Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2108.06084.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T22:51:57.213305Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T21:15:09.614618Z
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 ea503212-0815-49dc-8665-297f8e2606cb · inbound
TinyHelen's First Curriculum: Training and Evaluating Tiny Language Models in a Simpler Language Environment cites this paper.
TinyHelen's First Curriculum: Training and Evaluating Tiny Language Models in a Simpler Language Environment The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models
Reference 2011
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:51:57.213305Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 75d63b07-ed97-4d91-b8e8-87f72239ce93 · inbound
MegaScale-Data: Scaling Dataloader for Multisource Large Foundation Model Training cites this paper.
MegaScale-Data: Scaling Dataloader for Multisource Large Foundation Model Training The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T21:15:09.617034Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 760a3f7b-41bf-4277-b85a-4857b90daf43 · inbound
Dense Local Dependencies Induce Attention-Logit Explosion and Training Instability During Long-Sequence Transformer Training cites this paper.
Dense Local Dependencies Induce Attention-Logit Explosion and Training Instability During Long-Sequence Transformer Training The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:19:26.765813Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.