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Paper Citation Record · LEDGER

Fairness Dynamics During Training

As of 8 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2506.01709.

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

pith.paper-citation-record.v1
2506.01709 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:39:53.019573Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

19 of 19 outbound references displayed

  • verified exact2
  • verified fuzzy5
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7afc7335-f27f-4c4f-823b-825322ec63be · outbound

This paper cites Pythia: A suite for analyzing large language models across training and scaling.

Fairness Dynamics During Training Pythia: A suite for analyzing large language models across training and scaling

Reference 1

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unresolved
no resolver link, observed 2026-08-07T11:39:47.145238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:39:47.145238Z digest=sha256:953b36e4f54cfd74f65022d1c1fef2f954562bc827fcef1681a4b7784af9537c

Observation 4535d807-217b-48dd-82b9-bbb1b8f7868c · outbound

This paper cites Pretrained Language Model Embryology: The Birth of ALBERT.

Fairness Dynamics During Training Pretrained Language Model Embryology: The Birth of ALBERT

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:40:08.043528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:39:47.302319Z digest=sha256:3a1831cf1fceade429e239eeaa63ac4719aeb269676e1bcc2acd5ea24a0e79ff

Observation 13c82353-e767-4011-8cf6-54562ec132a2 · outbound

This paper cites Theories of “gender” in nlp bias research.

Fairness Dynamics During Training Theories of “gender” in nlp bias research

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-07T11:40:11.955541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:39:47.435358Z digest=sha256:5631f40f681b4f6f719941ea1a3a8788c7e784bb7c3c3d61b32ae912f0a3518a

Observation 6ca4d6c6-2752-44c6-abd3-496846ebadb5 · outbound

This paper cites On the impact of machine learning randomness on group fairness.

Fairness Dynamics During Training On the impact of machine learning randomness on group fairness

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-07T11:40:11.807877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:39:47.497059Z digest=sha256:e1b611f64f020939ab3900aceffa6fef25cfa702fd9a096af64a4babc9af90b3

Observation 793c9687-3c9e-457b-9c3c-a5801acf6cf9 · outbound

This paper cites Bigbench: Towards an industry standard benchmark for big data analytics.

Fairness Dynamics During Training Bigbench: Towards an industry standard benchmark for big data analytics

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:40:11.502357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:39:47.676574Z digest=sha256:5900cd39b2ebb572c50eb330e66b896bf78c2c038d56c2275dfee34d9a52bbdf

Observation 35bc065b-4af7-49d1-87b7-df9fc3977269 · outbound

This paper cites Towards understanding fairness and its composition in ensemble machine learning.

Fairness Dynamics During Training Towards understanding fairness and its composition in ensemble machine learning

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:40:09.938519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:39:49.595501Z digest=sha256:83213b9577ed84ef00106ca667f0e68d55a140c2331cc782373deba923311079

Observation 7d87c434-e121-46b0-b0d0-acc9d97a7e1e · outbound

This paper cites Ffb: A fair fairness benchmark for in-processing group fairness methods, 2024.

Fairness Dynamics During Training Ffb: A fair fairness benchmark for in-processing group fairness methods, 2024

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:40:09.868562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:39:51.789578Z digest=sha256:7e323cd3c6a39f82bfe0730843aed35cf3c4c93ef6cf1b962a276ed0ab84d65c

Observation 7b352ee7-6a1e-469f-b9ec-b931fad6a9f1 · outbound

This paper cites Debiasing isn't enough! -- On the Effectiveness of Debiasing MLMs and their Social Biases in Downstream Tasks.

Fairness Dynamics During Training Debiasing isn't enough! -- On the Effectiveness of Debiasing MLMs and their Social Biases in Downstream Tasks

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:39:53.376023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:39:51.881533Z digest=sha256:67a550d168cfd7a702fb77ac8139de83d5129385e2191fb6f1d2f0bf5cfcc4c8

Observation 551278a1-3200-424a-85ee-9cbdc042b665 · outbound

This paper cites Scaling Laws for Neural Language Models.

Fairness Dynamics During Training Scaling Laws for Neural Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T11:39:51.999849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:39:51.999849Z digest=sha256:c9021c007bc8044d9e99c5d57ce075b67dfa39644a18ace4fc51191d80375795

Observation a23b781f-0596-419e-9e48-2e13b6e440da · outbound

This paper cites an unresolved cited work.

