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Paper Citation Record · LEDGER

Overcoming the Communication-Performance Tradeoff in LLM Pretraining

As of 20 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 9 inbound Pith citation observations for arXiv:2508.15706.

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

pith.paper-citation-record.v1
2508.15706 v3

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:50:42.853083Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:45:28.702340Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

32 of 32 outbound references displayed

  • verified exact2
  • verified fuzzy7
  • unresolved20
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch1

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 6221515e-e182-4be1-823f-8309dee29e8b · outbound

This paper cites 16 Preprint Table 12: Final validation loss for the 178M model while varying the number of workers (R∈ {8,16,32}) and the communication interval (H∈ {15,50,100}).Bestis bold.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining 16 Preprint Table 12: Final validation loss for the 178M model while varying the number of workers (R∈ {8,16,32}) and the communication interval (H∈ {15,50,100}).Bestis bold

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 02098e63-497e-48e5-b296-5fcc499f8ff9 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Training Compute-Optimal Large Language Models

Reference 6

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source=pdf_text observed=2026-08-05T17:50:42.630685Z digest=sha256:a7d8f175aee2dec51b94790a4d59c6488eca982aa3d88ae7fdf903466aeab9e8

Observation 63df926d-8e53-4189-88e7-22d9e4ffa8e5 · outbound

This paper cites INTELLECT-1 Technical Report.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining INTELLECT-1 Technical Report

Reference 8

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source=pdf_text observed=2026-08-05T17:50:42.768010Z digest=sha256:9189f81cfd0fb4a608683921f0553bdad8c9c9a35e3d11d4520b7ad8899b881f

Observation bf1d3653-3e5a-48ba-a4f7-dd2cbb1f5aa0 · outbound

This paper cites Noise Is Not the Main Factor Behind the Gap Between SGD and Adam on Transformers, but Sign Descent Might Be.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Noise Is Not the Main Factor Behind the Gap Between SGD and Adam on Transformers, but Sign Descent Might Be

Reference 11

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source=pdf_text observed=2026-08-05T17:50:42.783058Z digest=sha256:69670b38c9c7ce4191e1663dd8da9255395e3a137bf1f426c89fb151040738a8

Observation a45babaf-8826-4cf5-87ea-5c08e4a1d170 · outbound

This paper cites an unresolved cited work.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Unresolved cited work

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T17:50:42.786073Z digest=sha256:bf1cb8a736c2b48d119b7c83e02848a36707ac46d685c8d1da105aa1b0406e51

Observation 77bef573-8aeb-4a55-b5b4-a2b3846e9218 · outbound

This paper cites Shigang Li and Torsten Hoefler.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Shigang Li and Torsten Hoefler

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T17:50:42.789216Z digest=sha256:26b9901b1ab08051925b2cb774525cbed95ee7d38c8cc1855dcde0cada6accff

Observation 1e9f20c1-531a-4430-ae6f-0a1001da84c6 · outbound

This paper cites Federated optimization in heterogeneous networks.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Federated optimization in heterogeneous networks

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T17:50:42.793019Z digest=sha256:a63b4047ccc90d730bcf5e79bfd8dfd5ebfaa4fcd5b9bf4c0eb33ba3b7e5f7cb

Observation 0c0f2604-2fcd-4c56-98ed-9444dc80d49b · outbound

This paper cites Incentivizing Permissionless Distributed Learning of LLMs.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Incentivizing Permissionless Distributed Learning of LLMs

Reference 15

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local_arxiv, observed 2026-08-05T17:50:43.162053Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T17:50:42.795875Z digest=sha256:e05842b014e9dd5766d742eed0cb651650f6a54ac0e96aaa4fb60e04b1cd3804

Observation b85900f8-f8d3-49e3-8353-904a2293331a · outbound

This paper cites Don't Use Large Mini-Batches, Use Local SGD.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Don't Use Large Mini-Batches, Use Local SGD

Reference 16

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source=pdf_text observed=2026-08-05T17:50:42.798739Z digest=sha256:a1a7ab68ec97d81cf1e6a9a8c9fe19f731a2e090cc9bd9a98a102b3a05f3cc84

Observation fd604448-d23b-4e34-a966-a2ad89c2f040 · outbound

This paper cites Trade-offs of Local SGD at Scale: An Empirical Study.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Trade-offs of Local SGD at Scale: An Empirical Study

Reference 18

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local_arxiv, observed 2026-08-05T17:50:43.123584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T17:50:42.805050Z digest=sha256:12d96635ff1e768bb9d1d96bdf495b95008d6575352b3fc82f458005ad4f4db2

Observation 76434ade-3f92-47d1-995a-cf1f69e543e0 · outbound

This paper cites Adaptive Federated Optimization.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Adaptive Federated Optimization

