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Paper Citation Record · LEDGER

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs

As of 7 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2607.22577.

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

pith.paper-citation-record.v1
2607.22577 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T12:12:35.727863Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

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Source: cited_works

Reference resolution

42 of 42 outbound references displayed

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  • verified fuzzy0
  • unresolved40
  • parse uncertain0
  • malformed identifier0
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External citation measurements

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Outbound references

Observation eeda34eb-a0a9-44fd-9e43-518ead7681dd · outbound

This paper cites Scaling Laws for Neural Language Models.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Scaling Laws for Neural Language Models

Reference 1

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source=arxiv_source observed=2026-08-02T12:12:35.598077Z digest=sha256:d3214a07584cdfce64c0d5c91b19319a475c3cfc51d6e181564a0c9f4425bb5e

Observation a6fe5888-f152-4641-91ab-9d3da5ed5243 · outbound

This paper cites Training Compute-Optimal Large Language Models.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Training Compute-Optimal Large Language Models

Reference 2

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Observation d9268468-903e-4678-a8a1-a516b1dbfa30 · outbound

This paper cites Jacobs and Michael I.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Jacobs and Michael I

Reference 3

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Observation 02b86140-15df-4e37-959b-0bdf8ce43215 · outbound

This paper cites Jordan and Robert A.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Jordan and Robert A

Reference 4

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Observation 3f7be225-9697-42e1-8973-33201d962c6e · outbound

This paper cites Le and Geoffrey E.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Le and Geoffrey E

Reference 5

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Observation 8ed88e22-426c-44ea-9791-2514d1dd7bfc · outbound

This paper cites an unresolved cited work.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Unresolved cited work

Reference 6

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Observation 114358a5-b7d4-49af-8924-e659a9444938 · outbound

This paper cites 9th International Conference on Learning Representations,.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs 9th International Conference on Learning Representations,

Reference 7

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Observation 3ddf5dde-b2f6-436d-bb4c-d0f216902d4c · outbound

This paper cites an unresolved cited work.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Unresolved cited work

Reference 8

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Observation 61c82a74-a6e6-432b-8758-65469e81c69c · outbound

This paper cites Zhao and Andrew M.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Zhao and Andrew M

Reference 9

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Observation 67f495f4-0cb9-4803-8f3e-888f73ec96ef · outbound

This paper cites Parallel Scaling Law for Language Models.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Parallel Scaling Law for Language Models

Reference 10

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Observation b47d75da-56f1-4c3d-9b52-11064ae18ed5 · outbound

This paper cites Cutler and Nishanth Dikkala and Nikhil Ghosh and Rina Panigrahy and Xin Wang , editor =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Cutler and Nishanth Dikkala and Nikhil Ghosh and Rina Panigrahy and Xin Wang , editor =

Reference 11

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Observation 7d60712a-7073-4fe8-aeb0-845161cee736 · outbound

This paper cites Towards Understanding the Mixture-of-Experts Layer in Deep Learning , booktitle =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Towards Understanding the Mixture-of-Experts Layer in Deep Learning , booktitle =

Reference 12

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Observation 38d76e32-2bd6-4b47-8b4f-b09bf1e5af9a · outbound

This paper cites Proceedings of the 38th International Conference on Machine Learning,.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Proceedings of the 38th International Conference on Machine Learning,

Reference 13

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Observation 58419d10-4d5e-4675-8df7-eae560fbcf6d · outbound

This paper cites Dai and Simon Tong and Dmitry Lepikhin and Yuanzhong Xu and Maxim Krikun and Yanqi Zhou and Adams Wei Yu and Orhan Firat and Barret Zoph and Liam Fedus and Maarten P.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Dai and Simon Tong and Dmitry Lepikhin and Yuanzhong Xu and Maxim Krikun and Yanqi Zhou and Adams Wei Yu and Orhan Firat and Barret Zoph and Liam Fedus and Maarten P

Reference 14

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Observation b1b9d193-8e6b-41ea-baf3-4565c69c6a59 · outbound

This paper cites DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation

Reference 15

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Observation 3beb0c2d-1a91-4b1c-a9e6-4a8afd8d21a7 · outbound

This paper cites Le and Jiquan Ngiam , editor =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Le and Jiquan Ngiam , editor =

Reference 16

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Observation 7c79c8e5-f379-4f7b-bcce-007fc7ebdc74 · outbound

This paper cites Dauphin and Michael Auli , title =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Dauphin and Michael Auli , title =

Reference 17

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Observation 4a4829d4-1912-481e-9cfe-339e77068b97 · outbound

This paper cites WeightNet: Revisiting the Design Space of Weight Networks , booktitle =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs WeightNet: Revisiting the Design Space of Weight Networks , booktitle =

Reference 18

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Observation 5f25401f-e77a-44f8-82a6-a9afef044af0 · outbound

This paper cites Dynamic Filter Networks , booktitle =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Dynamic Filter Networks , booktitle =

Reference 19

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Observation e0857d47-689e-4c71-a06f-81e0d0710dc0 · outbound

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cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Unresolved cited work

Reference 20

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Observation 6a2eaf19-ef6b-457f-8123-e0b4504e97b3 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 21

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Observation c85e67ba-5e73-4102-bbb4-c9e33570fe7f · outbound

