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Paper Citation Record · LEDGER

Multi-Head Mixture-of-Experts

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2404.15045.

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

pith.paper-citation-record.v1
2404.15045 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:13:36.734762Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T19:40:10.166134Z

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 75637d93-5dd6-4d99-9a52-a2304ee1efc5 · inbound

Mixture of Hidden-Dimensions Transformer cites this paper.

Mixture of Hidden-Dimensions Transformer Multi-Head Mixture-of-Experts

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-11T20:38:23.718220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:38:23.718220Z digest=sha256:c495589469128bfe4a798dc01ebf59d3e299f977f45306d3c58644729d695a10

Observation b7ead2e0-1f47-4a5a-85c3-84b807d4c1ac · inbound

BLR-MoE: Boosted Language-Routing Mixture of Experts for Domain-Robust Multilingual E2E ASR cites this paper.

BLR-MoE: Boosted Language-Routing Mixture of Experts for Domain-Robust Multilingual E2E ASR Multi-Head Mixture-of-Experts

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-10T17:05:15.628787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:05:15.628787Z digest=sha256:e6a0e85f172d3af8cd4e77341c24afeaef22eb016014463ec4a2d9f513b4505b

Observation c3634cfe-a1da-4145-8e5b-9497b9a3bee3 · inbound

MolGraph-xLSTM: A graph-based dual-level xLSTM framework with multi-head mixture-of-experts for enhanced molecular representation and interpretability cites this paper.

MolGraph-xLSTM: A graph-based dual-level xLSTM framework with multi-head mixture-of-experts for enhanced molecular representation and interpretability Multi-Head Mixture-of-Experts

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-09T23:33:20.492346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T23:33:20.492346Z digest=sha256:d939c9e383e7f01baf9b6ea7bbb4ea0f0b67e3f384894927bb9833a3eee6cc69

Observation 1c69072e-898a-4f23-bf1b-49ea75647eba · inbound

Sigmoid Self-Attention has Lower Sample Complexity than Softmax Self-Attention: A Mixture-of-Experts Perspective cites this paper.

Sigmoid Self-Attention has Lower Sample Complexity than Softmax Self-Attention: A Mixture-of-Experts Perspective Multi-Head Mixture-of-Experts

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-08-09T19:40:10.171584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T19:40:10.104099Z digest=sha256:4458624127e1ddf844fd1c0a427ea857f4c4a64581edefa4fad41c3b7060fd30

Observation 9499ad40-770f-49ae-a774-ee24fec84991 · inbound

EfficientLLM: Efficiency in Large Language Models cites this paper.

EfficientLLM: Efficiency in Large Language Models Multi-Head Mixture-of-Experts

Reference 157

Resolution
unresolved
no resolver link, observed 2026-08-15T20:13:36.734762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:13:36.734762Z digest=sha256:708f374b57d363150e72e8fd8ab46272993a001951b389399de0335e20408bd2