Paper Citation Record · LEDGER

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing

As of 8 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 2 inbound Pith citation observations for arXiv:2505.18586.

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

pith.paper-citation-record.v1
2505.18586 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:33:36.683334Z

measured 44 of 44 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T12:34:19.755096Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:59:33.779589Z

Reference resolution

42 of 42 outbound references displayed

verified exact0
verified fuzzy25
unresolved17
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 08442a66-9689-48da-9833-e72dc47ed345 · outbound

This paper cites End-to-end object detection with transformers.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing End-to-end object detection with transformers

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:32.363333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c1d6240-1d06-49ab-a6f0-7ddf90d7b3a3 · outbound

This paper cites Emerging properties in self-supervised vision transformers.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Emerging properties in self-supervised vision transformers

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:42.553748Z

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 aa19de02-0129-4573-aba2-6d5d0e446318 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:32.552347Z

Source-reported events for the cited work

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Observation 70f53ef7-d7a0-4b45-af35-902f8574ac2b · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.Journal of Machine Learning Research, 23(120):1–39, 2022.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.Journal of Machine Learning Research, 23(120):1–39, 2022

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:32.647321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2578ae43-6540-4642-ad6f-8c5f5c4be33a · outbound

This paper cites Deep residual learning for im- age recognition.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Deep residual learning for im- age recognition

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:42.311410Z

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 418d4f76-4c2e-4f2d-939d-3924e34135df · outbound

This paper cites Tutel: Adaptive mixture-of-experts at scale.Proceedings of Machine Learning and Systems, 5:269–287, 2023.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Tutel: Adaptive mixture-of-experts at scale.Proceedings of Machine Learning and Systems, 5:269–287, 2023

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:42.011089Z

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 a55b314e-2de9-427f-b779-0955818b6baa · outbound

This paper cites Mixtral of Experts.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Mixtral of Experts

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:32.968718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aea484e8-e6e0-456f-aa98-29cbf9818730 · outbound

This paper cites Scaling Laws for Neural Language Models.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Scaling Laws for Neural Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:33.072626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f336ba35-812b-4da7-a3e9-46b0d5717f24 · outbound

This paper cites Segment anything.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Segment anything

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:41.771374Z

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 68465815-90c8-408c-a683-8658f16cc8e0 · outbound

This paper cites Soft mixture of experts - official implementation.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Soft mixture of experts - official implementation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:41.591814Z

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 04742cb3-b84b-4cc7-8781-4fa226eb6928 · outbound

This paper cites 3d object representations for fine- grained categorization.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing 3d object representations for fine- grained categorization

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:41.360301Z

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 d97b9e25-0e03-49e7-9cfa-1b5525d7770b · outbound

This paper cites Imagenet classification with deep convolutional neural networks.Advances in neural information processing systems, 25, 2012.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Imagenet classification with deep convolutional neural networks.Advances in neural information processing systems, 25, 2012

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:41.170507Z

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 bd3db919-91a7-4210-884f-1aa36e29f40b · outbound

This paper cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:33.599478Z

Source-reported events for the cited work

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Observation 1fac9e2a-18e8-488a-905e-80bc744184b8 · outbound

This paper cites Base layers: Simplifying training of large, sparse models.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Base layers: Simplifying training of large, sparse models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:40.915380Z

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 70c0881f-4f29-4dc4-97cb-427a7e3707a5 · outbound

This paper cites Grounded language-image pre-training.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Grounded language-image pre-training

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:40.672747Z

Source-reported events for the cited work

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Observation b9bfb604-2134-421e-b44e-99ee506f97c1 · outbound

This paper cites PyTorch Distributed: Experiences on Accelerating Data Parallel Training.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing PyTorch Distributed: Experiences on Accelerating Data Parallel Training

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:33.878303Z

Source-reported events for the cited work

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Observation 7127df2f-2c9c-4c75-a4c8-e59fdc6871e7 · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:33.970018Z

Source-reported events for the cited work

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Observation 2c85b294-3cd7-45b0-af65-c637eb7d077f · outbound

This paper cites DeepSeek-V3 Technical Report.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing DeepSeek-V3 Technical Report

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:34.094671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0121a585-6c28-4c10-9079-7ec80929632f · outbound

This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set object detection.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Grounding dino: Marrying dino with grounded pre-training for open-set object detection

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:40.448018Z

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 d36a74a9-b741-46e7-a269-1cce2ea8d590 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Swin transformer: Hierarchical vision transformer using shifted windows

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:40.238979Z

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 5751bc72-914d-485c-b574-6780ea1966bd · outbound

This paper cites A convnet for the 2020s.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing A convnet for the 2020s

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:40.031007Z

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 4b954fde-18f9-45be-9592-fb20b4ae6570 · outbound

