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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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-22T13:23:55.233840Z digest=sha256:d259bcca0e0f5f64fcbd1a72b5520c091cca1bed6aa89edbd0fc9943690aa629

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T15:16:58.221358Z digest=sha256:22c64b8764c451a10e300fd3f2dce76861ee126eecea0ab73a88ad88284c0426

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T16:59:22.216757Z digest=sha256:04dec6a9ae257d2c14ff95c67a3d2420d25299e50ed38955fa85d2ca84bfb88e

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-09T15:39:51.611115Z digest=sha256:0e920a6fdb7d18a24e84ed1dbfb437740b6c6629c0dc4328a5d45d08a5d48fe1

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