Paper Citation Record · LEDGER

FastMoE: A Fast Mixture-of-Expert Training System

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 29 inbound Pith citation observations for arXiv:2103.13262.

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

pith.paper-citation-record.v1
2103.13262 v1

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 29 of 29 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 29 of 29 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:52:07.475849Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T10:47:02.152647Z

Reference resolution

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External citation measurements

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Outbound references

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Pith citing papers

Observation c7019b44-4439-473e-9fe7-b5d9f57b046b · inbound

A Survey of Large Language Models cites this paper.

A Survey of Large Language Models FastMoE: A Fast Mixture-of-Expert Training System

Reference 211

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Source-reported events for the cited work

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Observation e463f93a-f277-4bcc-bbdd-44c1eb3066f8 · inbound

A Comprehensive Overview of Large Language Models cites this paper.

A Comprehensive Overview of Large Language Models FastMoE: A Fast Mixture-of-Expert Training System

Reference 85

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Source-reported events for the cited work

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Observation 3aed77df-0255-4bb4-a6b4-d1179ddc6545 · inbound

DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models cites this paper.

DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models FastMoE: A Fast Mixture-of-Expert Training System

Reference 172

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:07:22.306886Z

Source-reported events for the cited work

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Observation 25c84bbd-c5fb-4cb7-a2a6-361beccaed4f · 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 FastMoE: A Fast Mixture-of-Expert Training System

Reference 218

Resolution: verified exact; arxiv_id, observed 2026-05-20T13:35:02.311552Z

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Observation 6a27268a-ffa9-45a5-abaf-bc11ad728dae · 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 FastMoE: A Fast Mixture-of-Expert Training System

Reference 7

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Source-reported events for the cited work

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Observation caec5c3e-4025-450a-a09e-6bd5c6ccc09e · inbound

From System 1 to System 2: A Survey of Reasoning Large Language Models cites this paper.

From System 1 to System 2: A Survey of Reasoning Large Language Models FastMoE: A Fast Mixture-of-Expert Training System

Reference 66

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T01:36:23.955606Z

Source-reported events for the cited work

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Observation d73357d5-c507-4370-9956-4e1199b6fa67 · inbound

Two Is Better Than One: Rotations Scale LoRAs cites this paper.

Two Is Better Than One: Rotations Scale LoRAs FastMoE: A Fast Mixture-of-Expert Training System

Reference 9

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Source-reported events for the cited work

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Observation 22486253-f1f6-422c-88ad-715fb65d80bc · inbound

MoE-GPS: Guidlines for Prediction Strategy for Dynamic Expert Duplication in MoE Load Balancing cites this paper.

MoE-GPS: Guidlines for Prediction Strategy for Dynamic Expert Duplication in MoE Load Balancing FastMoE: A Fast Mixture-of-Expert Training System

Reference 8

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Observation d4340967-aa22-4a69-aad8-fd6b8cf1e4c5 · inbound

HarMoEny: Efficient Multi-GPU Inference of MoE Models cites this paper.

HarMoEny: Efficient Multi-GPU Inference of MoE Models FastMoE: A Fast Mixture-of-Expert Training System

Reference 12

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Observation 8e5341b7-536e-46e5-8b90-21ddb068f966 · inbound

Towards Accurate and Efficient 3D Object Detection for Autonomous Driving: A Mixture of Experts Computing System on Edge cites this paper.

Towards Accurate and Efficient 3D Object Detection for Autonomous Driving: A Mixture of Experts Computing System on Edge FastMoE: A Fast Mixture-of-Expert Training System

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T20:01:29.072590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f82d564-9f3c-467a-876f-ff097377227b · inbound

BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity cites this paper.

BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity FastMoE: A Fast Mixture-of-Expert Training System

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T18:20:00.189812Z

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Unavailable: canonical work link unavailable.

Observation 90764af7-1ac7-4b06-8082-f40da840398e · inbound

UltraMemV2: Memory Networks Scaling to 120B Parameters with Superior Long-Context Learning cites this paper.

UltraMemV2: Memory Networks Scaling to 120B Parameters with Superior Long-Context Learning FastMoE: A Fast Mixture-of-Expert Training System

Reference 11

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Source-reported events for the cited work

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Observation 79ae7997-4a84-4a1b-a01a-b522e7a2786d · inbound

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs cites this paper.

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs FastMoE: A Fast Mixture-of-Expert Training System

Reference 65

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:31:17.988693Z

Source-reported events for the cited work

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Observation 8365c891-d4f8-42c2-a69e-9252d4686c31 · inbound

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs cites this paper.

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs FastMoE: A Fast Mixture-of-Expert Training System

Reference 65

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T05:21:30.567351Z

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.

Observation c7825e9c-b3cf-4d82-9b09-622930c946f0 · inbound

MoE-Prefill: Zero Redundancy Overheads in MoE Prefill Serving cites this paper.

