Pith. sign in

Paper Citation Record · LEDGER

FL-TAC: Enhanced Fine-Tuning in Federated Learning via Low-Rank, Task-Specific Adapter Clustering

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.15384.

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

pith.paper-citation-record.v1
2404.15384 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:42:38.890182Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T05:37:34.073932Z

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 ad42d544-3981-4767-b31f-e5ad0b236c48 · inbound

Many-Task Federated Fine-Tuning via Unified Task Vectors cites this paper.

Many-Task Federated Fine-Tuning via Unified Task Vectors FL-TAC: Enhanced Fine-Tuning in Federated Learning via Low-Rank, Task-Specific Adapter Clustering

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-08T15:42:38.890182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:42:38.890182Z digest=sha256:1a60dfcba23db47e124dedacdf1ad03e098baff202e7a70020ff4fd8f027041c

Observation 10abb42e-1024-4fcf-9b58-830555fc7623 · inbound

Foundational Models and Federated Learning: Survey, Taxonomy, Challenges and Practical Insights cites this paper.

Foundational Models and Federated Learning: Survey, Taxonomy, Challenges and Practical Insights FL-TAC: Enhanced Fine-Tuning in Federated Learning via Low-Rank, Task-Specific Adapter Clustering

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-05T05:37:34.153328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T05:37:33.737099Z digest=sha256:6991b06426148c4c67105a330e8a8a3b8a0723967be390842655404223af539d