Paper Citation Record · LEDGER

Personalized Wireless Federated Learning for Large Language Models

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2404.13238.

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

pith.paper-citation-record.v1
2404.13238 v2

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 2026-08-15T23:50:24.531388Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T19:57:25.767960Z

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 bd07602f-c9dc-4536-9bd0-33f4531c6acc · inbound

Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions cites this paper.

Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions Personalized Wireless Federated Learning for Large Language Models

Reference 285

Resolution: unresolved; no resolver link, observed 2026-08-10T21:37:05.507024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbe248c7-2c22-4f51-846c-102073c7288b · inbound

Empowering Large Language Models in Wireless Communication: A Novel Dataset and Fine-Tuning Framework cites this paper.

Empowering Large Language Models in Wireless Communication: A Novel Dataset and Fine-Tuning Framework Personalized Wireless Federated Learning for Large Language Models

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-10T19:57:25.773855Z

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.

Observation 60256ae1-dd53-4e7e-b0b8-cde68d287445 · inbound

A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges cites this paper.

A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges Personalized Wireless Federated Learning for Large Language Models

Reference 113

Resolution: unresolved; no resolver link, observed 2026-08-15T23:50:24.531388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed960da9-36bb-4363-9f05-4038fbdc2d48 · inbound

Federated Large Language Models: Feasibility, Robustness, Security and Future Directions cites this paper.

Federated Large Language Models: Feasibility, Robustness, Security and Future Directions Personalized Wireless Federated Learning for Large Language Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T22:03:18.937163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.