Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
HLoRA: Efficient Federated Learning System for LLM Heterogeneous Fine-Tuning
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2503.00813.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T21:51:05.475899Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T09:26:25.192572Z
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 42adfbcd-c257-4b93-82c0-dbbe7d50c522 · inbound
MoE-Compression: How the Compression Error of Experts Affects the Inference Accuracy of MoE Model? cites this paper.
MoE-Compression: How the Compression Error of Experts Affects the Inference Accuracy of MoE Model? HLoRA: Efficient Federated Learning System for LLM Heterogeneous Fine-Tuning
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T21:51:05.475899Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14b63ca3-cd7b-4d08-96d2-9bb4456882da · inbound
SplitFT: An Adaptive Federated Split Learning System For LLMs Fine-Tuning cites this paper.
SplitFT: An Adaptive Federated Split Learning System For LLMs Fine-Tuning HLoRA: Efficient Federated Learning System for LLM Heterogeneous Fine-Tuning
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T09:26:25.194531Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 60993abc-fadd-4691-8708-99f58250551e · inbound
EdgeFlowerTune: Evaluating Federated LLM Fine-Tuning Under Realistic Edge System Constraints cites this paper.
EdgeFlowerTune: Evaluating Federated LLM Fine-Tuning Under Realistic Edge System Constraints HLoRA: Efficient Federated Learning System for LLM Heterogeneous Fine-Tuning
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T08:31:24.484550Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.