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Paper Citation Record · LEDGER

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models

As of 8 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 1 inbound Pith citation observation for arXiv:2508.18182.

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

pith.paper-citation-record.v1
2508.18182 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:36:50.562805Z

measured 13 of 13 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 2026-08-05T16:34:48.903774Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T16:34:48.928876Z

Reference resolution

12 of 12 outbound references displayed

  • verified exact2
  • verified fuzzy3
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9a9cfdc2-1215-45c2-89a2-0b9529789fc4 · outbound

This paper cites Adaptive Sampling Strategies for Stochastic Optimization.

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models Adaptive Sampling Strategies for Stochastic Optimization

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-05T16:36:50.830712Z

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=arxiv_source observed=2026-08-05T16:36:50.489347Z digest=sha256:260befbb9631ec07c8b6dc90f9a8c52c9c36e7f1b8d7c29bb5bf33a253533240

Observation 0dedbaec-4bce-41b4-bc00-a316b222f390 · outbound

This paper cites Byrd, Gillian M.

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models Byrd, Gillian M

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:36:50.949350Z

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=arxiv_source observed=2026-08-05T16:36:50.496519Z digest=sha256:36bfd413baec74f460cba5247bece3ee79eb789bb1bad50268a5b61729ef74a0

Observation d20fa830-0265-4a0b-8cef-3700bff4f7c1 · outbound

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

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models DiLoCo: Distributed Low-Communication Training of Language Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-05T16:36:50.502069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:36:50.502069Z digest=sha256:dbb89748efdbb181915a6b5ee8a8fa1007a9429315fd5a79cc32683960384e25

Observation c2240402-f84f-4bff-bf6b-e03ee30bc0a8 · outbound

This paper cites Adaptive subgradient methods for online learning and stochastic optimization.

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models Adaptive subgradient methods for online learning and stochastic optimization

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:36:50.919427Z

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=arxiv_source observed=2026-08-05T16:36:50.510950Z digest=sha256:3acf4e0e0c216565d5d14a4269a9209cfade839a4b9c4e5a8bcf6f6903440ccc

Observation f3fb0a2d-5752-45f3-9c02-a9c011bdbc33 · outbound

This paper cites Communication-Efficient Adaptive Batch Size Strategies for Distributed Local Gradient Methods.

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models Communication-Efficient Adaptive Batch Size Strategies for Distributed Local Gradient Methods

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-08-05T16:36:50.775729Z

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=arxiv_source observed=2026-08-05T16:36:50.517083Z digest=sha256:4ef521d6646947824e19ae32578629945b6e0d0571de8b187cd23720e69a07a9

Observation d73c9710-d506-4114-b18f-8aad88581f0c · outbound

This paper cites AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods.

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-05T16:36:50.522929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:36:50.522929Z digest=sha256:e4eb11c0749898f56d499295b8e2415f51b8a550e62e9d077aa281a9215c420d

Observation d83783d3-33d3-4d47-a3f5-abf2197918f1 · outbound

This paper cites Local SGD Converges Fast and Communicates Little.

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models Local SGD Converges Fast and Communicates Little

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-05T16:36:50.529584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:36:50.529584Z digest=sha256:e730b92ab57cc799b063ad2119be0294a0974d75c29d38cae72d025c6b41680f

Observation 34121115-5456-4696-b72b-d4227cc888ed · outbound

This paper cites Microllama: A 300m-parameter language model trained from scratch.

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models Microllama: A 300m-parameter language model trained from scratch

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:36:50.895404Z

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=arxiv_source observed=2026-08-05T16:36:50.535734Z digest=sha256:4c6e86b25faab4f0d14a5ade13eac339c78cb4b4af7c660597f24ac63805b3f7

Observation adfcd00d-5c64-48d2-aabc-d841230d7e95 · outbound

This paper cites write newline.

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models write newline

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T16:36:50.540026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:36:50.540026Z digest=sha256:4581fa604f3fde9f4ab7dbc6da5b360ad22674f9fc0e877bd9d70200bc74d76a

Observation e49ff0ef-618d-4131-afdd-51cb07683ae7 · outbound

This paper cites @esa (Ref.

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models @esa (Ref

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T16:36:50.548224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:36:50.548224Z digest=sha256:b9f2a5eb43ff8dc751d63fd16446a8187863b403b185c7c8b30ddac22c52f1c2

Observation b8ab24f6-bb8d-4714-b057-87857e9d4efd · outbound

This paper cites an unresolved cited work.

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models Unresolved cited work

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-05T16:36:50.556449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:36:50.556449Z digest=sha256:d29d81bee8f3f3ed7ad651d1246e54978e525c0046638eb6e346e9b8af287355

Observation 8c0c3f3f-decd-42c1-9808-1e904f37d80c · outbound

This paper cites 7 x4f [ @w떆d bQ̪̺;Y̬7.

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models 7 x4f [ @w떆d bQ̪̺;Y̬7

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T16:36:50.562805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:36:50.562805Z digest=sha256:452a811e9ca96c5b74eb9ddd30186e08c5707ae41496622d34b2a96cdd51ff04

Pith citing papers

Observation b6c6a4f1-e616-49e0-8f72-f3d0dca0b319 · inbound

What is digital about abstraction? cites this paper.

What is digital about abstraction? AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-05T16:34:48.933802Z

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=2026-08-05T16:34:48.903774Z digest=sha256:e10354461de136d25fa65301738262b65701a66523f04dfa05ffff9bc9276193