Paper Citation Record · LEDGER

Towards Understanding Mixture of Experts in Deep Learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2208.02813.

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

pith.paper-citation-record.v1
2208.02813 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:13:02.743977Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T19:36:08.163611Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
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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 b2aead1a-686f-4bef-b60a-4c82803de10d · inbound

VFX Creator: Animated Visual Effect Generation with Controllable Diffusion Transformer cites this paper.

VFX Creator: Animated Visual Effect Generation with Controllable Diffusion Transformer Towards Understanding Mixture of Experts in Deep Learning

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-08T17:13:02.743977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50a5a8e0-a97b-4e2c-af88-19c7f2c80bcb · inbound

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification cites this paper.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Towards Understanding Mixture of Experts in Deep Learning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:37.984923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb090b1d-ddd2-4263-8c74-04afbf69eb38 · inbound

Atmos-Bench: 3D Atmospheric Structures for Climate Insight cites this paper.

Atmos-Bench: 3D Atmospheric Structures for Climate Insight Towards Understanding Mixture of Experts in Deep Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T17:24:37.610539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 515910ae-dcb0-4d52-8f41-d2362af4efa9 · inbound

STM3: Mixture of Multiscale Mamba for Long-Term Spatio-Temporal Time-Series Prediction cites this paper.

STM3: Mixture of Multiscale Mamba for Long-Term Spatio-Temporal Time-Series Prediction Towards Understanding Mixture of Experts in Deep Learning

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:20:42.179391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3dd1f49b-42ac-4c70-b9bb-6950b0a6343c · inbound

STM3: Mixture of Multiscale Mamba for Long-Term Spatio-Temporal Time-Series Prediction cites this paper.

STM3: Mixture of Multiscale Mamba for Long-Term Spatio-Temporal Time-Series Prediction Towards Understanding Mixture of Experts in Deep Learning

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-25T07:36:41.900770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d02b1cad-4cec-4d16-803b-a652511949b5 · inbound

STK-Adapter: Incorporating Evolving Graph and Event Chain for Temporal Knowledge Graph Extrapolation cites this paper.

STK-Adapter: Incorporating Evolving Graph and Event Chain for Temporal Knowledge Graph Extrapolation Towards Understanding Mixture of Experts in Deep Learning

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:51:07.034934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 38429a2b-8ddf-46d2-a76d-dd331509da39 · inbound

How to Scale Mixture-of-Experts: From muP to the Maximally Scale-Stable Parameterization cites this paper.

How to Scale Mixture-of-Experts: From muP to the Maximally Scale-Stable Parameterization Towards Understanding Mixture of Experts in Deep Learning

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-15T04:49:44.821123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7b84bc13-3f97-4948-b698-472b96f180e8 · inbound

Geometric Asymmetry in MoE Specialization: Functional Decorrelation and Representational Overlap cites this paper.

Geometric Asymmetry in MoE Specialization: Functional Decorrelation and Representational Overlap Towards Understanding Mixture of Experts in Deep Learning

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-20T23:49:15.442108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f96388ab-840a-4290-846f-58a283fcd265 · inbound

CoX-MoE: Coalesced Expert Execution for High-Throughput MoE Inference with AMX-Enabled CPU-GPU Co-Execution cites this paper.

CoX-MoE: Coalesced Expert Execution for High-Throughput MoE Inference with AMX-Enabled CPU-GPU Co-Execution Towards Understanding Mixture of Experts in Deep Learning

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:08:15.407771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1c7e8d21-81e6-48d4-9b4f-a4de7080011a · inbound

MoG: Mixture of Experts for Graph-based Retrieval-Augmented Generation cites this paper.

MoG: Mixture of Experts for Graph-based Retrieval-Augmented Generation Towards Understanding Mixture of Experts in Deep Learning

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-01T19:36:08.165151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.