Paper Citation Record · LEDGER

The Intrinsic Riemannian Proximal Gradient Method for Convex Optimization

As of 19 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.

pith.paper-citation-record.v1
2507.16055 v2

Coverage vector

measured 8 of 8 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:27:56.519671Z

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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 2026-08-19T06:32:44.657259+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 2026-08-19T06:32:44.657259+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 2026-08-19T06:32:44.657259+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 2026-08-19T06:32:44.657259+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 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.