This paper cites Object-centric learning with slot attention.Advances in Neural Information Processing Systems (NeurIPS), 2020.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Object-centric learning with slot attention.Advances in Neural Information Processing Systems (NeurIPS), 2020

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:39.815555Z

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 a07ab3a6-3be3-4c14-a85c-bf6ab5ab159e · outbound

This paper cites Language segment anything.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Language segment anything

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:39.601367Z

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 1b8e5639-9a2b-4b7a-993c-c7d76221e730 · outbound

This paper cites Soft Merging of Experts with Adaptive Routing.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Soft Merging of Experts with Adaptive Routing

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:34.714949Z

Source-reported events for the cited work

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Observation a4432f0b-a46e-438b-a832-be56ef31d275 · outbound

This paper cites Intriguing properties of vision transformers.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Intriguing properties of vision transformers

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:39.438810Z

Source-reported events for the cited work

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Observation b61df33e-7bd8-4afb-a84c-15282843f707 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing DINOv2: Learning Robust Visual Features without Supervision

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:34.869978Z

Source-reported events for the cited work

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Observation 5837d8f7-1927-467d-80d2-f0ab832ee714 · outbound

This paper cites Moment matching for multi-source domain adaptation.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Moment matching for multi-source domain adaptation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:39.180697Z

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 d3e5b112-0a47-4851-8fba-acfa9b96d133 · outbound

This paper cites Spatial entropy as an inductive bias for vision transformers.Machine Learning, 113(9):6945– 6975, 2024.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Spatial entropy as an inductive bias for vision transformers.Machine Learning, 113(9):6945– 6975, 2024

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:39.055304Z

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 c1a987f1-b60b-4593-831b-0e420031a924 · outbound

This paper cites From Sparse to Soft Mixtures of Experts.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing From Sparse to Soft Mixtures of Experts

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:35.205550Z

Source-reported events for the cited work

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Observation c7232b33-d465-45cc-839d-f89613c39b5f · outbound

This paper cites Scaling vision with sparse mixture of experts.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Scaling vision with sparse mixture of experts

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:38.887296Z

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 7efe1547-5205-42ac-9601-1197c13169f5 · outbound

This paper cites Hash layers for large sparse models.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Hash layers for large sparse models

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:38.734475Z

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 f456e2d4-b5eb-408a-9ff9-8c9b99229696 · outbound

This paper cites Imagenet large scale visual recognition challenge.International Journal of Computer Vision (IJCV), 115:211–252, 2015.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Imagenet large scale visual recognition challenge.International Journal of Computer Vision (IJCV), 115:211–252, 2015

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:38.531961Z

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 27014677-41e2-46ce-b2fe-027040d82cc7 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:35.683430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89da59f5-fcd3-4e5a-9e8c-d97a7acd15ee · outbound

This paper cites Contrastive multiview coding.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Contrastive multiview coding

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:38.402031Z

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 2c13a29c-ca69-4462-af38-9b39c056b5d4 · outbound

This paper cites Go- ing deeper with image transformers.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Go- ing deeper with image transformers

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:38.253403Z

Source-reported events for the cited work

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Observation c406c8ea-9f83-4fe9-99a9-f2d6c41a0fcd · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:38.076829Z

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 814c3b5a-689e-454b-ae5c-17e389edf534 · outbound

This paper cites an unresolved cited work.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:33:37.886315Z

Source-reported events for the cited work

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Observation 4ab9749c-824a-4b17-b41d-6ae215953896 · outbound

This paper cites Mixture of LoRA Experts.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Mixture of LoRA Experts

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:36.228616Z

Source-reported events for the cited work

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Observation 6d25b483-8bf1-4e89-adad-12682c2cb369 · outbound

This paper cites Scaling vision transform- ers.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Scaling vision transform- ers

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:37.726000Z

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 4049b028-a20d-494a-9ae0-87b68e697488 · outbound

This paper cites Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:36.426040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 749d1670-6b59-4278-bbcf-c48ea6fd538a · outbound

This paper cites iBOT: Image BERT Pre-Training with Online Tokenizer.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing iBOT: Image BERT Pre-Training with Online Tokenizer

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:36.575066Z

Source-reported events for the cited work

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Observation a09011d1-c530-461b-97e8-9ee66a417533 · outbound

This paper cites scale + linear.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing scale + linear

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:33:37.319680Z

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.

Pith citing papers

Observation 80c2370b-2c9b-483b-8a59-37d818424f9e · inbound

AME-TS: Anchored Mixture-of-Experts for Time Series Forecasting cites this paper.

AME-TS: Anchored Mixture-of-Experts for Time Series Forecasting Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-06-30T12:34:38.534237Z

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 520aa51a-28d9-4bc3-9997-371a0320d37b · inbound

Toward Calibrated Mixture-of-Experts Under Distribution Shift cites this paper.

Toward Calibrated Mixture-of-Experts Under Distribution Shift Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:59:33.781369Z

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.