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Paper Citation Record · LEDGER

Sticky Routing: Training MoE Models for Memory-Efficient Inference

As of 23 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2607.08780.

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

pith.paper-citation-record.v1
2607.08780 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-13T07:34:15.530836Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved27
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 124ad6e4-a37d-4612-9e20-b1a3515db5bc · outbound

This paper cites International Conference on Learning Representations (ICLR) , year =.

Sticky Routing: Training MoE Models for Memory-Efficient Inference International Conference on Learning Representations (ICLR) , year =

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:41aac496353d2be70fe376a2f6d1c1775ecc13bf1d288fe4443718fbd2d3c0a4

Observation 9596f9ae-7be4-415b-b464-f5f0ca5004c1 · outbound

This paper cites Journal of Machine Learning Research , volume =.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Journal of Machine Learning Research , volume =

Reference 2

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:2fa2affe357b83d5120684df95bcf26fa5078994f78c0a15da388b924c533fde

Observation 634e2a4a-acde-4f96-aef2-9d956d9773af · outbound

This paper cites an unresolved cited work.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Unresolved cited work

Reference 3

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:9243cfc7adc350f8b73ceff37bf59dc168c5f3acb3d35d724fbd8ecc527c8bb9

Observation 45b0c8f6-0db7-4326-b610-d7efe53d58f4 · outbound

This paper cites an unresolved cited work.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Unresolved cited work

Reference 4

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:6141ff21e79eeea422c1f30ac0b7117e1d72f28f770598522eeaeda84729e84e

Observation 9fcfae56-6d63-4f4f-a5c5-188e60ef23d9 · outbound

This paper cites Advances in Neural Information Processing Systems (NeurIPS) , year =.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Advances in Neural Information Processing Systems (NeurIPS) , year =

Reference 5

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:3d7ff9c7f8c9eace888644d96e6ab9af64c5fb0b63a70eab6fd5cfe6e8eced76

Observation 69f5f9ae-0ee1-4e88-aa24-ee8d2c480151 · outbound

This paper cites Mixtral of Experts.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Mixtral of Experts

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:9737e146b8be334d026f3eec9f991510ceabf8452481130b9a0cff19cf864ff9

Observation 04b49ec3-8851-4875-89a1-c6acf37be5d5 · outbound

This paper cites and Lv, Qin and Zhu, Rui and Zhang, Chun and Yang, Fan and Lu, Tun and Gu, Ning and Shang, Li , booktitle =.

Sticky Routing: Training MoE Models for Memory-Efficient Inference and Lv, Qin and Zhu, Rui and Zhang, Chun and Yang, Fan and Lu, Tun and Gu, Ning and Shang, Li , booktitle =

Reference 7

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Source-reported events for the cited work

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:2ced456fb1ab1c29b5b441b5ed90a06d8298d89c6fb3ca60131d812938c65a03

Observation c18475df-10cf-4ca0-86ea-1845ab5b2fba · outbound

This paper cites ReMoE: Boosting Expert Reuse through Router Fine-Tuning in Memory-Constrained MoE LLM Inference.

Sticky Routing: Training MoE Models for Memory-Efficient Inference ReMoE: Boosting Expert Reuse through Router Fine-Tuning in Memory-Constrained MoE LLM Inference

Reference 8

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:d7f376ea8f37aa31c306ee4a7acd584f5735025d6c2b8380cffd828f69e1de92

Observation 3c3e7ae7-0775-4259-ab23-968da6ef3d1f · outbound

This paper cites arXiv preprint arXiv:2505.16056 , year=.

Sticky Routing: Training MoE Models for Memory-Efficient Inference arXiv preprint arXiv:2505.16056 , year=

Reference 9

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:692cb9f01f47f3dfd0cdd73198d38f523adc5733b80eb484db26618089f25150

Observation 6137cece-6c35-4114-91b3-961a8103c0b6 · outbound

This paper cites an unresolved cited work.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Unresolved cited work

Reference 10

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:983d549dee90720e78e5f735ed362d4efa5c1f3080148e193c7ebf727e27ccad

Observation 911d8eb6-408a-4c8d-ab63-fe0bf0eca435 · outbound

This paper cites Fiddler:.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Fiddler:

Reference 11

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:08000917d6f955636f54743813a8b9a7a936108a30effa3ecc43a76f426eb44f

Observation 94268baf-1e3b-4b72-8c91-cd5f53e30dbc · outbound

This paper cites DuoServe-MoE: Dual-Phase Expert Prefetch and Caching for LLM Inference QoS Assurance.

Sticky Routing: Training MoE Models for Memory-Efficient Inference DuoServe-MoE: Dual-Phase Expert Prefetch and Caching for LLM Inference QoS Assurance

Reference 12

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:e0f1c1a8b7161bdf73b9d94768912f52fef6a55d30d307350a43abb2d4785b7a

Observation bb5b9855-f544-4ba5-a0a4-7105703d5ccb · outbound

This paper cites SMoE: An Algorithm-System Co-Design for Pushing MoE to the Edge via Expert Substitution.

