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Paper Citation Record · LEDGER

No More Adam: Learning Rate Scaling at Initialization is All You Need

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2412.11768.

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

pith.paper-citation-record.v1
2412.11768 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T22:10:49.683444Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T13:24:53.244110Z

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 c732579d-e615-4f62-8939-4f4a3b6dc7df · inbound

Memory-Efficient LLM Pretraining via Minimalist Optimizer Design cites this paper.

Memory-Efficient LLM Pretraining via Minimalist Optimizer Design No More Adam: Learning Rate Scaling at Initialization is All You Need

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-22T13:24:53.247110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T13:23:55.233840Z digest=sha256:34abd7cde6091dd51075836ddb995ba50d819b94e9f49665ff9318d92f43688d

Observation 46d1497f-dc9c-4ad4-9a10-66c3666877b6 · inbound

Evolution of Optimization Methods: Algorithms, Scenarios, and Evaluations cites this paper.

Evolution of Optimization Methods: Algorithms, Scenarios, and Evaluations No More Adam: Learning Rate Scaling at Initialization is All You Need

Reference 32

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T10:51:20.166965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T15:16:58.221358Z digest=sha256:29f3f1751752c3e84d5bc32104eea3f2de99753ed6881b4ee3acca24c878974e

Observation fffd8c75-6370-485e-bd02-c6bfaf3be839 · inbound

Layerwise LQR for Geometry-Aware Optimization of Deep Networks cites this paper.

Layerwise LQR for Geometry-Aware Optimization of Deep Networks No More Adam: Learning Rate Scaling at Initialization is All You Need

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:51:09.813669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T16:59:22.216757Z digest=sha256:341aa1ae9ae545ff54634eab5361777b77eb425cc6085e620478f144343862da

Observation 90d18fcd-5287-4f14-b605-6fccffadd7e3 · 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 No More Adam: Learning Rate Scaling at Initialization is All You Need

Reference 39

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T16:41:05.035119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-09T15:39:51.611115Z digest=sha256:0d7a4aeadf7dd5db78c1440fc4b6d509607b85214f359a7da9cd53d56887a7e7

Observation 2da8cb7e-00cc-4a91-b77c-518ee26566e6 · inbound

OmniOpt: Taxonomy, Geometry, and Benchmarking of Modern Optimizers cites this paper.

OmniOpt: Taxonomy, Geometry, and Benchmarking of Modern Optimizers No More Adam: Learning Rate Scaling at Initialization is All You Need

Reference 118

Resolution
unresolved
no resolver link, observed 2026-07-11T22:10:49.683444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T22:10:49.683444Z digest=sha256:e6ab44c44e388dcfa6231d0dff3da8a2c8870c493f6e112baa38aea28fe00632