This paper cites 6th International Conference on Learning Representations,.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs 6th International Conference on Learning Representations,

Reference 22

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Observation a81bf01c-dcb0-402a-bc90-c2702a3512f0 · outbound

This paper cites Hu and Yelong Shen and Phillip Wallis and Zeyuan Allen.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Hu and Yelong Shen and Phillip Wallis and Zeyuan Allen

Reference 23

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Observation 5423ea1a-18ee-4a40-9089-85bec49c75fe · outbound

This paper cites Parameter-Efficient Transfer Learning for.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Parameter-Efficient Transfer Learning for

Reference 24

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Observation c4bcbd88-72ed-402d-a1dc-3a8d5180db21 · outbound

This paper cites Gomez and Lukasz Kaiser and Illia Polosukhin , editor =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Gomez and Lukasz Kaiser and Illia Polosukhin , editor =

Reference 25

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Observation c0a151d9-2e23-4179-9e33-9e06e9a776e2 · outbound

This paper cites 2019 , institution =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs 2019 , institution =

Reference 26

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Observation 5640fc16-8aad-4f20-8caa-e580de315e50 · outbound

This paper cites an unresolved cited work.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Unresolved cited work

Reference 27

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Observation 4cc22c42-08cb-4beb-b879-151b4a453569 · outbound

This paper cites The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale , booktitle =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale , booktitle =

Reference 28

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Observation b731d55b-69a0-4e42-b6b3-e518a65bf97b · outbound

This paper cites Bowman , title =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Bowman , title =

Reference 29

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Observation 2fe705c4-f82c-4d5f-b696-0cb499350739 · outbound

This paper cites Bowman , editor =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Bowman , editor =

Reference 30

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Observation 171fa4b0-4cf0-4ea2-bf32-ebabecb768fb · outbound

This paper cites SQuAD: 100, 000+ Questions for Machine Comprehension of Text , booktitle =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs SQuAD: 100, 000+ Questions for Machine Comprehension of Text , booktitle =

Reference 31

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Observation d4b13ef9-077d-443c-8b0b-7b325cf7506c · outbound

This paper cites Weld and Luke Zettlemoyer , editor =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Weld and Luke Zettlemoyer , editor =

Reference 32

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Observation 1d46c7b4-5ea2-4462-911f-5d601dd0b592 · outbound

This paper cites Scaling Vision with Sparse Mixture of Experts , booktitle =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Scaling Vision with Sparse Mixture of Experts , booktitle =

Reference 33

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cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs 2025 , url =

Reference 34

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Observation d9e98c6f-42ec-4204-94e0-adb6cd0c5047 · outbound

This paper cites A Survey on Inference Optimization Techniques for Mixture of Experts Models , journal =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs A Survey on Inference Optimization Techniques for Mixture of Experts Models , journal =

Reference 35

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Observation 8699a2d3-8215-4db0-af01-c0a140268791 · outbound

This paper cites CoRR , volume =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs CoRR , volume =

Reference 36

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Observation 3dca17f8-b79e-455f-83cf-d0116471d397 · outbound

This paper cites Deciding How to Decide: Dynamic Routing in Artificial Neural Networks , booktitle =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Deciding How to Decide: Dynamic Routing in Artificial Neural Networks , booktitle =

Reference 37

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Observation d8e2e6c9-56e8-43a2-adc9-5c2c1e43bf81 · outbound

This paper cites DyNet: Dynamic Convolution for Accelerating Convolutional Neural Networks.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs DyNet: Dynamic Convolution for Accelerating Convolutional Neural Networks

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-02T12:12:35.715372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:12:35.715372Z digest=sha256:4c25c5695b00a858667f13b3df1d81cacc71017bf8f7e94168dc057ff0e1fe22

Observation de9479dc-3cf7-4181-8356-283fe73bf320 · outbound

This paper cites CoRR , volume =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs CoRR , volume =

Reference 39

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unresolved
no resolver link, observed 2026-08-02T12:12:35.718674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:12:35.718674Z digest=sha256:93f25ec66b52c4a240e18f1f47bfb81532cc8cfa5ea03f13ab5c6a5715c98af2

Observation f2224c33-51b5-43a5-97a9-17b8e378c306 · outbound

This paper cites CoRR , volume =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs CoRR , volume =

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-08-02T12:13:24.409207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-02T12:12:35.721857Z digest=sha256:47141dd4af895219fe76a1ea2f0f0be4146bd7a72e75f8b6fc6bd612c2c9c53d

Observation d1ee4319-2156-44e0-bad1-2c77e2bfa5da · outbound

This paper cites 2025 , howpublished =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs 2025 , howpublished =

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-02T12:12:35.724792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:12:35.724792Z digest=sha256:021b3cd31bce8df8e23c9c9a5f5f8ef536818474581ad95ff4ad6325defdba88

Observation 668c01b4-2b65-4e4e-b8b6-096306118662 · outbound

This paper cites 2025 , url =.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs 2025 , url =

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-02T12:12:35.727863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:12:35.727863Z digest=sha256:eaa940ed95cb042d90bcad339a7a77be0a5b3fcd1332255e69ce8405440f15a7

Pith citing papers

No inbound Pith citation observations are available.