MoE-Prefill: Zero Redundancy Overheads in MoE Prefill Serving FastMoE: A Fast Mixture-of-Expert Training System

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T05:50:26.994223Z

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.

Observation d14e1f5f-ceca-4087-8593-731afe4b1243 · inbound

MoE-Prefill: Zero Redundancy Overheads in MoE Prefill Serving cites this paper.

MoE-Prefill: Zero Redundancy Overheads in MoE Prefill Serving FastMoE: A Fast Mixture-of-Expert Training System

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T17:47:41.970798Z

Source-reported events for the cited work

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Observation bb418645-f69b-465f-aabc-c9edaeedf98b · inbound

Hierarchical Mixture-of-Experts with Two-Stage Optimization cites this paper.

Hierarchical Mixture-of-Experts with Two-Stage Optimization FastMoE: A Fast Mixture-of-Expert Training System

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:01:15.400906Z

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.

Observation 39caa9a9-2175-4036-9aec-4f53d3543cf3 · inbound

Fast MoE Inference via Predictive Prefetching and Expert Replication cites this paper.

Fast MoE Inference via Predictive Prefetching and Expert Replication FastMoE: A Fast Mixture-of-Expert Training System

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:27:06.992817Z

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.

Observation 18fcc67d-21a3-4bb4-978c-03ae259594ac · inbound

EMO: Frustratingly Easy Progressive Training of Extendable MoE cites this paper.

EMO: Frustratingly Easy Progressive Training of Extendable MoE FastMoE: A Fast Mixture-of-Expert Training System

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T20:07:53.589798Z

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Observation 609fc325-8fc2-44b9-b51e-d6daba8d4007 · inbound

EMO: Frustratingly Easy Progressive Training of Extendable MoE cites this paper.

EMO: Frustratingly Easy Progressive Training of Extendable MoE FastMoE: A Fast Mixture-of-Expert Training System

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T05:35:04.303635Z

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.

Observation f1bb5ced-086e-4759-8a61-6d9a87a84c41 · inbound

ViBE: Co-Optimizing Workload Skew and Hardware Variability for MoE Serving cites this paper.

ViBE: Co-Optimizing Workload Skew and Hardware Variability for MoE Serving FastMoE: A Fast Mixture-of-Expert Training System

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:46:13.242761Z

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.

Observation d4629689-ac79-4e57-82d9-f7b0836d5666 · inbound

Language-Assisted Super-Resolution from Real-World Low-Resolution Patches cites this paper.

Language-Assisted Super-Resolution from Real-World Low-Resolution Patches FastMoE: A Fast Mixture-of-Expert Training System

Reference 49

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T10:05:41.498921Z

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.

Observation 28101062-bbed-4856-a13e-525275d988c6 · inbound

Language-Assisted Super-Resolution from Real-World Low-Resolution Patches cites this paper.

Language-Assisted Super-Resolution from Real-World Low-Resolution Patches FastMoE: A Fast Mixture-of-Expert Training System

Reference 49

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T22:18:59.533997Z

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.

Observation d503ead8-7bd4-46ff-b381-6b01c11a7451 · inbound

BrainFIBRE: A Foundation Model via Information Decomposition for Brain Microstructure cites this paper.

BrainFIBRE: A Foundation Model via Information Decomposition for Brain Microstructure FastMoE: A Fast Mixture-of-Expert Training System

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T15:07:04.023990Z

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.

Observation 999c85a5-de8c-4ad3-bcdc-2ad0e354f571 · inbound

BrainFIBRE: A Foundation Model via Information Decomposition for Brain Microstructure cites this paper.

BrainFIBRE: A Foundation Model via Information Decomposition for Brain Microstructure FastMoE: A Fast Mixture-of-Expert Training System

Reference 13

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Observation 6152210c-84fd-4605-a866-bb8536a07119 · inbound

From Tensor Buffer to Distributed Memory Hierarchy: A Survey of KV Cache Management for LLM Serving cites this paper.

From Tensor Buffer to Distributed Memory Hierarchy: A Survey of KV Cache Management for LLM Serving FastMoE: A Fast Mixture-of-Expert Training System

Reference 42

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Observation 0dd51e7f-3b5e-46f6-a27b-d4845e2ef976 · inbound

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting cites this paper.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting FastMoE: A Fast Mixture-of-Expert Training System

Reference 63

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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.

Observation 454c2b12-edc9-4083-bbb7-c81d2a7e2a93 · inbound

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting cites this paper.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting FastMoE: A Fast Mixture-of-Expert Training System

Reference 63

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e515c608-a980-4977-be24-17d305f175e5 · inbound

Relax Within, Balance Across: Geometry-Guided Load Balancing for Vision-Language Mixture-of-Experts cites this paper.

Relax Within, Balance Across: Geometry-Guided Load Balancing for Vision-Language Mixture-of-Experts FastMoE: A Fast Mixture-of-Expert Training System

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-05T00:38:32.753301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.