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Paper Citation Record Β· LEDGER

Nesterov Method for Asynchronous Pipeline Parallel Optimization

As of 17 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 2 inbound Pith citation observations for arXiv:2505.01099.

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

pith.paper-citation-record.v1
2505.01099 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:33:18.162390Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T06:41:55.732230Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:57:09.417491Z

Reference resolution

15 of 15 outbound references displayed

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  • verified fuzzy5
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6cd016a3-a827-4f24-a7d4-777fb5dd6827 Β· outbound

This paper cites Now, to enable telescoping sum, we want, πœ†π‘‘Β―h𝑑 + w𝑑 +πœ†π‘‘dπ‘‘βˆ’ w* = w𝑑+1 +πœ†π‘‘+1d𝑑+1βˆ’ w* = w𝑑 + d𝑑 + Β―h𝑑 +πœ†π‘‘+1𝛾𝑑+1(d𝑑 + Β―h𝑑)βˆ’ w*.

Nesterov Method for Asynchronous Pipeline Parallel Optimization Now, to enable telescoping sum, we want, πœ†π‘‘Β―h𝑑 + w𝑑 +πœ†π‘‘dπ‘‘βˆ’ w* = w𝑑+1 +πœ†π‘‘+1d𝑑+1βˆ’ w* = w𝑑 + d𝑑 + Β―h𝑑 +πœ†π‘‘+1𝛾𝑑+1(d𝑑 + Β―h𝑑)βˆ’ w*

Reference 1

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation c32af626-ada4-4561-a99e-1d4f354de55b Β· outbound

This paper cites Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays.

Nesterov Method for Asynchronous Pipeline Parallel Optimization Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays

Reference 10

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source=pdf_text observed=2026-08-16T04:33:18.142975Z digest=sha256:c14a66daebfab5555bdf82736fc1b38d7c8fb5b1689fde47324c20be5391ac3d

Observation aa5e9492-7b52-40ed-93f2-39caaf8dcfc8 Β· outbound

This paper cites Asynchrony begets momentum, with an application to deep learning.

Nesterov Method for Asynchronous Pipeline Parallel Optimization Asynchrony begets momentum, with an application to deep learning

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:33:18.146879Z digest=sha256:86623f6b958d6db12dfebbc67b40cb5b0d36f5a2e1aacc507dd7ea748d686489

Observation daa8b81a-0093-4bd6-abf6-461c1f430af7 Β· outbound

This paper cites Max Ryabinin, Alexander Borzunov, Michael Diskin, Anton Gusev, Denis Mazur, Vsevolod Plokhot- nyuk, Alexey Bukhtiyarov, Pavel Samygin, Anton Sinitsin, and Artem Chumachenko.

Nesterov Method for Asynchronous Pipeline Parallel Optimization Max Ryabinin, Alexander Borzunov, Michael Diskin, Anton Gusev, Denis Mazur, Vsevolod Plokhot- nyuk, Alexey Bukhtiyarov, Pavel Samygin, Anton Sinitsin, and Artem Chumachenko

Reference 13

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:33:18.154766Z digest=sha256:379f3c451cb637c5e5fc247308a2eb7794c6eed4a009a3c9a28c57c9091a3458

Observation 08522034-655a-4ead-b40b-9968d9265051 Β· outbound

This paper cites Language models are few-shot learners.

Nesterov Method for Asynchronous Pipeline Parallel Optimization Language models are few-shot learners

Reference 2004

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:33:18.116212Z digest=sha256:800d5153fa047968588e31e40572f360031a04bda538571ab09ae2a9a87e97b6

Observation 62d113df-7b33-4911-9c7c-ff5937abacce Β· outbound

This paper cites Advances in asynchronous parallel and distributed optimization.

Nesterov Method for Asynchronous Pipeline Parallel Optimization Advances in asynchronous parallel and distributed optimization

Reference 2011

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:33:18.108463Z digest=sha256:04eb14dceb19d6070b5d89452ab0668777a9291a662ad0b4659ca332267d50c5

Observation 7443af50-4f89-4810-b2d0-f17a11956b9b Β· outbound

This paper cites DeepSeek-V3 Technical Report.

Nesterov Method for Asynchronous Pipeline Parallel Optimization DeepSeek-V3 Technical Report

Reference 2014

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source=pdf_text observed=2026-08-16T04:33:18.139427Z digest=sha256:70bb15ecf155332d98c3a78309e2816306cd0c5208f284bae2ba2eaf058ef3d0

Observation 3fd4e7a3-dcb0-40dc-9765-de4d9b5941d9 Β· outbound

This paper cites Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform.

