Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Universal End-to-End Approach to Portfolio Optimization via Deep Learning
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2111.09170.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T17:38:20.841824Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T20:20:07.257954Z
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 d1ab4597-cea8-48d7-b5c2-3befd07ad926 · inbound
Decision-informed Neural Networks with Large Language Model Integration for Portfolio Optimization cites this paper.
Decision-informed Neural Networks with Large Language Model Integration for Portfolio Optimization A Universal End-to-End Approach to Portfolio Optimization via Deep Learning
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T17:38:20.841824Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 41466854-6874-4994-a799-506d8f17b9b4 · inbound
A Systematic Review of Recent Advancements in PINN Augmented Deep Learning and Mathematical Modeling for Efficient Portfolio Management cites this paper.
A Systematic Review of Recent Advancements in PINN Augmented Deep Learning and Mathematical Modeling for Efficient Portfolio Management A Universal End-to-End Approach to Portfolio Optimization via Deep Learning
Reference 66
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:26:30.275966Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 273e317e-1828-42ea-8bb5-a0cc9628975f · inbound
Generating Input Distributions for Explaining Portfolio Optimization Pipelines cites this paper.
Generating Input Distributions for Explaining Portfolio Optimization Pipelines A Universal End-to-End Approach to Portfolio Optimization via Deep Learning
Reference 44
- Resolution
- malformed identifier
- arxiv_id, observed 2026-07-04T20:20:07.259275Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 71ecc5c7-5f72-41e2-b863-2a3a5027c9c5 · inbound
End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? cites this paper.
End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? A Universal End-to-End Approach to Portfolio Optimization via Deep Learning
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T02:16:25.696341Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 0bd4fa11-b041-4dd7-a816-5d13e77fb8ed · inbound
Smooth Learning with Hard Constraints via Legendre-Regularized Policies cites this paper.
Smooth Learning with Hard Constraints via Legendre-Regularized Policies A Universal End-to-End Approach to Portfolio Optimization via Deep Learning
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T23:30:16.920235Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.