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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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-23T17:04:13.905401Z digest=sha256:7d37727c12c8bad3b5aed8018e341f11f26bcb670fe543e03d6e586815836472

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=sha256:3a4fbc3a57bdbd010bae0fad69903733422255e7670dddd913c785c3e348dbe1

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=sha256:314eb43f28b9d8bdd72d27579870567f222f34153ffa80cb6ae92c298a33571a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T12:01:32.788979Z digest=sha256:088198716bfd365907279c121f038107df5735ed055891896713a546a54dcb17

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:ca9f76999356f8baaa431a0c3ae20e2ece3505e67e7d9c9f4ae1d116ca682d27

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T14:34:48.524592Z digest=sha256:fcae6a0e59c4a6450230bc1071d81a72bf8035910262de6929ef5edb7dbf888a

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-12T03:34:10.370956Z digest=sha256:4cc645927556bfa586b1703342cb7c32735bfb8bf498afb5411c58395f150b99

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-20T23:22:51.808346Z digest=sha256:05e433f9374923c3648acf001ce77bd456efc9afed1a6f1e7fd3aea46e7ce2b4

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T05:54:32.496951Z digest=sha256:4e9f2cbc7f9738690aecb33fec9f2bc89cd11b9e1928536f46d91a475c08d4d3

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-20T12:00:35.496822Z digest=sha256:89fa474a5a72671305af58d46f56450e5dad9f965d8b057e881a45514b387f07

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T18:22:45.702572Z digest=sha256:a598732255791d29f396113285fa497d8090c15cd62ae51a010acdfdafba6bda

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T07:55:57.959580Z digest=sha256:50fbc75dce6e14557847dd55bfe796b6ab302d8bb77c318133393f602e57c126

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T03:11:23.755739Z digest=sha256:4281fa927ab7348fbc4479092be3b12f3e9b12513f1885d7c6c5beaee72d7d7d

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=sha256:2755d421f825f496aacf8a127eec085e2996aa6e39e36ab113379b3ed7e27096