Reference 20

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source=pdf_text observed=2026-08-05T17:50:42.811192Z digest=sha256:e4d454c9d5b0d18ed33d3e31ec4e962807e0171ac8720fbc0bafbd38762e3860

Observation 4a93db86-469d-456f-8eb1-fbe2d0c37ee1 · outbound

This paper cites Fedpaq: A communication-efficient federated learning method with periodic averaging and quan- tization.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Fedpaq: A communication-efficient federated learning method with periodic averaging and quan- tization

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T17:50:42.814455Z digest=sha256:2b666b698c9c8f698ae57a6dc6054b995bf7196042e7434e931c1eb4b9629a97

Observation f54a0ab4-e55b-46fc-a858-74364dacdff9 · outbound

This paper cites Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, and Raman Arora.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, and Raman Arora

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T17:50:42.817061Z digest=sha256:d7ad75f90a3b00f69cdba2ed945a228737bc1e6637e66388edc97cf9c13cfa27

Observation e9ceadcd-49c7-4772-b107-db8fe1eada13 · outbound

This paper cites Frank Seide, Hao Fu, Jasha Droppo, Gang Li, and Dong Yu.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Frank Seide, Hao Fu, Jasha Droppo, Gang Li, and Dong Yu

Reference 23

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raw_fallback, observed 2026-08-05T17:50:43.348698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T17:50:42.819836Z digest=sha256:1d83dd614c36e8ed5e97f299b23b82ee0ad6d049cc1d47304e9f815160054b2d

Observation cfda8956-9216-4fbf-abad-c3a3e96ce514 · outbound

This paper cites Local SGD Converges Fast and Communicates Little.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Local SGD Converges Fast and Communicates Little

Reference 25

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source=pdf_text observed=2026-08-05T17:50:42.825545Z digest=sha256:62469f42bb1332408317dce7805cb90982044f20a04a080e1a9746501f39687e

Observation c7b2f858-94bd-43c9-aaa2-4f663a26e2d7 · outbound

This paper cites The Error-Feedback Framework: Better Rates for SGD with Delayed Gradients and Compressed Communication.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining The Error-Feedback Framework: Better Rates for SGD with Delayed Gradients and Compressed Communication

Reference 27

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source=pdf_text observed=2026-08-05T17:50:42.832022Z digest=sha256:43452dffd734fc3dda6a5f081daae21452d8a0f1f2b5c2626214aebdcf99b52b

Observation cfa86fd4-b77c-4429-a9d6-4c88b674ac0b · outbound

This paper cites MuLoCo: Muon is a practical inner optimizer for DiLoCo.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining MuLoCo: Muon is a practical inner optimizer for DiLoCo

Reference 28

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source=pdf_text observed=2026-08-05T17:50:42.834629Z digest=sha256:6bc11e6ab8fa780517da4d30345e9ddab084ffa1dc37d4d736a2477a8ca5ccc9

Observation bc7ce4e6-e092-4508-84f9-ee6e9fb245d7 · outbound

This paper cites Powersgd: Practical low-rank gra- dient compression for distributed optimization.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Powersgd: Practical low-rank gra- dient compression for distributed optimization

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T17:50:42.837941Z digest=sha256:d415b78a5458745084f5bdbbfe461e0e7574da06fa04947bab56edf046270d5e

Observation 319545ff-8ff6-45a6-bd7d-c89389b22308 · outbound

This paper cites SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum

Reference 30

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source=pdf_text observed=2026-08-05T17:50:42.840735Z digest=sha256:f9d7e5214ce1c349f015b34d541dd55310e3d9c8485dfd0b913a4b4cd85116ac

Observation cb840401-95b0-47c9-8ce9-921e70a0c235 · outbound

This paper cites 12 Preprint Prateek Yadav, Derek Tam, Leshem Choshen, Colin Raffel, and Mohit Bansal.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining 12 Preprint Prateek Yadav, Derek Tam, Leshem Choshen, Colin Raffel, and Mohit Bansal

Reference 31

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source=pdf_text observed=2026-08-05T17:50:42.843800Z digest=sha256:a5132044b2a216d47a9a8903361093750fb62788a8da5aa413b52c3ecf2b5ba2

Observation 0b5e8ceb-46a3-4688-9858-41b8c4b4d0c1 · outbound

This paper cites TIES-Merging: Resolving Interference When Merging Models.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining TIES-Merging: Resolving Interference When Merging Models

Reference 32

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source=pdf_text observed=2026-08-05T17:50:42.846515Z digest=sha256:15e4ad56be00b0efa619f998754bafc67c113a8d93944e0adb4bcbe419eaeafd

Observation 22f7550f-3658-46d9-98b9-5618ee0a8859 · outbound

This paper cites an unresolved cited work.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Unresolved cited work

