Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
No More Adam: Learning Rate Scaling at Initialization is All You Need
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2412.11768.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T14:37:23.786570Z
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 f4028448-fec2-4f51-9294-9d575a3c015a · inbound
Gradient Multi-Normalization for Stateless and Scalable LLM Training cites this paper.
Gradient Multi-Normalization for Stateless and Scalable LLM Training No More Adam: Learning Rate Scaling at Initialization is All You Need
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:37:23.786570Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 938f875f-cad8-42ce-916b-ecc6ec5e8f30 · inbound
Towards Efficient Optimizer Design for LLM via Structured Fisher Approximation with a Low-Rank Extension cites this paper.
Towards Efficient Optimizer Design for LLM via Structured Fisher Approximation with a Low-Rank Extension No More Adam: Learning Rate Scaling at Initialization is All You Need
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T11:46:47.782800Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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 2026-08-09T06:31:02.800959+00:00.
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 2026-08-09T06:31:02.800959+00:00.
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 2026-08-09T06:31:02.800959+00:00.
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 2026-08-09T06:31:02.800959+00:00.
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.