Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2502.15828.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T16:16:46.503937Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T07:14:20.871130Z
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 53ffc4f0-e91e-41b9-9488-948c7070777b · inbound
C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning cites this paper.
C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T16:16:46.503937Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 21831690-3225-4fa1-9258-8824e506373c · inbound
Breaking the MoE LLM Trilemma: Dynamic Expert Clustering with Structured Compression cites this paper.
Breaking the MoE LLM Trilemma: Dynamic Expert Clustering with Structured Compression A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T14:50:28.482094Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 77ba51de-7419-4fbe-83f5-1fe83658cee7 · inbound
Mixture of Debaters: Learn to Debate at Architectural Level in Multi-Agent Reasoning cites this paper.
Mixture of Debaters: Learn to Debate at Architectural Level in Multi-Agent Reasoning A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T07:14:20.872666Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.