Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Curvature-Informed SGD via General Purpose Lie-Group Preconditioners
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.04553.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T13:28:29.100571Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T18:45:00.344001Z
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 5721afeb-b1a6-4472-bfef-5dd3671c81f8 · inbound
SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training cites this paper.
SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training Curvature-Informed SGD via General Purpose Lie-Group Preconditioners
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T13:28:29.100571Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 772ca94a-a126-4143-9964-926742eb0bb6 · inbound
Training Deep Learning Models with Norm-Constrained LMOs cites this paper.
Training Deep Learning Models with Norm-Constrained LMOs Curvature-Informed SGD via General Purpose Lie-Group Preconditioners
Reference 204
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T21:22:37.091354Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 07dcae0d-99ef-421d-9a27-abaf2e1bb770 · 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 Curvature-Informed SGD via General Purpose Lie-Group Preconditioners
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T11:46:47.759576Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0a56f6fd-d7f9-4e88-80ce-14ed6b70c41b · inbound
Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers cites this paper.
Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers Curvature-Informed SGD via General Purpose Lie-Group Preconditioners
Reference 123
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T09:38:11.184041Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 217cf82f-604e-4b35-a355-719b40f5f824 · inbound
Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers cites this paper.
Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers Curvature-Informed SGD via General Purpose Lie-Group Preconditioners
Reference 125
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T18:45:00.361894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.