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Paper Citation Record · LEDGER

Incentivizing Permissionless Distributed Learning of LLMs

As of 8 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 1 inbound Pith citation observation for arXiv:2505.21684.

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

pith.paper-citation-record.v1
2505.21684 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:30:21.191030Z

measured 21 of 21 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:50:42.795875Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T17:50:43.158551Z

Reference resolution

20 of 20 outbound references displayed

  • verified exact2
  • verified fuzzy7
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 71d06f28-d8d0-49ab-9be8-8531856fe026 · outbound

This paper cites Dion: A communication-efficient optimizer for large models.

Incentivizing Permissionless Distributed Learning of LLMs Dion: A communication-efficient optimizer for large models

Reference 1

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unresolved
no resolver link, observed 2026-08-07T13:30:18.911867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:18.911867Z digest=sha256:e860b04b82f300d65bec07588d8442854abe56dcf8cf191a245e5bdaedfb8d43

Observation 90a663fc-25f3-4e17-b239-68b5ec71eef8 · outbound

This paper cites Verde: Verification via Refereed Delegation for Machine Learning Programs.

Incentivizing Permissionless Distributed Learning of LLMs Verde: Verification via Refereed Delegation for Machine Learning Programs

Reference 2

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unresolved
no resolver link, observed 2026-08-07T13:30:18.981644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:18.981644Z digest=sha256:d7f39b64f22868edac82979492737947cdeb1b8b6958363ee9f0ae6601e178ff

Observation 24bb72ec-4bec-4274-a20c-d2c3ca861d53 · outbound

This paper cites Training transformers together.

Incentivizing Permissionless Distributed Learning of LLMs Training transformers together

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:24.774936Z

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.

source=pdf_text observed=2026-08-07T13:30:19.064762Z digest=sha256:7dada9970c4ada992260348846e799c9630e79a386fdca92228e44d231f30f83

Observation 071f1e30-5c6f-4492-bf64-3c50eca7c604 · outbound

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

Incentivizing Permissionless Distributed Learning of LLMs DiLoCo: Distributed Low-Communication Training of Language Models

Reference 4

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unresolved
no resolver link, observed 2026-08-07T13:30:19.164843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:19.164843Z digest=sha256:5a8127aea7f533a91ac6da3d140211a10a3b8d5ec2772b0ea2d938736bcf0dbb

Observation 08ee0530-9bc9-442c-a3bc-95493a14085d · outbound

This paper cites Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour.

Incentivizing Permissionless Distributed Learning of LLMs Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Reference 5

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unresolved
no resolver link, observed 2026-08-07T13:30:19.229714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:19.229714Z digest=sha256:1f132bb7547dc843f2361ee018787d6da0a03a9b528bb1ed15398b64afa0c187

Observation 00911ebd-df77-41b9-9f9b-f5f8253a9625 · outbound

This paper cites INTELLECT-1 Technical Report.

Incentivizing Permissionless Distributed Learning of LLMs INTELLECT-1 Technical Report

Reference 6

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unresolved
no resolver link, observed 2026-08-07T13:30:19.364823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:19.364823Z digest=sha256:2439919cc8586a00cf94f276f1ba5edddbe905eccb62a0990b07e24c75e3b7a8

Observation 411b4fa5-8d18-40a9-a337-072ddc688936 · outbound

This paper cites Proof-of-learning: Definitions and practice.

Incentivizing Permissionless Distributed Learning of LLMs Proof-of-learning: Definitions and practice

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:24.514885Z

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.

source=pdf_text observed=2026-08-07T13:30:19.446094Z digest=sha256:32ad69f9dd152c1879b9bec0739e724eaa2d72c58afb4e42d40f81a42affd9c6

Observation e7b4c6dd-4207-45ea-9c23-7fccfe5fedb6 · outbound

This paper cites OpenSkill: A faster asymmetric multi-team, multiplayer rating system.

Incentivizing Permissionless Distributed Learning of LLMs OpenSkill: A faster asymmetric multi-team, multiplayer rating system

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:30:22.520576Z

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.

source=pdf_text observed=2026-08-07T13:30:19.532728Z digest=sha256:fe33e748b7c0fceee3bf8ae9fd2d1ba6a512935f03c99b9e203c72a37d8f4a02

Observation f744b9e0-54c2-44ac-8324-a49dd095bfb8 · outbound

This paper cites Error feedback fixes signsgd and other gradient compression schemes.

Incentivizing Permissionless Distributed Learning of LLMs Error feedback fixes signsgd and other gradient compression schemes

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T13:30:19.671117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:19.671117Z digest=sha256:b4641f3390e4d18a888ccb0956a140e2032126fbe8d71574ba10d5a16c6708c2

Observation 80c67255-b081-48f4-9de5-5d5e220a94f0 · outbound

This paper cites Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences.

Incentivizing Permissionless Distributed Learning of LLMs Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:30:22.224827Z

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.

source=pdf_text observed=2026-08-07T13:30:19.794923Z digest=sha256:574d022812d24b108db02ade690f45059ea454fe9cd3cc5c352131ec0fe0cf9d

Observation 555235df-03e4-4568-a42f-e48d2edd5e64 · outbound

This paper cites The fineweb datasets: Decanting the web for the finest text data at scale.

