Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.10054.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T06:00:51.852982Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T09:01:24.487604Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 744d6b0b-ed8c-4240-ab1c-b2f5e709fced · inbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias AlphaLoRA: Assigning LoRA Experts Based on Layer Training Quality
Reference 44
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 07055b55-1e84-4520-9110-fa594d18c30a · inbound
Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization AlphaLoRA: Assigning LoRA Experts Based on Layer Training Quality
Reference 15
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7cfc5459-c9d0-4868-a2fd-766ee5d4818d · inbound
Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization AlphaLoRA: Assigning LoRA Experts Based on Layer Training Quality
Reference 15
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bd5bbfdb-8dd0-4ca3-b2fa-60bf512d4182 · inbound
Adaptive and Fine-grained Module-wise Expert Pruning for Efficient LoRA-MoE Fine-Tuning AlphaLoRA: Assigning LoRA Experts Based on Layer Training Quality
Reference 10
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.