Fairness Dynamics During Training Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:40:09.642906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:39:52.101832Z digest=sha256:947bbba817f6cc2ed63e85acf99363b1f0bc89b1e5b6e78c4bde2eb210ea87f2

Observation f14aece9-1c94-4d96-ab5f-ad70b570e923 · outbound

This paper cites Probing Across Time: What Does RoBERTa Know and When?.

Fairness Dynamics During Training Probing Across Time: What Does RoBERTa Know and When?

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T11:39:52.178797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:39:52.178797Z digest=sha256:de38d481fabe512f92384a9e50327ded2e9f9cbe1c4d715ed1bb5bcede3123b7

Observation 37ba012d-bbf6-49e7-b746-47263d65ee75 · outbound

This paper cites On a test of whether one of two random variables is stochastically larger than the other.The annals of mathematical statistics, pages 50–60, 1947.

Fairness Dynamics During Training On a test of whether one of two random variables is stochastically larger than the other.The annals of mathematical statistics, pages 50–60, 1947

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T11:39:52.259942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:39:52.259942Z digest=sha256:f51f4b2fde0c648a1c721311351923dd47d57227b964e1847fa43cd305def4c5

Observation 691bbec6-ea1a-479d-b6b8-54dbf47a5769 · outbound

This paper cites StereoSet: Measuring stereotypical bias in pretrained language models.

Fairness Dynamics During Training StereoSet: Measuring stereotypical bias in pretrained language models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T11:39:52.329107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:39:52.329107Z digest=sha256:b5fc8a2e8e021f62a8ffbfbd28e99aee9015f633fc1c36ac899475b1894750cb

Observation d944497f-7a5c-4241-b556-6f5bc7a114c2 · outbound

This paper cites CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models.

Fairness Dynamics During Training CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T11:39:52.400219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:39:52.400219Z digest=sha256:e324541ab4989b0a88cd80a1eb3018a65ee502fcb60f6e318cc0beb1bde205f2

Observation 81a5de6c-883f-455e-bd52-e4858d7cd1a6 · outbound

This paper cites The LAMBADA dataset: Word prediction requiring a broad discourse context.

Fairness Dynamics During Training The LAMBADA dataset: Word prediction requiring a broad discourse context

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T11:39:52.464536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:39:52.464536Z digest=sha256:b64ffa988a471094b26f9120e5d6725bf3904376923718c528f29fef268dec90

Observation fd5d1a77-75c8-4a24-9a57-ac36000bc52a · outbound

This paper cites Are emergent abilities of large language models a mirage?, 2023.

Fairness Dynamics During Training Are emergent abilities of large language models a mirage?, 2023

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T11:39:52.554247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:39:52.554247Z digest=sha256:3348316be932b0878e970a748d80f71af5ae81adb8c41742e092f1e2ea6be8d8

Observation 420ddf81-26b1-4fa9-8364-baf0e49c8b4d · outbound

This paper cites Fewer Errors, but More Stereotypes? The Effect of Model Size on Gender Bias.

Fairness Dynamics During Training Fewer Errors, but More Stereotypes? The Effect of Model Size on Gender Bias

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T11:39:52.777069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:39:52.777069Z digest=sha256:2276d5087fc3a90f33b3a6b88f690c126856027fa6c2d1709c57f09d6d886e74

Observation 472b5137-f1ae-45ce-90c0-e4df3b90f4dd · outbound

This paper cites Training Trajectories of Language Models Across Scales.

Fairness Dynamics During Training Training Trajectories of Language Models Across Scales

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T11:39:52.924492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:39:52.924492Z digest=sha256:b9a6808b63b9cea9c0698701010c30cbfef92e7ad055b4a325065456ae0c3162

Observation 596b6869-2972-4b7d-b6ed-25088d714e44 · outbound

This paper cites Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods.

Fairness Dynamics During Training Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T11:39:53.019573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:39:53.019573Z digest=sha256:1e1f8ae50fb4033e232f26d65ae30f110a8383497fce075ea6264d2d3af9a1ef

Pith citing papers

No inbound Pith citation observations are available.