Incentivizing Permissionless Distributed Learning of LLMs The fineweb datasets: Decanting the web for the finest text data at scale

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-07T13:30:24.238630Z

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.

source=pdf_text observed=2026-08-07T13:30:19.958617Z digest=sha256:d354bbee651861d584fb28825e1b72fcdc4c9943eb7fc7eb47ced45ed51848a4

Observation b5c56abf-8d48-4c4d-9293-025a9824335c · outbound

This paper cites Decoupled momentum optimization.

Incentivizing Permissionless Distributed Learning of LLMs Decoupled momentum optimization

Reference 12

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unresolved
no resolver link, observed 2026-08-07T13:30:20.047809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:20.047809Z digest=sha256:bd4230473819edc86d93e8124a459ee841f1622ee0b1defaa80b44c4a0acbb3c

Observation c8769ec5-d5cc-4aa4-8ed9-0d58ea162613 · outbound

This paper cites Robust aggregation for federated learning.

Incentivizing Permissionless Distributed Learning of LLMs Robust aggregation for federated learning

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:24.085989Z

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.

source=pdf_text observed=2026-08-07T13:30:20.156195Z digest=sha256:b0cad7fd1577f4b28b32d4ebf260369f9a167df9d68cf2eaf089f3e02bd63402

Observation 12ba31d3-7903-493a-9f88-baa952a9ce39 · outbound

This paper cites Error compensated distributed sgd can be acceler- ated.

Incentivizing Permissionless Distributed Learning of LLMs Error compensated distributed sgd can be acceler- ated

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:23.945852Z

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.

source=pdf_text observed=2026-08-07T13:30:20.276354Z digest=sha256:35de6bd97b88d824a4dd02bcc9d95820350e01f3d60c654f46a8cc1a176b94a1

Observation 7a0f263c-4924-40f0-8a69-822ab6c8cfa1 · outbound

This paper cites Adaptive Federated Optimization.

Incentivizing Permissionless Distributed Learning of LLMs Adaptive Federated Optimization

Reference 15

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unresolved
no resolver link, observed 2026-08-07T13:30:20.436592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:20.436592Z digest=sha256:f9d5c8a59c41928c472d5d7a16f3afb6fa7909f882b6811ea07dad7c7440de42

Observation 2c5c9e9a-a28e-4f9c-8be1-1ddcfe7c7ce4 · outbound

This paper cites The Future of Large Language Model Pre-training is Federated.

Incentivizing Permissionless Distributed Learning of LLMs The Future of Large Language Model Pre-training is Federated

Reference 16

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unresolved
no resolver link, observed 2026-08-07T13:30:20.559975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:20.559975Z digest=sha256:de162d1acee952796dc5530afcff865cf491d236d6dae6c355acf8de9b050e23

Observation fe360e9a-7311-4540-916f-f8614cb9d405 · outbound

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

Incentivizing Permissionless Distributed Learning of LLMs Understanding Top-k Sparsification in Distributed Deep Learning

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T13:30:20.657655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:20.657655Z digest=sha256:489c500db3de36b3df1f86c1ce1a7427eadf8f2fc11a1a8cab731806ebe3688c

Observation 9dd4ddeb-3a93-42ac-9ef5-393f9bf367d2 · outbound

This paper cites Incentivizing intelligence: The bittensor approach, 2022.

Incentivizing Permissionless Distributed Learning of LLMs Incentivizing intelligence: The bittensor approach, 2022

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:23.754894Z

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.

source=pdf_text observed=2026-08-07T13:30:20.881500Z digest=sha256:ee533bf5797a0942ba74e30c3832b0be225c4d3bbf3003202e3bb97fb636acf8

Observation 1bb3d3ca-d05c-4f6b-8435-13e29d985437 · outbound

This paper cites Cocktailsgd: Fine-tuning foundation models over 500mbps networks.

Incentivizing Permissionless Distributed Learning of LLMs Cocktailsgd: Fine-tuning foundation models over 500mbps networks

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:23.435151Z

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.

source=pdf_text observed=2026-08-07T13:30:20.964991Z digest=sha256:a16b3455922fad705fb0d9e5e462b58be1a7a4488e231260e7df60fb37e6d9cf

Observation b0309c5a-d531-43da-a857-f8785fbe31a6 · outbound

This paper cites Generalized Byzantine-tolerant SGD.

Incentivizing Permissionless Distributed Learning of LLMs Generalized Byzantine-tolerant SGD

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T13:30:21.191030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:21.191030Z digest=sha256:094207b07af5ddd2ec3f0a04f3190c92f86d97d7de420208085611e35c36c617

Pith citing papers

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

Overcoming the Communication-Performance Tradeoff in LLM Pretraining cites this paper.

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

Reference 15

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

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.

source=pdf_text observed=2026-08-05T17:50:42.795875Z digest=sha256:eb80e6686bb875a156ffdd2c0c15ece0f16585fd00accf16dab5082b5dfdffd1