Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:27:56.519671Z
Paper Citation Record · LEDGER
The Intrinsic Riemannian Proximal Gradient Method for Convex Optimization
As of 8 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 0 inbound Pith citation observations for arXiv:2507.16055.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
8 of 8 outbound references displayed
- verified exact2
- verified fuzzy1
- unresolved3
- parse uncertain0
- malformed identifier1
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a8b8fa9a-d11e-4e40-abbb-ad171c3956ca · outbound
This paper cites Manifolds.Jl: An Exten- sible Julia Framework for Data Analysis on Manifolds.
The Intrinsic Riemannian Proximal Gradient Method for Convex Optimization Manifolds.Jl: An Exten- sible Julia Framework for Data Analysis on Manifolds
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:27:56.417762Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6510d359-ab6a-4fae-8cc3-9d742ee58806 · outbound
This paper cites A fast iterative shrinkage-thresholding algorithm for linear inverse problems.
The Intrinsic Riemannian Proximal Gradient Method for Convex Optimization A fast iterative shrinkage-thresholding algorithm for linear inverse problems
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:27:56.465660Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a0e20ffa-46c4-41d8-89b7-e83c59a2974d · outbound
This paper cites First-order Methods for Geodesically Convex Optimization.
The Intrinsic Riemannian Proximal Gradient Method for Convex Optimization First-order Methods for Geodesically Convex Optimization
Reference 49
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T15:27:56.550202Z
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.
Observation c7ace041-67aa-4add-b6bd-e79293533bd0 · outbound
This paper cites Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point.
The Intrinsic Riemannian Proximal Gradient Method for Convex Optimization Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point
Reference 195
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:27:57.483287Z
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.
Observation d671f047-dc6f-4d09-9f15-03f578fe452f · outbound
This paper cites Implicit Riemannian Optimism with Applications to Min-Max Problems.
The Intrinsic Riemannian Proximal Gradient Method for Convex Optimization Implicit Riemannian Optimism with Applications to Min-Max Problems
Reference 235
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-06T15:27:56.559139Z
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.
Observation 298cb763-a318-4579-bad7-ba5d3cdf2a1b · outbound
This paper cites On some basic results related to affine functions on Riemannian manifolds.
The Intrinsic Riemannian Proximal Gradient Method for Convex Optimization On some basic results related to affine functions on Riemannian manifolds
Reference 297
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:27:56.517586Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c42da6ef-b41a-42f8-ad86-a8998a5a6aa6 · outbound
This paper cites An accelerated first-order method for non-convex optimization on manifolds.
The Intrinsic Riemannian Proximal Gradient Method for Convex Optimization An accelerated first-order method for non-convex optimization on manifolds
Reference 319
- Resolution
- malformed identifier
- local_arxiv, observed 2026-08-06T15:27:56.567486Z
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.
Observation 1f923d20-8de5-4ddd-be6d-4150e9608502 · outbound
This paper cites Fenchel Duality Theory and A Primal-Dual Algorithm on Riemannian Manifolds.
The Intrinsic Riemannian Proximal Gradient Method for Convex Optimization Fenchel Duality Theory and A Primal-Dual Algorithm on Riemannian Manifolds
Reference 3866
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T15:27:56.576805Z
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.
Pith citing papers
No inbound Pith citation observations are available.