Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2501.15103.
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 2026-08-04T17:57:25.245487Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T19:57:19.019883Z
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 cf65be58-0a90-4f4b-a38d-d32fbfe1f93c · inbound
Dropping Experts, Recombining Neurons: Retraining-Free Pruning for Sparse Mixture-of-Experts LLMs cites this paper.
Dropping Experts, Recombining Neurons: Retraining-Free Pruning for Sparse Mixture-of-Experts LLMs Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T17:57:25.245487Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation db05630d-57f8-4472-8431-ac7392949e70 · inbound
Train Large, Deploy Compact: Structured Compression for Compact Low-Rank Adaptation cites this paper.
Train Large, Deploy Compact: Structured Compression for Compact Low-Rank Adaptation Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning
Reference 96
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T13:31:06.541083Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f4bd96ab-002e-4018-8795-a3c4cc2b2faf · inbound
DAG-MoE: From Simple Mixture to Structural Aggregation in Mixture-of-Experts cites this paper.
DAG-MoE: From Simple Mixture to Structural Aggregation in Mixture-of-Experts Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning
Reference 2
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-01T21:16:14.381989Z
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.
Observation 917a3134-5e4c-404a-8579-451135f9c617 · inbound
Clinically Structured Rank-Gated LoRA for Cross-Benchmark Medical Question Answering cites this paper.
Clinically Structured Rank-Gated LoRA for Cross-Benchmark Medical Question Answering Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T10:05:40.984015Z
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.
Observation 2374fd49-aa79-4004-8a4f-1fb9dd61cd72 · inbound
Clinically Structured Rank-Gated LoRA for Cross-Benchmark Medical Question Answering cites this paper.
Clinically Structured Rank-Gated LoRA for Cross-Benchmark Medical Question Answering Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T19:57:19.021556Z
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.