Paper Citation Record · LEDGER

EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2112.14397.

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

pith.paper-citation-record.v1
2112.14397 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:30:35.382095Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:59:33.788512Z

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 70e48860-b676-4071-bf22-be765ed05106 · inbound

TCSinger 2: Customizable Multilingual Zero-shot Singing Voice Synthesis cites this paper.

TCSinger 2: Customizable Multilingual Zero-shot Singing Voice Synthesis EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T15:30:35.382095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ccc9126-c31e-4147-9308-8ef32a0b2326 · inbound

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts cites this paper.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-05T14:43:01.896670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d9dfd16-b263-4123-9d1c-1713bb2336e5 · inbound

Universal Pansharpening Model cites this paper.

Universal Pansharpening Model EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.543093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d34bc577-a63e-4b10-b7f9-134f5e756dcb · inbound

When Does Sparse MoE Help in Vision? The Role of Backbone Compute Leverage in Sparse Routing cites this paper.

When Does Sparse MoE Help in Vision? The Role of Backbone Compute Leverage in Sparse Routing EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:22:39.632480Z

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 ee7739e0-3a6f-49fe-b42a-43aa2588393d · inbound

Towards Generalization-Oriented Models for Vehicle Routing Problems with Mixture-of-Experts cites this paper.

Towards Generalization-Oriented Models for Vehicle Routing Problems with Mixture-of-Experts EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T19:53:55.836016Z

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 5ad68858-9593-447d-85c7-15058f7d9846 · inbound

Toward Calibrated Mixture-of-Experts Under Distribution Shift cites this paper.

Toward Calibrated Mixture-of-Experts Under Distribution Shift EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:59:33.790375Z

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.