Paper Citation Record · LEDGER

pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2405.04146.

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

pith.paper-citation-record.v1
2405.04146 v3

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 2026-08-16T06:30:59.297886+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:51:45.356563Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:07:09.151686Z

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 4ae8ccbb-6a94-4ce4-b5d3-59343755c549 · inbound

A Hybrid Swarm Intelligence Approach for Optimizing Multimodal Large Language Models Deployment in Edge-Cloud-based Federated Learning Environments cites this paper.

A Hybrid Swarm Intelligence Approach for Optimizing Multimodal Large Language Models Deployment in Edge-Cloud-based Federated Learning Environments pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving

Reference 4479

Resolution: unresolved; no resolver link, observed 2026-08-09T13:56:15.713427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 399addf8-2fae-4913-83ac-fe951aa8d4c1 · inbound

FedEMA: Federated Exponential Moving Averaging with Negative Entropy Regularizer in Autonomous Driving cites this paper.

FedEMA: Federated Exponential Moving Averaging with Negative Entropy Regularizer in Autonomous Driving pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:45.356563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c36c265-b258-445a-b7f6-b42bd504d278 · inbound

FedSaaS: Class-Consistency Federated Semantic Segmentation via Global Prototype Supervision and Local Adversarial Harmonization cites this paper.

FedSaaS: Class-Consistency Federated Semantic Segmentation via Global Prototype Supervision and Local Adversarial Harmonization pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T21:39:35.523520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1edad89-0f14-4fa3-8c0c-14960465fa9b · inbound

Federated Foundation Models over Vehicular Networks cites this paper.

Federated Foundation Models over Vehicular Networks pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:07:09.153222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.