Paper Citation Record · LEDGER

SpeechMoE: Scaling to Large Acoustic Models with Dynamic Routing Mixture of Experts

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2105.03036.

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

pith.paper-citation-record.v1
2105.03036 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:05:55.285944Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T05:21:30.028684Z

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 3c0f0013-3795-4faa-acdd-7e56b87e99e7 · inbound

FSMoE: A Flexible and Scalable Training System for Sparse Mixture-of-Experts Models cites this paper.

FSMoE: A Flexible and Scalable Training System for Sparse Mixture-of-Experts Models SpeechMoE: Scaling to Large Acoustic Models with Dynamic Routing Mixture of Experts

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T19:05:55.285944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc2b7f1a-0b9a-425a-a8a9-b788e2943258 · 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 SpeechMoE: Scaling to Large Acoustic Models with Dynamic Routing Mixture of Experts

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-09T19:40:10.112733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3ecaf77-01ec-481a-a198-454c9cd959a0 · inbound

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs cites this paper.

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs SpeechMoE: Scaling to Large Acoustic Models with Dynamic Routing Mixture of Experts

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:31:18.498408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f9bae3c0-02f2-49bb-9929-86df285f1c07 · inbound

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs cites this paper.

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs SpeechMoE: Scaling to Large Acoustic Models with Dynamic Routing Mixture of Experts

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:21:30.031654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.