Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Input complexity and out-of-distribution detection with likelihood-based generative models
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1909.11480.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:42:37.733491Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T07:41:49.133559Z
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 16d94544-b688-4f5c-9895-33458e732d21 · inbound
Optimizing Latent Dimension Allocation in Hierarchical VAEs: Balancing Attenuation and Information Retention for OOD Detection cites this paper.
Optimizing Latent Dimension Allocation in Hierarchical VAEs: Balancing Attenuation and Information Retention for OOD Detection Input complexity and out-of-distribution detection with likelihood-based generative models
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:42:37.733491Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation de949469-b5b3-4c4c-a767-486f001a9222 · inbound
Energy-Based Transformers are Scalable Learners and Thinkers cites this paper.
Energy-Based Transformers are Scalable Learners and Thinkers Input complexity and out-of-distribution detection with likelihood-based generative models
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:42:30.846893Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 961ee42b-2fc7-4372-b020-1ef13f6036a1 · inbound
Native Extrapolation Awareness in Flow-Based Conditional Generation cites this paper.
Native Extrapolation Awareness in Flow-Based Conditional Generation Input complexity and out-of-distribution detection with likelihood-based generative models
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T23:42:36.462013Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e481e2de-108b-4f7f-8a6a-35dfa5e6084b · inbound
Generalization and Memorization in Rectified Flow cites this paper.
Generalization and Memorization in Rectified Flow Input complexity and out-of-distribution detection with likelihood-based generative models
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-07-15T12:03:26.994509Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7900987b-99e5-4b30-a182-02e15a5a04b9 · inbound
Beyond Penalization: Diffusion-based Out-of-Distribution Detection and Selective Regularization in Offline Reinforcement Learning cites this paper.
Beyond Penalization: Diffusion-based Out-of-Distribution Detection and Selective Regularization in Offline Reinforcement Learning Input complexity and out-of-distribution detection with likelihood-based generative models
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T07:41:49.141241Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.