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Paper Citation Record · LEDGER

Wasserstein Barycenter-based Model Fusion and Linear Mode Connectivity of Neural Networks

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2210.06671.

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

pith.paper-citation-record.v1
2210.06671 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:56:29.986325Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T07:01:11.752794Z

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 d9a3416a-9131-4dbf-98ad-2b60279ea504 · inbound

Heterogeneous Federated Reinforcement Learning Using Wasserstein Barycenters cites this paper.

Heterogeneous Federated Reinforcement Learning Using Wasserstein Barycenters Wasserstein Barycenter-based Model Fusion and Linear Mode Connectivity of Neural Networks

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T23:56:29.986325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:56:29.986325Z digest=sha256:0e0a26ec13dccb162de463e3759afee7cb05b393c84fe30320f33df014f4186a

Observation 551a1d87-ca75-4e99-b823-f552c70bc379 · inbound

Robustness and Regularization in Hierarchical Re-Basin cites this paper.

Robustness and Regularization in Hierarchical Re-Basin Wasserstein Barycenter-based Model Fusion and Linear Mode Connectivity of Neural Networks

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-21T20:34:20.861641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T20:34:15.461619Z digest=sha256:105487ab38fd251669ccf60a1b6b1852380ecb7e90e6e5b60db35f95b0f9c72b

Observation f66785f6-5b0e-45cb-9e1c-0cd3d23d9024 · inbound

Partial Fusion of Neural Networks: Efficient Tradeoffs Between Ensembles and Weight Aggregation cites this paper.

Partial Fusion of Neural Networks: Efficient Tradeoffs Between Ensembles and Weight Aggregation Wasserstein Barycenter-based Model Fusion and Linear Mode Connectivity of Neural Networks

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-22T07:01:11.756594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-22T06:59:09.799156Z digest=sha256:45c773f572c9e31f8d8572363260a3328426d9ea1d9ab2f0d0ebc34f8368e6f0