Sticky Routing: Training MoE Models for Memory-Efficient Inference SMoE: An Algorithm-System Co-Design for Pushing MoE to the Edge via Expert Substitution

Reference 13

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:693544ce04ddf3d8eee8a46cc622ee7bd805349f713ae9f237ba5ad49461cf6c

Observation c60a2889-5d1b-470c-8c81-2fac8f6d6edf · outbound

This paper cites Mixture-of-Depths: Dynamically allocating compute in transformer-based language models.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Reference 14

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:6887bfec698511b6c70aa85f36edc5e2c4ced8ab3de76dbe1a884b1dadf0de63

Observation 0ac4d876-6ac8-444e-9dbb-6b49a74bf6ff · outbound

This paper cites Pre-gated.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Pre-gated

Reference 15

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:97dd12d8f5d565267c0d1a90d85effd94360274cb2bee8d3731474692abc6d82

Observation 3703a241-6352-475b-ad8a-7c2cab510cac · outbound

This paper cites EvidenceMoE: A Physics-Guided Mixture-of-Experts with Evidential Critics for Advancing Fluorescence Light Detection and Ranging in Scattering Media.

Sticky Routing: Training MoE Models for Memory-Efficient Inference EvidenceMoE: A Physics-Guided Mixture-of-Experts with Evidential Critics for Advancing Fluorescence Light Detection and Ranging in Scattering Media

Reference 16

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:57cc080ba7641c9e12f82c28fb296dc699c155530ff636cc7bb4e32b513ae808

Observation 8dc5b7bd-2d3d-424e-adb2-fd3e18fd0043 · outbound

This paper cites International Conference on Learning Representations (ICLR) , year =.

Sticky Routing: Training MoE Models for Memory-Efficient Inference International Conference on Learning Representations (ICLR) , year =

Reference 17

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:6e46dbd8ea8c57a72302cb452533516541ba92a7da8266444359591c7e2eb4f6

Observation d778207d-8c9e-4099-a023-c49500d78e42 · outbound

This paper cites an unresolved cited work.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Unresolved cited work

Reference 18

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:dcb105e5d3054f8c6b354db8973d7910c578c14670e490c13d9e2156b73cb6fc

Observation b2e12cca-16c8-4a69-b78d-6ce6052dfcbb · outbound

This paper cites International Conference on Learning Representations (ICLR) , year =.

Sticky Routing: Training MoE Models for Memory-Efficient Inference International Conference on Learning Representations (ICLR) , year =

Reference 19

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:b2c50fc5aae1ba04af12974385d37025a9aa67abe98ddbab67ecf6bc1c92c0ea

Observation 2b3929b3-6bab-4346-bb70-ab6d65a995e4 · outbound

This paper cites Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , year =.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , year =

Reference 20

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:430e6a54e7d730ae15a30c3f2d1ec04283264b1bba068c61b8ff23994cce3198

Observation 719e297c-fc0c-4196-aba1-9b6945fb4d76 · outbound

This paper cites Safety-Oriented Routing Analysis of Mixtral MoE Under Benign and Harmful Prompts.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Safety-Oriented Routing Analysis of Mixtral MoE Under Benign and Harmful Prompts

Reference 21

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:37a164b326b92127414821ecfb808878c0ae98e730d8285a0082b4dc1c348791

Observation 6c77ccbf-1fc7-455e-9518-3f611790bf52 · outbound

This paper cites OpenAI blog , volume=.

Sticky Routing: Training MoE Models for Memory-Efficient Inference OpenAI blog , volume=

Reference 22

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:07f041039bc5e8e7bc87afebff15b511667a20c36a6de13af099f5edee47e6e9

Observation 3748a49a-57bd-49c9-835a-d4f3d30c728f · outbound

This paper cites Proceedings of the 2020 conference on empirical methods in natural language processing: system demonstrations , pages=.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Proceedings of the 2020 conference on empirical methods in natural language processing: system demonstrations , pages=

Reference 23

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:abcb5bc31ab456f13f0c75c3ab97dc8001d01261a7da15b78d27f5c8eef14799

Observation 28ac1096-5a0c-4896-af73-e2a4c5777f08 · outbound

This paper cites 2018 , publisher=.

Sticky Routing: Training MoE Models for Memory-Efficient Inference 2018 , publisher=

Reference 24

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:bcbcaf34d8d8d0b53794d19218e09fde84e5e47b10ad6185a9e50aaa5aee73c1

Observation 85aeb579-d3ab-44af-ad55-2baced0e2a6d · outbound

This paper cites Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers , pages=.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers , pages=

Reference 25

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:1f83573e6ba96fac6e939105331d6204ec0e14b1036e643e7611a0a835460a6b

Observation c0631911-88a5-4fb7-8799-8fc4e6ee9311 · outbound

This paper cites advances in neural information processing systems , volume=.

Sticky Routing: Training MoE Models for Memory-Efficient Inference advances in neural information processing systems , volume=

Reference 26

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source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:4f0e9e056046e776d2dd0ac6cc4fe3c553e6c4093a2583a7a550b48b04bab1ce

Observation d5fd9d23-6fbf-4139-aff7-9d6179a83cf4 · outbound

This paper cites Advances in neural information processing systems , volume=.

Sticky Routing: Training MoE Models for Memory-Efficient Inference Advances in neural information processing systems , volume=

Reference 27

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T07:34:15.530836Z digest=sha256:bbc092f0c63964fddfa3ae5008a530f1dd225cfeda16ab0ad08f731aedbfd5de

Pith citing papers

No inbound Pith citation observations are available.