Paper Citation Record · LEDGER

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting

As of 19 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2508.11869.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.11869 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:50:48.981156Z

measured 18 of 18 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

18 of 18 outbound references displayed

verified exact2
verified fuzzy10
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cbe688c8-0657-4b36-9200-58541ab254c5 · outbound

This paper cites fk is Lipschitz continuous with constantL =σmax(I +M), as∥∇fk(x)−∇fk(y)∥≤ L∥x−y∥.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting fk is Lipschitz continuous with constantL =σmax(I +M), as∥∇fk(x)−∇fk(y)∥≤ L∥x−y∥

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:50:49.321354Z

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 0dd9e94b-7770-48e7-81f1-e81c020771f1 · outbound

This paper cites an unresolved cited work.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-05T19:50:49.331333Z

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 5c03ccef-850d-4974-b164-f3a47b217cf3 · outbound

This paper cites an unresolved cited work.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-05T19:50:49.342079Z

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 aa3aa50d-e54e-44be-9669-af44b8bb8c31 · outbound

This paper cites Inf. Time(s).

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Inf. Time(s)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:50:49.300443Z

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 2736fe33-1ee0-4e13-89c0-cff9b75dd35d · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Adam: A Method for Stochastic Optimization

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T19:50:48.947457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1b1e006-3fb0-4e75-bab7-d874470adf92 · outbound

This paper cites an unresolved cited work.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T19:50:48.962645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9220cf42-12df-4b7e-8c29-d9354e53b75a · outbound

This paper cites Obj.”), feasibility satisfaction (“Max Viol.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Obj.”), feasibility satisfaction (“Max Viol

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:50:49.289702Z

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 88b40bd7-87b5-43ec-a3df-8ced6b3359f5 · outbound

This paper cites Therefore, ∀k > K,∃0 < c <1, such that∥wk+1−wk∥≤ c∥wk−wk−1∥ and thus∑ k=K∥wk+1−wk∥ < +∞.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Therefore, ∀k > K,∃0 < c <1, such that∥wk+1−wk∥≤ c∥wk−wk−1∥ and thus∑ k=K∥wk+1−wk∥ < +∞

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:50:49.310731Z

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 2503669f-59ca-422a-a25a-f8a43725cb32 · outbound

This paper cites On the douglas—rachford splitting method and the proximal point algorithm for maximal monotone operators.Mathematical Programming, 55:293–318,.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting On the douglas—rachford splitting method and the proximal point algorithm for maximal monotone operators.Mathematical Programming, 55:293–318,

Reference 1956

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:50:49.382203Z

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 353af111-18e1-487c-bd8c-b2af740c7444 · outbound

This paper cites An Efficient Unsupervised Framework for Convex Quadratic Programs via Deep Unrolling.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting An Efficient Unsupervised Framework for Convex Quadratic Programs via Deep Unrolling

Reference 1959

Resolution: verified exact; local_arxiv, observed 2026-08-05T19:50:49.106817Z

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 dacdbeba-d6b8-49c0-be67-7381cc72480a · outbound

This paper cites The machine learning for combinatorial optimization competition (ml4co): Results and insights.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting The machine learning for combinatorial optimization competition (ml4co): Results and insights

Reference 1989

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:50:49.372527Z

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 7c3cdaca-986c-4727-8aef-a72a0d2e4988 · outbound

This paper cites Operator splitting for a homogeneous embedding of the linear complementarity problem.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Operator splitting for a homogeneous embedding of the linear complementarity problem

Reference 1999

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:50:49.362683Z

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 604695da-3339-4d09-a299-0b11c37c0e0e · outbound

This paper cites Warm-starting ac optimal power flow with graph neural networks.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Warm-starting ac optimal power flow with graph neural networks

Reference 2016

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:50:49.391544Z

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 980018a0-b245-44c4-b6fa-b19188697a03 · outbound

This paper cites Learning warm-start points for ac optimal power flow.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Learning warm-start points for ac optimal power flow

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:50:49.401140Z

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 0da91e6f-753c-4900-8a4a-2a6a7a2a6531 · outbound

This paper cites Learning context-aware adaptive solvers to accelerate quadratic programming.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Learning context-aware adaptive solvers to accelerate quadratic programming

Reference 2021

Resolution: verified exact; local_arxiv, observed 2026-08-05T19:50:49.216779Z

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 1895e0f9-6b8f-456d-9501-9146f9803ea4 · outbound

This paper cites Expressive power of graph neural networks for (mixed-integer) quadratic programs.arXiv preprint arXiv:2406.05938,.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Expressive power of graph neural networks for (mixed-integer) quadratic programs.arXiv preprint arXiv:2406.05938,

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-05T19:50:48.931439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e45f70cd-be71-436c-8405-a359f327ff49 · outbound

This paper cites Learning to solve the ac optimal power flow via a lagrangian approach.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Learning to solve the ac optimal power flow via a lagrangian approach

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:50:49.352513Z

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 bb6b6ed2-1056-4b6c-be53-123a8c8439ef · outbound

This paper cites Mpax: Mathematical programming in jax.

Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting Mpax: Mathematical programming in jax

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-05T19:50:48.950293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.