Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Deep Inception Networks: A General End-to-End Framework for Multi-asset Quantitative Strategies
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2307.05522.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T10:32:52.452900Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T05:41:19.477729Z
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 337759b8-c935-40ac-b4fc-55dda5be57ab · inbound
Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making cites this paper.
Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making Deep Inception Networks: A General End-to-End Framework for Multi-asset Quantitative Strategies
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T20:08:47.884640Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 83704d63-0f48-4357-a349-1c21f1b631f7 · inbound
QuantBench: Benchmarking AI Methods for Quantitative Investment cites this paper.
QuantBench: Benchmarking AI Methods for Quantitative Investment Deep Inception Networks: A General End-to-End Framework for Multi-asset Quantitative Strategies
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:32:52.353198Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation af0f64ae-8f93-4296-af9f-e0361d624207 · inbound
QuantBench: Benchmarking AI Methods for Quantitative Investment cites this paper.
QuantBench: Benchmarking AI Methods for Quantitative Investment Deep Inception Networks: A General End-to-End Framework for Multi-asset Quantitative Strategies
Reference 68
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:32:52.452900Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b2216ef4-8015-4171-b674-7fd14584cb00 · inbound
ClusterLOB: Enhancing Trading Strategies by Clustering Orders in Limit Order Books cites this paper.
ClusterLOB: Enhancing Trading Strategies by Clustering Orders in Limit Order Books Deep Inception Networks: A General End-to-End Framework for Multi-asset Quantitative Strategies
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T05:37:22.114008Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ad11a319-1213-4819-a023-5306c2c8e721 · inbound
Painting the market: generative diffusion models for financial limit order book simulation and forecasting cites this paper.
Painting the market: generative diffusion models for financial limit order book simulation and forecasting Deep Inception Networks: A General End-to-End Framework for Multi-asset Quantitative Strategies
Reference 22
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T05:41:19.521189Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.