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Paper Citation Record · LEDGER

MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2410.12013.

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

pith.paper-citation-record.v1
2410.12013 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:14:55.827299Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T11:36:55.519986Z

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 b5705d1d-83a9-4439-b435-90cfa9e35ed0 · inbound

Utility-Driven Speculative Decoding for Mixture-of-Experts cites this paper.

Utility-Driven Speculative Decoding for Mixture-of-Experts MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T00:14:55.827299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:14:55.827299Z digest=sha256:97df9c0dacf2cc7f0ed5ad275abe301eadfe708da6d29ff283dd7383f9e9e95d

Observation 8a9c4c16-8373-497e-ab30-db5d5a85d8f2 · inbound

Sub-MoE: Efficient Mixture-of-Expert LLMs Compression via Subspace Expert Merging cites this paper.

Sub-MoE: Efficient Mixture-of-Expert LLMs Compression via Subspace Expert Merging MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T21:52:09.202720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:52:09.202720Z digest=sha256:1be790cac7598f7ecd4c89466d08ce10309f1eb8380f766b11ca28647039f614

Observation f52d5f90-66f0-4cb2-80f1-e44ab92f74ee · inbound

LExI: Layer-Adaptive Active Experts for Efficient MoE Model Inference cites this paper.

LExI: Layer-Adaptive Active Experts for Efficient MoE Model Inference MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-05T11:30:14.229857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:30:14.229857Z digest=sha256:44b09cfd48518a5e7fe3c37bde8218d41b49dee89f22f8124b01580f79bf9354

Observation 08c9e74e-3e7c-44c8-9e29-d72f963ee022 · 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 MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-04T17:57:25.214956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T17:57:25.214956Z digest=sha256:10f57114701ec0ace5c4acd6722d8f234ec2fb5b174bd679df068b3e6383ba93

Observation 004f3f9e-bb2a-4b06-bc39-57ed81f83761 · inbound

Train Large, Deploy Compact: Structured Compression for Compact Low-Rank Adaptation cites this paper.

Train Large, Deploy Compact: Structured Compression for Compact Low-Rank Adaptation MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-04T13:31:04.500933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:31:04.500933Z digest=sha256:1b13570491ebcd3f67d2f2263ef34f3145150c4e4bd3cf90b00877b0b96844de

Observation 13d50f4b-b377-4f43-80d1-db1bddc04c00 · inbound

Automatic Pruning Discovery for Large Language Models cites this paper.

Automatic Pruning Discovery for Large Language Models MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-03T21:28:03.295344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:28:03.295344Z digest=sha256:6490055b9d083b53d370e6cc334423ba34cda1268288a1c07407605a9f22f705

Observation c24d08c0-8be8-4d72-80c6-0d28a6d236e4 · inbound

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

EvoESAP: Non-Uniform Expert Pruning for Sparse MoE MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-15T14:35:55.510540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-15T14:34:48.524592Z digest=sha256:24f488b08b6f2dafe2d5774598353300e7dbc5e5bad891ef6687bb29ce353e77

Observation 5c0bf64d-960e-418f-9913-65ffa1198357 · inbound

Temporally Extended Mixture-of-Experts Models cites this paper.

Temporally Extended Mixture-of-Experts Models MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:39:48.336657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T00:39:39.492135Z digest=sha256:a5c89dc79d77533ac5ee5f14ecf5cb7db5d83cd321b25abc766e343d3bae2412

Observation 6914bdf1-3f57-486b-91cc-1473a9019c5e · inbound

MACS: Modality-Aware Capacity Scaling for Efficient Multimodal MoE Inference cites this paper.

MACS: Modality-Aware Capacity Scaling for Efficient Multimodal MoE Inference MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T06:51:46.427436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T06:47:25.155437Z digest=sha256:17fd20600ce9a91d0685bb246c4acd496e5e928f70d0148ad907fd63a6b83b35

Observation 3d2fa2c5-9e59-4187-b9ed-3ee784a3372c · inbound

MACS: Modality-Aware Capacity Scaling for Efficient Multimodal MoE Inference cites this paper.

MACS: Modality-Aware Capacity Scaling for Efficient Multimodal MoE Inference MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T01:45:52.021526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-05-11T01:29:26.298131Z digest=sha256:541068f1693dd6d25f802eae8563872d07bbec53e64c4c435018ff7a65bf45ae

Observation 77413185-7326-4c13-a446-34a062805b97 · 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 MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-15T05:55:04.777849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-15T05:54:32.496951Z digest=sha256:e16d8ac558a34a0bf365c890225e56e1acbda65996e4c8504540cc9d2f49a180

Observation 2bcca7bc-b1c6-486a-a04a-a2e7cca1cf0e · inbound

Pruning and Distilling Mixture-of-Experts into Dense Language Models cites this paper.

Pruning and Distilling Mixture-of-Experts into Dense Language Models MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-06-29T12:43:25.601092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T12:39:25.535897Z digest=sha256:a3bc4cdd8b2abd98c104f46d9c41f81eaa7afea26d00794778c89450d6243f37

Observation 4e5017c8-185e-468e-96f6-315e8b9a6c45 · inbound

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

Less is MoE: Trimming Experts in Domain-Specialist Language Models MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 41

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T11:36:55.521603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-28T03:11:23.755739Z digest=sha256:940c9a1b46e350b4fd17ca07c59332ac542085b67a6fd5956717bcfb2643caf0

Observation e8b8f526-749f-4ba4-94c3-84435e8c2945 · inbound

Beyond Uniform Experts: Cost-Aware Expert Execution for Efficient Multi-Device MoE Inference cites this paper.

Beyond Uniform Experts: Cost-Aware Expert Execution for Efficient Multi-Device MoE Inference MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-06-30T17:14:57.485708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T04:27:02.915854Z digest=sha256:049c6ba4201060f25ed0dbf854b37c3f96c98f104d3da741c774ee65729e8d97

Observation cd5067b8-57f7-4d0f-ac62-7566fda30974 · inbound

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

It Takes a MAESTRO To Prune Bad Experts MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-02T07:56:24.589911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T07:56:24.589911Z digest=sha256:dcda6b9db3d3b2ce0c442c1f304a25b1ef91875de2e7bf71f6e2f0dd4a253ec4