Paper Citation Record · LEDGER

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models

As of 6 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 0 inbound Pith citation observations for arXiv:2604.24708.

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

pith.paper-citation-record.v1
2604.24708 v1

Coverage vector

measured 10 of 10 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-08T04:08:25.530778Z

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

10 of 10 outbound references displayed

verified exact10
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 993438df-88ea-4ba5-9c63-c73fe0c4445c · outbound

This paper cites Learning with Random Learning Rates.

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models Learning with Random Learning Rates

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-04T23:21:15.605326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e686002a-931a-4a28-8aa9-b861c5c41fa0 · outbound

This paper cites an unresolved cited work.

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models Unresolved cited work

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:20.025965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b68142d7-9a5c-48df-a10e-76dba254aa36 · outbound

This paper cites The Road Less Scheduled.

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models The Road Less Scheduled

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:20.966380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b42801bf-da72-481e-a4e3-b5e9f1dcc683 · outbound

This paper cites GRAWA: Gradient-based Weighted Averaging for Distributed Training of Deep Learning Models.

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models GRAWA: Gradient-based Weighted Averaging for Distributed Training of Deep Learning Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:20.266150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 669f8d3c-b7c6-48da-a9fa-389612f0a24d · outbound

This paper cites DiLoCo: Distributed Low-Communication Training of Language Models.

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models DiLoCo: Distributed Low-Communication Training of Language Models

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:20.305569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ac5e7557-7b9b-4f1c-905e-b8dd7ba53d18 · outbound

This paper cites Deep Ensembles: A Loss Landscape Perspective.

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models Deep Ensembles: A Loss Landscape Perspective

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:20.547192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b9aa4aff-fd2e-4e49-aef2-726731ed5d0f · outbound

This paper cites DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule.

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:19.971064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ef5653d3-969c-4693-ac8a-c77fa5228ce9 · outbound

This paper cites Population Based Training of Neural Networks.

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models Population Based Training of Neural Networks

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:19.923638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6212c532-49b1-422d-ac12-223f9d75b118 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models Adam: A Method for Stochastic Optimization

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-11T21:51:20.675202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0fcf3ee0-31f0-4ed1-aa90-789ef7dea36f · outbound

This paper cites Evolution Strategies as a Scalable Alternative to Reinforcement Learning.

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:20.851702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

No inbound Pith citation observations are available.