Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MoE$^2$: Optimizing Collaborative Inference for Edge Large Language Models
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2501.09410.
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 2026-08-06T21:36:34.326476Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T01:05:16.477250Z
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 b1aebb35-e76a-415e-8470-1548c2eb8a77 · inbound
Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices cites this paper.
Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices MoE$^2$: Optimizing Collaborative Inference for Edge Large Language Models
Reference 76
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T01:05:16.479630Z
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 ce0e1d10-43db-43c2-9978-882172760e83 · inbound
Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead cites this paper.
Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead MoE$^2$: Optimizing Collaborative Inference for Edge Large Language Models
Reference 152
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:36:34.326476Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 70db2372-76c3-471d-830d-f75024a99334 · inbound
Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges cites this paper.
Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges MoE$^2$: Optimizing Collaborative Inference for Edge Large Language Models
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:06:47.875762Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.