rmation-free location spooﬁng,.

MaxModShift: Model Privacy via Designed Shifts Optimized parameter design for channel state info rmation-free location spooﬁng,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.142914Z

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.

Observation d7b69a9a-1caf-4882-a776-71b80e7bbde4 · outbound

This paper cites Modshift: Model privacy via designed shifts,.

MaxModShift: Model Privacy via Designed Shifts Modshift: Model privacy via designed shifts,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.129239Z

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.

Observation 560cd13a-4131-45d2-b5df-81245bab0482 · outbound

This paper cites Scaffold: Stochastic controlled averaging for fe derated learn- ing,.

MaxModShift: Model Privacy via Designed Shifts Scaffold: Stochastic controlled averaging for fe derated learn- ing,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.116303Z

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.

Observation d0c47881-dc44-4705-a4c5-3b5703bd2791 · outbound

This paper cites Feddc: F ederated learning with non-iid data via local drift decoupling and co rrection,.

MaxModShift: Model Privacy via Designed Shifts Feddc: F ederated learning with non-iid data via local drift decoupling and co rrection,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.103124Z

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.

Observation d1cdd4b7-0fe7-474c-a439-b0daaf1474b7 · outbound

This paper cites Block mo dshift: Model privacy via dynamic designed shifts,.

MaxModShift: Model Privacy via Designed Shifts Block mo dshift: Model privacy via dynamic designed shifts,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.089179Z

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.

Observation 0042fe49-ed14-4d44-a914-052c2cdf82e0 · outbound

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

MaxModShift: Model Privacy via Designed Shifts Communication-efﬁcient learning of deep networks from de centralized data,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T19:29:47.932714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad6ac38a-1980-4780-a5ad-4918265240f0 · outbound

This paper cites Maximal dissent: a state-dependent way to agree in distributed convex optimi zation,.

MaxModShift: Model Privacy via Designed Shifts Maximal dissent: a state-dependent way to agree in distributed convex optimi zation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.072767Z

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.

Observation c3a8085a-038e-495d-9746-806e08b9ce34 · outbound

This paper cites Goldsmith, Wireless communications.

MaxModShift: Model Privacy via Designed Shifts Goldsmith, Wireless communications

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T19:29:47.939141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffc608ad-154a-4e72-b10a-452d41acab55 · outbound

This paper cites Guaranteed private c ommunication with secret block structure,.

MaxModShift: Model Privacy via Designed Shifts Guaranteed private c ommunication with secret block structure,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.057030Z

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.

Observation be737e01-be24-449d-8dfd-b082258a1d7a · outbound

This paper cites Block modshift: Model priva cy via dynamic designed shifts,.

MaxModShift: Model Privacy via Designed Shifts Block modshift: Model priva cy via dynamic designed shifts,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.046382Z

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.

Observation 7d8e4347-b830-4185-b03a-f20eec44bd59 · outbound

This paper cites Gradient-based learning applied to document recognition,.

MaxModShift: Model Privacy via Designed Shifts Gradient-based learning applied to document recognition,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:29:48.034602Z

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.

Pith citing papers

No inbound Pith citation observations are available.