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Paper Citation Record · LEDGER

Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2310.01334.

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

pith.paper-citation-record.v1
2310.01334 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:52:07.528858Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T11:36:55.530752Z

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 dd981604-a46f-48da-9f9a-c38957b7304a · inbound

Lynx: Enabling Efficient MoE Inference through Dynamic Batch-Aware Expert Selection cites this paper.

Lynx: Enabling Efficient MoE Inference through Dynamic Batch-Aware Expert Selection Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-23T17:05:42.971649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T17:04:13.905401Z digest=sha256:86a05ec6d641e0c2f2f941b4abb5658972ed63edf2ee78af44266833b7396d1f

Observation 6d5107b5-56e6-41e1-b2cd-ef4883e8de01 · inbound

MoETuner: Optimized Mixture of Expert Serving with Balanced Expert Placement and Token Routing cites this paper.

MoETuner: Optimized Mixture of Expert Serving with Balanced Expert Placement and Token Routing Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-08T14:52:07.528858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T14:52:07.528858Z digest=sha256:fa881f12633be4525cb0b2addfdcb4582157278fa9bd925af461410649f0c2f5

Observation 1d054ccb-b942-499f-a29d-6e18b595ffc3 · inbound

Dropping Experts, Recombining Neurons: Retraining-Free Pruning for Sparse Mixture-of-Experts LLMs cites this paper.

Dropping Experts, Recombining Neurons: Retraining-Free Pruning for Sparse Mixture-of-Experts LLMs Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-04T17:57:25.113322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T17:57:25.113322Z digest=sha256:17d3123c122b28729985d5f6131c5c0e20d9f97f794934c61fa25177709981fa

Observation ee872ec2-f586-4638-b6d0-197f4682f767 · inbound

GRACE-MoE: Grouping and Replication with Locality-Aware Routing for Efficient Distributed MoE Inference cites this paper.

GRACE-MoE: Grouping and Replication with Locality-Aware Routing for Efficient Distributed MoE Inference Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T12:02:35.580056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T12:01:32.788979Z digest=sha256:af1a87b1bf437536cded9927a9dd10df427a9905053e06d6f75a98ee067a5cc3

Observation d48c4271-7f56-4a8e-b8f5-47e105aec39a · inbound

PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference cites this paper.

PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-03T23:41:52.892552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T23:41:52.892552Z digest=sha256:1e9fd1a9be7b546da2c54056427ebee8506222d304803ef4bd6a1cd16d45ad51

Observation 7af7e47b-0204-48a3-bcdd-4ed22d06387b · inbound

EvoESAP: Non-Uniform Expert Pruning for Sparse MoE cites this paper.

EvoESAP: Non-Uniform Expert Pruning for Sparse MoE Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-15T14:35:55.555503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T14:34:48.524592Z digest=sha256:324c81cf856e639d73679af30457a47d02e76e9e42d3d571b4b24783187a8d31

Observation bc706dc3-c8f6-4aa0-9d76-e4d0ba795fc8 · inbound

SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training cites this paper.

SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 42

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T07:16:28.312598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-12T03:34:10.370956Z digest=sha256:eb03ff30a786c6d830489d420de27ba4a4d1e5cc9b288b3552396439b1372455

Observation 9dd30c1c-c65b-4529-898e-91e9491c072f · inbound

SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training cites this paper.

SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 42

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T23:23:51.266327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-20T23:22:51.808346Z digest=sha256:c18d8f7017dd45f2c0c2086636f94e86db6feb5df0378b4e7c39aaab96a06744

Observation 63d7ec45-8099-4597-b10d-d5bbac4a1bbe · inbound

HodgeCover: Higher-Order Topological Coverage Drives Compression of Sparse Mixture-of-Experts cites this paper.

HodgeCover: Higher-Order Topological Coverage Drives Compression of Sparse Mixture-of-Experts Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T05:55:04.761542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T05:54:32.496951Z digest=sha256:4ed51cbba1a626a02ef7028b75280df5f91fe7d6e7140b791d433f9cc1f1d1a2

Observation a9d852be-85ed-499f-9570-b6a922a7f85a · inbound

Post-Trained MoE Can Skip Half Experts via Self-Distillation cites this paper.

Post-Trained MoE Can Skip Half Experts via Self-Distillation Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 27

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T12:03:15.167297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T12:00:35.496822Z digest=sha256:643cd71b624f8d4b6e2d1099debde28f2fdf18ed019dc469a0a9e4fcfb28346f

Observation 5687dfb1-6f63-4e98-b8ce-53de53f3cf1a · inbound

Post-Trained MoE Can Skip Half Experts via Self-Distillation cites this paper.

Post-Trained MoE Can Skip Half Experts via Self-Distillation Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 27

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T18:25:00.063104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T18:22:45.702572Z digest=sha256:a0515af67f4ca5223df5d0deb228bf83c32d284fe77477db9a280d4c20d0ff54

Observation 4c53275d-7919-4f72-8e76-dc8be3760d04 · inbound

ConMoE: Expert-Pool Consolidation via Prototype Reassignment for MoE Compression cites this paper.

ConMoE: Expert-Pool Consolidation via Prototype Reassignment for MoE Compression Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T08:03:14.589238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T07:55:57.959580Z digest=sha256:88c57599aa1561a7e40ede2bc906fab5d7bd8917838d9a7f8ee9a19942bba14d

Observation 71624156-0df2-4337-9e75-bd989715d315 · inbound

Less is MoE: Trimming Experts in Domain-Specialist Language Models cites this paper.

Less is MoE: Trimming Experts in Domain-Specialist Language Models Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 48

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T11:36:55.532343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-28T03:11:23.755739Z digest=sha256:7af1784bea0a5df03e71ae236d27a7191573c98269a6cf3a84509122e15d9821

Observation 37323293-24c3-4318-90ca-f853c871c272 · inbound

It Takes a MAESTRO To Prune Bad Experts cites this paper.

It Takes a MAESTRO To Prune Bad Experts Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-02T07:56:24.689820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T07:56:24.689820Z digest=sha256:4c9ab78607463b2c86f077c294c91c387e9826193d3306507a048750f4ddaf3c