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Paper Citation Record · LEDGER

Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1909.05125.

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

pith.paper-citation-record.v1
1909.05125 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:02:01.865031Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T02:03:44.395929Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 58a16f11-b0fc-49db-8c89-47606245bed0 · inbound

Aggressive or Imperceptible, or Both: Network Pruning Assisted Hybrid Byzantines in Federated Learning cites this paper.

Aggressive or Imperceptible, or Both: Network Pruning Assisted Hybrid Byzantines in Federated Learning Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-24T02:03:44.399249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-24T02:01:08.959453Z digest=sha256:310558ad401ad9184e9d9bc46500d8ff74318faccb6a384f900eb48d28970605

Observation 0e8a345a-7903-411e-8ca1-24fc9a710214 · inbound

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) cites this paper.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-10T21:02:01.865031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:01.865031Z digest=sha256:92524a45bed87a9f4145cb14a5f25b7c420dbbcd583429b6c8e847ce6db3efe1

Observation 9328c595-1c1d-407f-8b0b-ab0aa7098d90 · inbound

SecureAFL: Secure Asynchronous Federated Learning cites this paper.

SecureAFL: Secure Asynchronous Federated Learning Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:08:01.673376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-13T16:55:09.736811Z digest=sha256:19e641374929c70f8881148974db255e24b082b15942373b2bebfb6b1a05aa9b

Observation 0022eb10-2b32-41d1-b402-33a1f36125f4 · inbound

AdaBFL: Multi-Layer Defensive Adaptive Aggregation for Bzantine-Robust Federated Learning cites this paper.

AdaBFL: Multi-Layer Defensive Adaptive Aggregation for Bzantine-Robust Federated Learning Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging

Reference 30

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T09:36:26.301635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-07T10:26:19.049908Z digest=sha256:629a431591de66ea0f7165f6ed3132f73c3e05ddf47ccfeea0b1984da6b0620d