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Paper Citation Record · LEDGER

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives

As of 14 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 2 inbound Pith citation observations for arXiv:2412.20679.

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

pith.paper-citation-record.v1
2412.20679 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:21:41.481027Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T08:39:35.258680Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T19:16:09.307154Z

Reference resolution

11 of 11 outbound references displayed

  • verified exact2
  • verified fuzzy2
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a94f0caf-cd5f-4620-96e3-73b77fb7d912 · outbound

This paper cites Differentiable Convex Optimization Layers.

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives Differentiable Convex Optimization Layers

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T23:21:41.431042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T23:21:41.431042Z digest=sha256:a69bd6f6cb0208aeb44522c895baec71d0ab98ab028862f9a7b37d99d41c3a95

Observation 325fc8ac-8990-4a04-aed9-a919cf83981b · outbound

This paper cites Differentiating Through a Cone Program.

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives Differentiating Through a Cone Program

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-10T23:21:41.436444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T23:21:41.436444Z digest=sha256:b3ef7ca0500a9b9cefec5529eb6f03ea54372f9f92816ab810ee9767065cf6a8

Observation ee6e4b24-a456-4e9c-8dfc-de4f79be46cf · outbound

This paper cites OptNet: Differentiable Optimization as a Layer in Neural Networks.

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives OptNet: Differentiable Optimization as a Layer in Neural Networks

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-10T23:21:41.441520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T23:21:41.441520Z digest=sha256:d357fd9ca95a6e5c4c23766321a6188e223e5b9b1c0a130bc77263706d8ca4b9

Observation 5396aa6b-78c5-4639-b1fd-8f7eba9980b0 · outbound

This paper cites On the Differentiability of the Solution to Convex Optimization Problems.

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives On the Differentiability of the Solution to Convex Optimization Problems

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-10T23:21:41.446558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T23:21:41.446558Z digest=sha256:355889d22aaf5cc6700a0a90e04e0e53737e25a0403655ead2c086e3b2c517df

Observation f96a9a1a-9cb3-4949-b775-f51cba29e01c · outbound

This paper cites Convex Optimization.

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives Convex Optimization

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T23:21:41.452215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T23:21:41.452215Z digest=sha256:6b2af5a14d6989158c42c1e204a36f5b605adf33c2856717a84435ca9101b795

Observation 5c22a1ac-2fb0-4ff8-b272-1f0153357ae6 · outbound

This paper cites On Differentiating Parameterized Argmin and Argmax Problems with Application to Bi-level Optimization.

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives On Differentiating Parameterized Argmin and Argmax Problems with Application to Bi-level Optimization

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-10T23:21:41.456630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T23:21:41.456630Z digest=sha256:3ba81c8c17adeb70dfef2b31edce94f1c09c5eb43a126dc0705fed989b9d2898

Observation 28c7c166-1175-458b-8e3f-ebf66f70d3db · outbound

This paper cites Grant, S.

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives Grant, S

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:21:41.802243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-10T23:21:41.462142Z digest=sha256:ac6a9a8c6d5365435ffbf5b79cb70bdbdbd843db731815874cba69389652a0c5

Observation 1932c5fe-ffe5-4295-ad38-ebae0889f87e · outbound

This paper cites Cvxgen: A code generator for embedded convex optimization.

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives Cvxgen: A code generator for embedded convex optimization

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:21:41.786475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-10T23:21:41.466553Z digest=sha256:0e3b7e21d5439ee3bbae8ab1f94e148ac3c14ad0b1d701a8c7b8619d2c46321f

Observation 3903d633-827f-4c3a-b271-8df6cbdd0f5e · outbound

This paper cites Paige and Michael A.

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives Paige and Michael A

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T23:21:41.472378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T23:21:41.472378Z digest=sha256:81ffd2e3f182295a0f543cf5c48cbe357931f3f613f52b7992998b6960b75930

Observation 4deee607-8a3f-4ca5-86d5-433ad137696e · outbound

This paper cites an unresolved cited work.

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives Unresolved cited work

Reference 10

Resolution
verified exact
doi, observed 2026-08-10T23:21:41.514932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-10T23:21:41.476669Z digest=sha256:077455175dfc9e8c4ce3f031af075c427f2625911b3d82cc2d21779b0681f021

Observation 3dbe38aa-445a-46dd-90d3-813052c34235 · outbound

This paper cites Todd, and Shinji Mizuno.

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives Todd, and Shinji Mizuno

Reference 11

Resolution
verified exact
raw_fallback, observed 2026-08-10T23:21:41.594003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-10T23:21:41.481027Z digest=sha256:487f683248a3b62e431930cc953eedad199d66f1fd490a5ac62952f1e9a65c2b

Pith citing papers

Observation bbcdbf0e-1402-4b62-8226-2995369ae99d · inbound

Learning to Optimize by Differentiable Programming cites this paper.

Learning to Optimize by Differentiable Programming Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-03T08:39:35.258680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T08:39:35.258680Z digest=sha256:afbe891010bfc6328fda2bf9fdbedf0e0c2816128cef105a1cf44ba5a1d9676a

Observation 3fac4301-f118-4b2c-bc90-2c430c6300c2 · inbound

SOC-ICNN: From Polyhedral to Conic Geometry for Learning Convex Surrogate Functions cites this paper.

SOC-ICNN: From Polyhedral to Conic Geometry for Learning Convex Surrogate Functions Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:16:09.313162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-08T12:24:45.333057Z digest=sha256:ee0fa271de51e20ebd606591d231bd3661a73a4e2083cb904fbdbd778865cb4d