Paper Citation Record · LEDGER

Mixture of A Million Experts

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:2407.04153.

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

pith.paper-citation-record.v1
2407.04153 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 23 of 23 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:48:11.364496Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:37:56.692349Z

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 121e1a94-c352-40bd-aace-8d04fe613942 · inbound

Towards Foundational Models for Dynamical System Reconstruction: Hierarchical Meta-Learning via Mixture of Experts cites this paper.

Towards Foundational Models for Dynamical System Reconstruction: Hierarchical Meta-Learning via Mixture of Experts Mixture of A Million Experts

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-08T19:48:11.364496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6287b0f-f201-490d-b5b4-5e8dc12f5861 · inbound

Scaling and Enhancing LLM-based AVSR: A Sparse Mixture of Projectors Approach cites this paper.

Scaling and Enhancing LLM-based AVSR: A Sparse Mixture of Projectors Approach Mixture of A Million Experts

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T15:39:32.373581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb39ab09-f000-46e2-98cf-a409e0b67f47 · inbound

PC-MoE: Memory-Efficient and Privacy-Preserving Collaborative Training for Mixture-of-Experts LLMs cites this paper.

PC-MoE: Memory-Efficient and Privacy-Preserving Collaborative Training for Mixture-of-Experts LLMs Mixture of A Million Experts

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T11:17:09.108597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b5d0f0f-6f70-4f1f-9b93-74b345fadb35 · 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 Mixture of A Million Experts

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T16:17:41.950238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4016bff-8614-4827-8e25-b67cda9bb738 · inbound

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection cites this paper.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Mixture of A Million Experts

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:27.224525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ade3434-a3de-479a-b864-57022517dc0a · inbound

OmniMoE: An Efficient MoE by Orchestrating Atomic Experts at Scale cites this paper.

OmniMoE: An Efficient MoE by Orchestrating Atomic Experts at Scale Mixture of A Million Experts

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T04:13:59.832245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e49ea68-8357-465c-919d-25b64cad0efb · inbound

Equifinality in Mixture of Experts: Routing Topology Does Not Determine Language Modeling Quality cites this paper.

Equifinality in Mixture of Experts: Routing Topology Does Not Determine Language Modeling Quality Mixture of A Million Experts

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:05:25.086899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cd592267-68a2-4dd4-b2c6-2abb046a696e · inbound

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

Temporally Extended Mixture-of-Experts Models Mixture of A Million Experts

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-10T00:39:48.228957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bafeb384-a0fa-431c-a211-8a5063e2c5eb · inbound

Adaptive Inverted-Index Routing for Granular Mixtures-of-Experts cites this paper.

Adaptive Inverted-Index Routing for Granular Mixtures-of-Experts Mixture of A Million Experts

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T06:55:43.470352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5799d1e2-3407-4da7-88f6-1367878d7f2b · inbound

TIDE: Every Layer Knows the Token Beneath the Context cites this paper.

TIDE: Every Layer Knows the Token Beneath the Context Mixture of A Million Experts

Reference 84

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:56:09.981433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b1d229bd-51c7-4249-a4e2-19d2f716b43b · inbound

UniPool: A Globally Shared Expert Pool for Mixture-of-Experts cites this paper.

UniPool: A Globally Shared Expert Pool for Mixture-of-Experts Mixture of A Million Experts

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:26:09.384847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cdbc6248-daf8-4605-8b37-3e2d1be6b662 · inbound

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices cites this paper.

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices Mixture of A Million Experts

Reference 138

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:36:19.888923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b5eeb441-4021-44de-b6bb-e1ca58a5eec5 · inbound

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices cites this paper.

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices Mixture of A Million Experts

Reference 138

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:32:30.357681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b9b62680-b302-4991-847a-1b18ee10a28b · inbound

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices cites this paper.

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices Mixture of A Million Experts

Reference 138

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:59:50.211883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 41ea0c41-45ba-45aa-9119-406cba099cb3 · inbound

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

Fast MoE Inference via Predictive Prefetching and Expert Replication Mixture of A Million Experts

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:27:06.988620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3dd333e6-64a6-4f97-b62c-9839998c6e5a · inbound

How to Scale Mixture-of-Experts: From muP to the Maximally Scale-Stable Parameterization cites this paper.

How to Scale Mixture-of-Experts: From muP to the Maximally Scale-Stable Parameterization Mixture of A Million Experts

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-15T04:49:44.989030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 809f2788-440c-42b3-9ce8-abde9189cb07 · inbound

DAG-MoE: From Simple Mixture to Structural Aggregation in Mixture-of-Experts cites this paper.

DAG-MoE: From Simple Mixture to Structural Aggregation in Mixture-of-Experts Mixture of A Million Experts

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:16:14.388131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4489dfe9-ad7a-419a-9437-017a59a40d71 · inbound

Sparsely gated tiny linear experts cites this paper.

Sparsely gated tiny linear experts Mixture of A Million Experts

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T16:17:09.302550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ac2a1825-b19d-4496-8fd2-153890b1b080 · inbound

Augmenting Molecular Language Models with Local $n$-gram Memory cites this paper.

Augmenting Molecular Language Models with Local $n$-gram Memory Mixture of A Million Experts

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:37:56.693740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6970dd79-d760-4dd0-8be9-d49f2d2aad34 · inbound

CMSL: Constructive Multi-Sequence Learning for Recommendation Systems cites this paper.

CMSL: Constructive Multi-Sequence Learning for Recommendation Systems Mixture of A Million Experts

Reference 99

Resolution: verified exact; arxiv_id, observed 2026-07-01T16:05:49.806130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 888c7626-4b91-4bbd-85f8-6d701390a12a · inbound

Training, Reading, and Editing Legible Transformers cites this paper.

Training, Reading, and Editing Legible Transformers Mixture of A Million Experts

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-13T05:35:58.568346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e7c3cc1-065d-4c66-a6cd-3b2116b3d7e7 · inbound

More Than Memory: Task-Conditioned Signed FFN Writes in Long-Context Retrieval cites this paper.

More Than Memory: Task-Conditioned Signed FFN Writes in Long-Context Retrieval Mixture of A Million Experts

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T09:48:58.072705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 876f88c5-56eb-4a9f-bd84-ba0df0479b50 · inbound

The SpiNNaker2 chip: a many-core platform for flexible and scalable brain-inspired computing cites this paper.

The SpiNNaker2 chip: a many-core platform for flexible and scalable brain-inspired computing Mixture of A Million Experts

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-31T16:02:10.656508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.