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Paper Citation Record · LEDGER

Understanding the Difficulty of Training Transformers

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2004.08249.

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

pith.paper-citation-record.v1
2004.08249 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:10:29.797034Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T05:19:34.958362Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 66847ad0-6d38-4560-ae74-b30dcff183ab · inbound

H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models cites this paper.

H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models Understanding the Difficulty of Training Transformers

Reference 83

Resolution
verified exact
arxiv_id, observed 2026-05-17T18:00:50.203271Z

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=2026-05-17T18:00:50.053377Z digest=sha256:fd76ecc06e2f007486e34f797a413971c8e1d0980222130ebaadd738e65622e7

Observation b2b02d37-08a6-438d-ae56-7976968cb27e · inbound

One Rank at a Time: Cascading Error Dynamics in Sequential Learning cites this paper.

One Rank at a Time: Cascading Error Dynamics in Sequential Learning Understanding the Difficulty of Training Transformers

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T13:10:29.797034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:29.797034Z digest=sha256:2e286b55fb10b026820c0cb26b36de2055c231305ceac2e6bccc1497eccba373

Observation cba16ffd-1a5f-4d76-988d-a4abbe2cb58f · inbound

Scalable Complexity Control Facilitates Reasoning Ability of LLMs cites this paper.

Scalable Complexity Control Facilitates Reasoning Ability of LLMs Understanding the Difficulty of Training Transformers

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:11.673134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:11.673134Z digest=sha256:00c34074f2d62c60fc736c9c28d83f890281b37cbc1b7be1cb84fcfa0198ab77

Observation 8d5ed22f-8a93-43e9-bb94-1311996b8197 · inbound

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities cites this paper.

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities Understanding the Difficulty of Training Transformers

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-19T05:52:07.757730Z

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=arxiv_source observed=2026-05-19T05:48:02.828938Z digest=sha256:b6e8ad62626d41861934e7b08208497dd46b8e1caa75dda63eecd64b26074d63

Observation dbb8e446-e99e-4367-8166-5e3dca91abff · inbound

One task to rule them all: A closer look at traffic classification generalizability cites this paper.

One task to rule them all: A closer look at traffic classification generalizability Understanding the Difficulty of Training Transformers

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T19:08:52.635579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:08:52.635579Z digest=sha256:0bbdad12ed341bf394627da918a04f87d00216b0c647b13f79c321872399bb69

Observation 81412f7d-d3c9-443f-b776-78d06309f9d7 · inbound

SoftSignSGD(S3): An Enhanced Optimizer for Practical DNN Training and Loss Spikes Minimization Beyond Adam cites this paper.

SoftSignSGD(S3): An Enhanced Optimizer for Practical DNN Training and Loss Spikes Minimization Beyond Adam Understanding the Difficulty of Training Transformers

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T19:10:16.577022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:10:16.577022Z digest=sha256:d5950f4232388a9d14346392b7705416d803e9cf3ee8f7d73b23feaec145673f

Observation 6f731f1d-530c-464c-84b5-096da2279561 · inbound

On the Performance of Differentially Private Optimization with Heavy-Tail Class Imbalance cites this paper.

On the Performance of Differentially Private Optimization with Heavy-Tail Class Imbalance Understanding the Difficulty of Training Transformers

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T17:35:00.542162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:35:00.542162Z digest=sha256:25e6dd1a44700ae1e437b8bf2c44d55426a18ed03de8cda44a8cd32e213ab840

Observation 06a6a077-4966-4941-a9c8-77293f1e293c · inbound

Revealing Modular Gradient Noise Imbalance in LLMs: Calibrating Adam via Signal-to-Noise Ratio cites this paper.

Revealing Modular Gradient Noise Imbalance in LLMs: Calibrating Adam via Signal-to-Noise Ratio Understanding the Difficulty of Training Transformers

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:41:05.000237Z

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=2026-05-09T15:39:51.611115Z digest=sha256:41ddcc6d6e772b20cc51ef0137a8204048995b04523911bd814c4780b4311f54

Observation 1d789494-00a5-4c49-837d-c3cd11031bad · inbound

Improving End-to-End Speech Recognition for Dysarthric Speech through In-Domain Data Augmentation cites this paper.

Improving End-to-End Speech Recognition for Dysarthric Speech through In-Domain Data Augmentation Understanding the Difficulty of Training Transformers

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-07-04T05:19:34.960081Z

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=2026-06-26T16:09:00.257229Z digest=sha256:e3276374ff0870c9f842f7210e0ed6aefb1d1d66e83a4c451d8c26f518f9331f