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Paper Citation Record · LEDGER

Understanding the Difficulty of Training Transformers

As of 8 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=sha256:620b04adf39699e1d55e3eb5dd442baa245591813b1029d0deb18f14e3480f75

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:d3619694e6593343182bfc40c345880da975c216983b8e84346ce81a0b5963f7

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=sha256:224b3e3ea3e34014c1803292ab05ea220370d4339aa2a1d3f9d8181f58056bc9

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=sha256:360ff28b9623c9ab469282cdcb888cd7effd06ed0a8284310d14d1dc6ce1fc3e

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:cd95e0325305cc9a06517c0516fc98ec40e8f5b1678c3b5626accc17020969e4

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:b957e1df6749d63e1d7f2b3a8c9f8e906e9e133fc78a7baf9c06242ce0213955

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:bf3e18a84c5175a5e3d13fee4ed2e1049c2e5414a31953391381e3c25120f40c

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:b951a4de305b52823889bc2a287c1eb2c865c8e63e5cb56367a60b2c5d272a9e

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=sha256:002673458b0b79b65d594170efcde25d605b8e7023c9ed0e96362db388fcdd1c