Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Exploring Gradient Subspaces: Addressing and Overcoming LoRA's Limitations in Federated Fine-Tuning of Large Language Models
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.23111.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T20:35:03.831568Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T09:19:42.893014Z
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 d9b5e249-9d6f-47af-91cc-0f5eb366fd72 · inbound
Continual Gradient Low-Rank Projection Fine-Tuning for LLMs cites this paper.
Continual Gradient Low-Rank Projection Fine-Tuning for LLMs Exploring Gradient Subspaces: Addressing and Overcoming LoRA's Limitations in Federated Fine-Tuning of Large Language Models
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:35:03.831568Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cb778588-41c1-42ce-b032-30d2cde1ac15 · inbound
An Efficient Subspace Algorithm for Federated Learning on Heterogeneous Data cites this paper.
An Efficient Subspace Algorithm for Federated Learning on Heterogeneous Data Exploring Gradient Subspaces: Addressing and Overcoming LoRA's Limitations in Federated Fine-Tuning of Large Language Models
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T05:38:50.097225Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6a4ebc3d-d36d-41fa-b1ec-502992f717ee · inbound
Subspace-Constrained Federated Learning with Low-Rank Adaptation cites this paper.
Subspace-Constrained Federated Learning with Low-Rank Adaptation Exploring Gradient Subspaces: Addressing and Overcoming LoRA's Limitations in Federated Fine-Tuning of Large Language Models
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T09:19:42.894525Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.