Nesterov Method for Asynchronous Pipeline Parallel Optimization Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform

Reference 2015

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source=pdf_text observed=2026-08-16T04:33:18.119891Z digest=sha256:303e99176acca4b342e9bef1e435546d4769bf1a38b54a3c7d12026d6c4732b8

Observation eca3eaee-feb5-451b-aa17-7ee4f2267dcc Β· outbound

This paper cites The Llama 3 Herd of Models.

Nesterov Method for Asynchronous Pipeline Parallel Optimization The Llama 3 Herd of Models

Reference 2016

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source=pdf_text observed=2026-08-16T04:33:18.123712Z digest=sha256:8c951fd1263a5819a8bf2604b4c79ce97b20376a0c356ac10b5f7745a4d2445a

Observation 6263b47d-7a6d-4a0d-9dc7-801cdcd5a309 Β· outbound

This paper cites XPipe: Efficient Pipeline Model Parallelism for Multi-GPU DNN Training.

Nesterov Method for Asynchronous Pipeline Parallel Optimization XPipe: Efficient Pipeline Model Parallelism for Multi-GPU DNN Training

Reference 2019

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source=pdf_text observed=2026-08-16T04:33:18.127596Z digest=sha256:40703c79628f5263f8883e5c63d35064a9d3663360a3dbd322b97c9fb65c3cc7

Observation a3486c1a-1f31-42ec-90fa-93f15d60b108 Β· outbound

This paper cites Gap Aware Mitigation of Gradient Staleness.

Nesterov Method for Asynchronous Pipeline Parallel Optimization Gap Aware Mitigation of Gradient Staleness

Reference 2020

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source=pdf_text observed=2026-08-16T04:33:18.112310Z digest=sha256:d10ce9403b53d3ff57e5effbb9741067be4df5a5c2a9b66d37a1a0879fff8223

Observation 11340616-e711-4c5d-bb51-69ec3357c693 Β· outbound

This paper cites Adam: A Method for Stochastic Optimization.

Nesterov Method for Asynchronous Pipeline Parallel Optimization Adam: A Method for Stochastic Optimization

Reference 2022

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source=pdf_text observed=2026-08-16T04:33:18.135471Z digest=sha256:7174f447cd796388cbbfb8a5eb65067fc7ecbaf029a5736422e5a9a3440a6479

Observation 9cea2d2c-3dbc-4ac9-8593-e7bb9983b6cf Β· outbound

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

Nesterov Method for Asynchronous Pipeline Parallel Optimization The Error-Feedback Framework: Better Rates for SGD with Delayed Gradients and Compressed Communication

Reference 2023

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source=pdf_text observed=2026-08-16T04:33:18.158765Z digest=sha256:0dbfcdf08a0b71a2f32603e0ebcfadc121ede959e0e490d2ddfc1a03e4d6eaef

Observation b087d70e-8c01-4fd7-a878-8507f1a172dd Β· outbound

This paper cites Taming Momentum in a Distributed Asynchronous Environment.

Nesterov Method for Asynchronous Pipeline Parallel Optimization Taming Momentum in a Distributed Asynchronous Environment

Reference 2024

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source=pdf_text observed=2026-08-16T04:33:18.131529Z digest=sha256:a6a3819618b6caf299b930c8b62a7c7e675556322f5f56e6d1f1be6f117197f8

Observation 7e5cb269-4d7e-4837-b501-baddecfc3d6b Β· outbound

This paper cites Zero Bubble Pipeline Parallelism.

Nesterov Method for Asynchronous Pipeline Parallel Optimization Zero Bubble Pipeline Parallelism

Reference 2025

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source=pdf_text observed=2026-08-16T04:33:18.151163Z digest=sha256:9c6bf5568d9bd800e20672e92b33cc576519262b068ea079d71cb2242d3d2406

Pith citing papers

Observation 136c4d28-48f5-4862-841a-0f2d7451a81e Β· inbound

Breaking the Bubble: Asynchronous Pipeline Parallel Training with Bounded Weight Inconsistency cites this paper.

Breaking the Bubble: Asynchronous Pipeline Parallel Training with Bounded Weight Inconsistency Nesterov Method for Asynchronous Pipeline Parallel Optimization

Reference 1

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arxiv_id, observed 2026-07-02T16:57:09.419832Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-27T22:19:15.307830Z digest=sha256:26ee477bc72ab924dacc52b45fc270a907d80239fc8b485970432e6d2cdc9e35

Observation bfc4c18a-7763-4ebc-a7dd-0c21d091d0db Β· inbound

One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining cites this paper.

One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining Nesterov Method for Asynchronous Pipeline Parallel Optimization

Reference 2

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-30T06:41:55.732230Z digest=sha256:262f1035b210dbad86eaeedfd2e116849160793d7956987df3b08bf8e64559c7