Reference 33

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T17:50:42.850040Z digest=sha256:b0304fa3de2541fb7c0f4e0374693c6951c6fe1ed8f1da342986a76b470a8155

Observation b4982b35-9e66-4f74-905e-e11c073a41fe · outbound

This paper cites Understanding Top-k Sparsification in Distributed Deep Learning.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Understanding Top-k Sparsification in Distributed Deep Learning

Reference 2014

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source=pdf_text observed=2026-08-05T17:50:42.822540Z digest=sha256:9d484f02f68b02537e477aecfe5bcc0a8b3f605063e8207ab9dbb1de10beff61

Observation 9882bc39-c807-4627-80db-8146ef538214 · outbound

This paper cites Ilyas Fatkhullin, Alexander Tyurin, and Peter Richt´arik.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Ilyas Fatkhullin, Alexander Tyurin, and Peter Richt´arik

Reference 2016

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verified fuzzy
raw_fallback, observed 2026-08-05T17:50:43.405846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T17:50:42.460974Z digest=sha256:e2fc6e04326d4bff6052b81c1c62c8508d2e066f7a4c7e557ca84b5c0eb56084

Observation 705b1671-64c1-4608-8a81-a1538f6a8306 · outbound

This paper cites Optimizing the Communication-Accuracy Trade-off in Federated Learning with Rate-Distortion Theory.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Optimizing the Communication-Accuracy Trade-off in Federated Learning with Rate-Distortion Theory

Reference 2017

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local_arxiv, observed 2026-08-05T17:50:43.138006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T17:50:42.801755Z digest=sha256:6a0641424864e2beab4d74fb44bf4f8d45af13619c6785706ab91c7b6c151b1d

Observation 86d2e3ab-221c-43e8-9605-21c57eb89b87 · outbound

This paper cites Error Feedback Fixes SignSGD and other Gradient Compression Schemes.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Error Feedback Fixes SignSGD and other Gradient Compression Schemes

Reference 2019

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:50:42.775569Z digest=sha256:cc9bd0f88c009c481523355af98833f25d6d1729e42897e34dc5a52707cb4139

Observation ee5d3247-a933-498e-a5b7-1107f4133822 · outbound

This paper cites Federated Optimization: Distributed Machine Learning for On-Device Intelligence.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Federated Optimization: Distributed Machine Learning for On-Device Intelligence

Reference 2020

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:50:42.779456Z digest=sha256:c592020bf96073a5e8458c396eac6823def69219784c9de88eee2ea59a40526c

Observation a3705fd5-2814-4ef8-82cf-5495a7ca8831 · outbound

This paper cites Decoupled momentum optimization.arXiv preprint arXiv:2411.19870,.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Decoupled momentum optimization.arXiv preprint arXiv:2411.19870,

Reference 2021

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:50:42.808173Z digest=sha256:387aa04651949e46e3848a2f7ac30f878b90f7a1e3a958c814a20c664ce8ffae

Observation e163af05-5ad3-4b11-9034-c2322da03950 · outbound

This paper cites INTELLECT-1 Technical Report.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining INTELLECT-1 Technical Report

Reference 2022

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source=pdf_text observed=2026-08-05T17:50:42.668228Z digest=sha256:e944ea67d2f20a571d6b3f79307819aaaa6f9406e15b2ff8222669e1cea7eee3

Observation 2f595d93-b45a-42a4-8cd5-f81b06ca3339 · outbound

This paper cites WASH: Train your Ensemble with Communication-Efficient Weight Shuffling, then Average.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining WASH: Train your Ensemble with Communication-Efficient Weight Shuffling, then Average

Reference 2023

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source=pdf_text observed=2026-08-05T17:50:42.528727Z digest=sha256:ee09dc1166e8af2aab4751b49c7b8bce52836db51f57c023eb7132cc53692a88

Observation 56cd2afe-9f0a-41fd-a231-e5696fb4f400 · outbound

This paper cites DiLoCo: Distributed Low-Communication Training of Language Models.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining DiLoCo: Distributed Low-Communication Training of Language Models

Reference 2024

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source=pdf_text observed=2026-08-05T17:50:42.327928Z digest=sha256:4e74e1553278326d8bab1c87e89e07c3a1dd60b277f844dfa6593d1247b95988

Observation 89ce55a4-0b28-47c8-a9b6-6077f25d8c10 · outbound

This paper cites Debraj Basu, Deepesh Data, Can Karakus, and Suhas Diggavi.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining Debraj Basu, Deepesh Data, Can Karakus, and Suhas Diggavi

Reference 2025

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source=pdf_text observed=2026-08-05T17:50:42.224878Z digest=sha256:14878af04e62394e0de4e64fae9580bccdca48b946d04064500d17076c9dfa6a

Pith citing papers

Observation c154d6ed-ccdb-41eb-b8d5-14eba14dc59e · inbound

MuLoCo: Muon is a practical inner optimizer for DiLoCo cites this paper.

