Paper Citation Record · LEDGER

MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2411.01016.

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

pith.paper-citation-record.v1
2411.01016 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:53:43.594876Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T17:14:57.406110Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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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 43ae9bfd-f2b9-4bd6-8214-c8482cc2ae76 · inbound

A Survey on Inference Optimization Techniques for Mixture of Experts Models cites this paper.

A Survey on Inference Optimization Techniques for Mixture of Experts Models MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 203

Resolution: unresolved; no resolver link, observed 2026-08-11T12:44:36.127711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9199348c-1b5d-493f-9db0-fb834161f713 · inbound

Faster MoE LLM Inference for Extremely Large Models cites this paper.

Faster MoE LLM Inference for Extremely Large Models MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T23:53:43.594876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4635aa8b-5752-4e4d-be90-438bdaba0c1d · inbound

QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration cites this paper.

QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T22:45:12.243625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 533e0c95-9a40-499f-9fc9-bb97515cf5ef · inbound

Occult: Optimizing Collaborative Communication across Experts for Accelerated Parallel MoE Training and Inference cites this paper.

Occult: Optimizing Collaborative Communication across Experts for Accelerated Parallel MoE Training and Inference MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T20:20:58.277550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38e4c1b4-dff6-4853-919d-8e25c1d55aed · inbound

SlimMoE: Structured Compression of Large MoE Models via Expert Slimming and Distillation cites this paper.

SlimMoE: Structured Compression of Large MoE Models via Expert Slimming and Distillation MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-15T18:58:34.901052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0272af74-5132-471d-816a-2bfd2ee463fa · 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-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:09.523179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation adc35558-fd31-43f6-910d-11c348de5fea · 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-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T11:30:14.314029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3df6d3c-33f2-43a4-89fc-75718c3ca28c · 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-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-04T17:57:25.224160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c986254d-4e84-45a7-81e5-e58639686ea9 · 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 MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T23:41:52.927468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba5cfb40-d5cc-4cea-be5f-101809737376 · inbound

ButterflyMoE: Compression-Scalable Ternary Experts via Structured Butterfly Orbits cites this paper.

ButterflyMoE: Compression-Scalable Ternary Experts via Structured Butterfly Orbits MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T09:32:55.511235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd1471e9-d9dd-431f-b701-928b761f5709 · inbound

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

EvoESAP: Non-Uniform Expert Pruning for Sparse MoE MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-15T14:35:55.646451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation db7cfda7-5df8-4f90-82bf-f193ef37c6fb · inbound

Path-Constrained Mixture-of-Experts cites this paper.

Path-Constrained Mixture-of-Experts MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-15T09:19:54.276593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 95615c89-1ce1-4a93-948e-e8717e670abb · inbound

FluxMoE: Decoupling Expert Residency for High-Performance MoE Serving cites this paper.

FluxMoE: Decoupling Expert Residency for High-Performance MoE Serving MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:18:13.280550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d58bc009-1d59-459c-9739-63e84a7a37cd · inbound

BitsMoE: Efficient Spectral Energy-Guided Bit Allocation for MoE LLM Quantization cites this paper.

BitsMoE: Efficient Spectral Energy-Guided Bit Allocation for MoE LLM Quantization MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-06-30T15:44:48.466223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 528da36e-b37d-4f86-af60-f3647c4a628a · 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-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-06-30T17:14:57.407554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 49ffc646-cb1b-4427-b0e8-255ff2f9e063 · inbound

Communication-Aware Placement and Pruning for Efficient Mixture-of-Experts Inference cites this paper.

Communication-Aware Placement and Pruning for Efficient Mixture-of-Experts Inference MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Reference 38

Resolution: unresolved; no resolver link, observed 2026-07-11T08:35:22.347459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.