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Paper Citation Record · LEDGER

LIBMoE: A Library for comprehensive benchmarking Mixture of Experts in Large Language Models

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.00918.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.00918 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:44:35.818816Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T21:52:09.932810Z

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 1263e767-35da-47e3-a47c-f439cabafcd6 · inbound

A Survey on Inference Optimization Techniques for Mixture of Experts Models cites this paper.

A Survey on Inference Optimization Techniques for Mixture of Experts Models LIBMoE: A Library for comprehensive benchmarking Mixture of Experts in Large Language Models

Reference 122

Resolution
unresolved
no resolver link, observed 2026-08-11T12:44:35.818816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:44:35.818816Z digest=sha256:36a1c8cefbecf1156c314239cd35aa61ea35c49c77f29bd0eda55a2df25bac7d

Observation 251c96d4-4a0f-4673-b87a-39a89bf6e3bd · inbound

Sub-MoE: Efficient Mixture-of-Expert LLMs Compression via Subspace Expert Merging cites this paper.

Sub-MoE: Efficient Mixture-of-Expert LLMs Compression via Subspace Expert Merging LIBMoE: A Library for comprehensive benchmarking Mixture of Experts in Large Language Models

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:52:09.978004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-06T21:52:06.379550Z digest=sha256:1bd6b40b910c036b7d39df8024641accba2dd7599063616cae092ebf05aa0f37