MuLoCo: Muon is a practical inner optimizer for DiLoCo Overcoming the Communication-Performance Tradeoff in LLM Pretraining

Reference 43

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no resolver link, observed 2026-08-07T12:45:28.702340Z

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source=arxiv_source observed=2026-08-07T12:45:28.702340Z digest=sha256:37eb105d1f4c7cafaeb0cd30e364fcfb4293cb295ba6a4a863d242ae0f823844

Observation 126fe051-41cf-4dbe-ad5b-43d896bd82b0 · inbound

Understanding and Exploiting Weight Update Sparsity for Communication-Efficient Distributed RL cites this paper.

Understanding and Exploiting Weight Update Sparsity for Communication-Efficient Distributed RL Overcoming the Communication-Performance Tradeoff in LLM Pretraining

Reference 19

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arxiv_id, observed 2026-07-24T02:22:54.639277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-21T13:37:20.114152Z digest=sha256:0999be19a852b2655f7bc6f217207279681eba26be10b38561a9dfef7a137537

Observation a68ffe5a-ef00-452d-a16c-cbcc61f46106 · inbound

LoRDO: Distributed Low-Rank Optimization with Infrequent Communication cites this paper.

LoRDO: Distributed Low-Rank Optimization with Infrequent Communication Overcoming the Communication-Performance Tradeoff in LLM Pretraining

Reference 17

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T04:44:55.982385Z digest=sha256:6be0cb7fed47bcdea4aeb7d1727c764048d45942e2bfcb964d873f29ad2002c0

Observation c0dcd1dc-464b-4c46-84c0-ed2d084ad204 · inbound

ResBM: Residual Bottleneck Models for Low-Bandwidth Pipeline Parallelism cites this paper.

ResBM: Residual Bottleneck Models for Low-Bandwidth Pipeline Parallelism Overcoming the Communication-Performance Tradeoff in LLM Pretraining

Reference 8

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verified exact
arxiv_id, observed 2026-07-24T02:22:54.639277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T16:36:15.760164Z digest=sha256:c0295436b2e42d247f7d3fee478739a1b82c66283ee5f664f8a0629f25e3a526

Observation 3646a5f2-e9f7-45ea-9aa6-f819aa2acaf6 · inbound

ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL cites this paper.

ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL Overcoming the Communication-Performance Tradeoff in LLM Pretraining

Reference 55

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arxiv_id, observed 2026-07-24T02:22:54.639277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-08T05:14:14.168753Z digest=sha256:11e111110f0e5564447d6425fb240896abd599a4a50550d7ad0e074f5fa104b3

Observation 9fb95a3d-52ce-4a82-ad20-b73f8a39e7da · inbound

ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL cites this paper.

ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL Overcoming the Communication-Performance Tradeoff in LLM Pretraining

Reference 54

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arxiv_id, observed 2026-07-24T02:22:54.639277Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-21T08:39:31.911497Z digest=sha256:42c2f53de7cd2035f9b790a2ae1681f24e7defbe3fb565a349bcc783d86de9a9

Observation 6cc8a123-c7b5-4134-83e1-63c5c4fb1c83 · inbound

Learned Subspace Compression for Communication-Efficient Pipeline Parallelism cites this paper.

Learned Subspace Compression for Communication-Efficient Pipeline Parallelism Overcoming the Communication-Performance Tradeoff in LLM Pretraining

Reference 46

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arxiv_id, observed 2026-07-24T02:22:54.639277Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-28T06:41:58.301482Z digest=sha256:09a81f9d708a4179a4bf8fb9a6670858ff82beb597738ac8196526e84a6cf5d6

Observation bc42eb0a-9ce7-46ac-9282-99f3de76e69b · inbound

Unifying Local Communications and Local Updates for LLM Pretraining cites this paper.

Unifying Local Communications and Local Updates for LLM Pretraining Overcoming the Communication-Performance Tradeoff in LLM Pretraining

Reference 29

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arxiv_id, observed 2026-07-24T02:22:54.639277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-27T14:07:42.062805Z digest=sha256:02d21294a7a2a209d87bfddf435d72830b4fd5e5a38b4fe7005b6a5f8b20135b

Observation abe9d0ca-ee98-467a-870c-9ed1dcc00a57 · inbound

FoMoE: Breaking the Full-Replica Barrier with a Federation of MoEs cites this paper.

FoMoE: Breaking the Full-Replica Barrier with a Federation of MoEs Overcoming the Communication-Performance Tradeoff in LLM Pretraining

Reference 143

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arxiv_id, observed 2026-07-24T02:22:54.639277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-26T21:25:15.709652Z digest=sha256:a58f1b8cb44bc448ea857ca9c1dc14ea5a6fff2f4d4aa9ea5e8a7656073d7d10