Paper Citation Record · LEDGER

Hash Layers For Large Sparse Models

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2106.04426.

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

pith.paper-citation-record.v1
2106.04426 v3

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 2026-08-20T06:33:59.587034+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:38:42.014505Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T12:53:28.548600Z

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 f6e2fbd0-25a1-447a-bb5d-5012cb73d76c · inbound

ST-MoE: Designing Stable and Transferable Sparse Expert Models cites this paper.

ST-MoE: Designing Stable and Transferable Sparse Expert Models Hash Layers For Large Sparse Models

Reference 190

Resolution: verified exact; arxiv_id, observed 2026-05-12T23:14:25.780881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0c03582e-169a-4c8f-a68c-330302a48b8d · inbound

DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models cites this paper.

DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models Hash Layers For Large Sparse Models

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:50:12.905631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e52a3f5d-5c7d-4d63-b82d-710d619f4813 · inbound

Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask Learning cites this paper.

Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask Learning Hash Layers For Large Sparse Models

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-11T13:38:42.014505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cbfbd0f-6751-4f47-a2b2-d373c6134c0e · inbound

MoASE++: Mixture of Activation Sparsity Experts with Domain-Adaptive On-policy Distillation for Continual Test Time Adaptation cites this paper.

MoASE++: Mixture of Activation Sparsity Experts with Domain-Adaptive On-policy Distillation for Continual Test Time Adaptation Hash Layers For Large Sparse Models

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:53:28.551354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.