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Paper Citation Record · LEDGER

On Stochastic Rounding with Few Random Bits

As of 20 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2504.20634.

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

pith.paper-citation-record.v1
2504.20634 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:36:11.715272Z

measured 14 of 14 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 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

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

Source: cited_works

Reference resolution

14 of 14 outbound references displayed

  • verified exact1
  • verified fuzzy11
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 88d9b2ed-17b1-49c7-896d-8862786e39b2 · outbound

This paper cites Dynamic point stochastic rounding algorithm for limited precision arithmetic in deep belief network training,.

On Stochastic Rounding with Few Random Bits Dynamic point stochastic rounding algorithm for limited precision arithmetic in deep belief network training,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:36:11.956139Z

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 3c341977-195c-4989-8e1a-7882fbac0a1e · outbound

This paper cites 8-bit Numerical Formats for Deep Neural Networks.

On Stochastic Rounding with Few Random Bits 8-bit Numerical Formats for Deep Neural Networks

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-16T05:36:11.660412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:36:11.660412Z digest=sha256:d225b7589d8b9560b9a2dd38857ff11a95d404be209ca9f81faa4965bfb1efba

Observation 35d8c057-f28e-4cab-99ad-9fddbbb4353d · outbound

This paper cites Climate modeling in low precision: Effects of both deterministic and stochastic rounding,.

On Stochastic Rounding with Few Random Bits Climate modeling in low precision: Effects of both deterministic and stochastic rounding,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:36:11.942149Z

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=2026-08-16T05:36:11.665421Z digest=sha256:636584f5f11273b3aa09a8ddac2bfb0303f675d1af3a9fc552fe14f79c48b8b2

Observation d87e8ed8-03e1-45c3-abb9-e803b23fa7bc · outbound

This paper cites Fast: DNN training under variable precision block floating point with stochastic rounding,.

On Stochastic Rounding with Few Random Bits Fast: DNN training under variable precision block floating point with stochastic rounding,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:36:11.927102Z

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=2026-08-16T05:36:11.670776Z digest=sha256:0eef05db3c64fe05258029526896a339273f068debe7f69703adbeaee6d7b4f0

Observation ae33ad5a-2ab5-4b93-a3ca-912755ee6164 · outbound

This paper cites Effects of round-to-nearest and stochastic rounding in the numerical solution of the heat equation in low precision,.

On Stochastic Rounding with Few Random Bits Effects of round-to-nearest and stochastic rounding in the numerical solution of the heat equation in low precision,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:36:11.912182Z

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=2026-08-16T05:36:11.675483Z digest=sha256:f9a208fda2d52567205b4497d2dd13cf866e0307d12f28dbb0b5a1b0f7ebdb37

Observation 19670d27-7807-4519-8ade-5bc2fb4ba589 · outbound

This paper cites Stochastic rounding: implementation, error analysis and applications,.

On Stochastic Rounding with Few Random Bits Stochastic rounding: implementation, error analysis and applications,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:36:11.897031Z

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=2026-08-16T05:36:11.680048Z digest=sha256:128e84a1d79747f7a1329c0f1138542d77fbff600949bb388d68ef809335082a

Observation ab5130ef-f5b4-4f16-9ea2-e1452e34156c · outbound

This paper cites Stochastic rounding variance and probabilistic bounds: A new approach,.

On Stochastic Rounding with Few Random Bits Stochastic rounding variance and probabilistic bounds: A new approach,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:36:11.882107Z

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=2026-08-16T05:36:11.684833Z digest=sha256:78b8d6354f785c50659d1c0ac4a582597719f1520802da4039e77a2099790b1c

Observation 4a11f3af-c243-4295-b2f9-08222ccc6b76 · outbound

This paper cites Probabilistic error analysis of limited-precision stochastic rounding.

On Stochastic Rounding with Few Random Bits Probabilistic error analysis of limited-precision stochastic rounding

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-16T05:36:11.770145Z

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=2026-08-16T05:36:11.689078Z digest=sha256:932f831bcc65a1ffb3eb8dcc20cf91e4b6449cf28e08a9ff9bfa35e7f27cea2a

Observation 5feb34c5-9684-45a5-ab2f-78fbb0fd5adb · outbound

This paper cites Improved stochastic rounding.

On Stochastic Rounding with Few Random Bits Improved stochastic rounding

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-16T05:36:11.693389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:36:11.693389Z digest=sha256:6ab14613ada2c83ca004c4dfff06d08f3c61b205a9fa6965c9ac71716e53ea4f

Observation 5d7e6af0-5544-4dcb-b719-f5d576bc86e3 · outbound

This paper cites You already have it: A generator-free low- precision DNN training framework using stochastic rounding,.

On Stochastic Rounding with Few Random Bits You already have it: A generator-free low- precision DNN training framework using stochastic rounding,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:36:11.863706Z

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=2026-08-16T05:36:11.697983Z digest=sha256:7996e070fd32e777bfc01d57db77369fbc961323ff3e84d5d5a7b9d39b0ccebc

Observation 2c18d076-002a-4b9a-bb65-c9f09d8cf0d1 · outbound

This paper cites Quantization-aware training for large language models with PyTorch,.

On Stochastic Rounding with Few Random Bits Quantization-aware training for large language models with PyTorch,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:36:11.848149Z

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=2026-08-16T05:36:11.702281Z digest=sha256:9e8e7ca0b1fa8f7ad622696d44efebbd4b30b2b7944b409d502c0c311353bfda

Observation ee179818-a968-4f81-b96b-3d74a95c95eb · outbound

This paper cites NanoGPT,.

On Stochastic Rounding with Few Random Bits NanoGPT,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:36:11.832334Z

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=2026-08-16T05:36:11.706384Z digest=sha256:c344090aa1e0db1984e196a5dd0e7f448d9781d30995ce439c14c8ca54bd8530

Observation b31c9037-b93e-45d8-829b-f9cdcd98f325 · outbound

This paper cites GFloat: Generic floating point formats in Python,.

On Stochastic Rounding with Few Random Bits GFloat: Generic floating point formats in Python,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:36:11.817074Z

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=2026-08-16T05:36:11.710978Z digest=sha256:849e5575a9000043a566bee8f66c247aaa11c02acb55f90f2a3b47a3b58d8291

Observation cf0c0907-d982-4776-a572-a0e84b582ab9 · outbound

This paper cites Interim report on binary floating-point formats for machine learning,.

On Stochastic Rounding with Few Random Bits Interim report on binary floating-point formats for machine learning,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:36:11.801965Z

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=2026-08-16T05:36:11.715272Z digest=sha256:34616ecd3ab052f2dab07d64d0aa0f9cc340b00488dfd3d6d1d60758604f77ec

Pith citing papers

No inbound Pith citation observations are available.