Paper Citation Record · LEDGER

On the Representation Collapse of Sparse Mixture of Experts

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2204.09179.

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

pith.paper-citation-record.v1
2204.09179 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 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:22:10.778037Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T17:13:13.982257Z

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 0a1cbc44-3106-48d0-85a1-a9eaeac23c38 · inbound

Condense, Don't Just Prune: Enhancing Efficiency and Performance in MoE Layer Pruning cites this paper.

Condense, Don't Just Prune: Enhancing Efficiency and Performance in MoE Layer Pruning On the Representation Collapse of Sparse Mixture of Experts

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-23T17:13:13.984927Z

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 9d36e823-d708-4683-b279-341b2a2b74e0 · inbound

TabICL: A Tabular Foundation Model for In-Context Learning on Large Data cites this paper.

TabICL: A Tabular Foundation Model for In-Context Learning on Large Data On the Representation Collapse of Sparse Mixture of Experts

Reference 90

Resolution: verified exact; arxiv_id, observed 2026-05-20T13:35:02.398877Z

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 191d71a8-475c-41c1-b5bb-1269cba7e060 · inbound

Neural Inhibition Improves Dynamic Routing and Mixture of Experts cites this paper.

Neural Inhibition Improves Dynamic Routing and Mixture of Experts On the Representation Collapse of Sparse Mixture of Experts

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T20:22:10.778037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72a97b4e-45d4-4f57-9c86-86ca5b7edabe · inbound

Routers Learn the Geometry of Their Experts: Geometric Coupling in Sparse Mixture-of-Experts cites this paper.

Routers Learn the Geometry of Their Experts: Geometric Coupling in Sparse Mixture-of-Experts On the Representation Collapse of Sparse Mixture of Experts

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:27:18.838062Z

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.