Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Conditional Sig-Wasserstein GANs for Time Series Generation
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2006.05421.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T05:44:27.549180Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
18
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation ca8eaa79-83ed-457a-9039-7e90c4529ad3 · inbound
Uncertainty-Aware Strategies: A Model-Agnostic Framework for Robust Financial Optimization through Subsampling cites this paper.
Uncertainty-Aware Strategies: A Model-Agnostic Framework for Robust Financial Optimization through Subsampling Conditional Sig-Wasserstein GANs for Time Series Generation
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:44:27.549180Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 320c41fc-e473-4716-b6d2-b9692cf853fa · inbound
CTBench: Cryptocurrency Time Series Generation Benchmark cites this paper.
CTBench: Cryptocurrency Time Series Generation Benchmark Conditional Sig-Wasserstein GANs for Time Series Generation
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T05:26:03.617765Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a6135e0-3482-4c50-bc31-6b144db36441 · inbound
AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation cites this paper.
AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation Conditional Sig-Wasserstein GANs for Time Series Generation
Reference 66
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T21:31:39.353543Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f61d0d89-7097-4ed7-9c80-233c5cbf9fc7 · inbound
Anticipatory Reinforcement Learning: From Generative Path-Laws to Distributional Value Functions cites this paper.
Anticipatory Reinforcement Learning: From Generative Path-Laws to Distributional Value Functions Conditional Sig-Wasserstein GANs for Time Series Generation
Reference 26
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T22:55:49.975226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 6047b9f6-44a6-4b02-86b1-9eab5a8e09ff · inbound
Generative Path-Law Jump-Diffusion: Sequential MMD-Gradient Flows and Generalisation Bounds in Marcus-Signature RKHS cites this paper.
Generative Path-Law Jump-Diffusion: Sequential MMD-Gradient Flows and Generalisation Bounds in Marcus-Signature RKHS Conditional Sig-Wasserstein GANs for Time Series Generation
Reference 21
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T22:55:51.748347Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 9e0c692d-6fb6-418c-8974-f06110652ff2 · inbound
Preserving Temporal Dynamics in Time Series Generation cites this paper.
Preserving Temporal Dynamics in Time Series Generation Conditional Sig-Wasserstein GANs for Time Series Generation
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:01:28.923816Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 9c9e7d87-338a-4975-ba20-6d01fff2f884 · inbound
Detecting Diffusion-Generated Time Series Under Generator Shift cites this paper.
Detecting Diffusion-Generated Time Series Under Generator Shift Conditional Sig-Wasserstein GANs for Time Series Generation
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T13:53:28.928648Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 59ccbb4a-ec01-4aa5-b70e-8a77d7a6278a · inbound
PrismFlow: Residual Dynamics for Flow Matching in Time-Series Generation cites this paper.
PrismFlow: Residual Dynamics for Flow Matching in Time-Series Generation Conditional Sig-Wasserstein GANs for Time Series Generation
Reference 47
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:35:12.730898Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation bdcf0593-79c1-4af4-97f1-e2a969825c3d · inbound
Continuous Hidden Markov Models for Equity Returns: Heavy-Tail Emission Families and Regime-Conditional Value-at-Risk cites this paper.
Continuous Hidden Markov Models for Equity Returns: Heavy-Tail Emission Families and Regime-Conditional Value-at-Risk Conditional Sig-Wasserstein GANs for Time Series Generation
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-06-26T01:58:54.092796Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.