Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Learning Robust Global Representations by Penalizing Local Predictive Power
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1905.13549.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:25:04.097282Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T04:25:19.596825Z
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 d0d0e904-5f80-44ca-9ed7-64676e635ef2 · inbound
LAION-5B: An open large-scale dataset for training next generation image-text models cites this paper.
LAION-5B: An open large-scale dataset for training next generation image-text models Learning Robust Global Representations by Penalizing Local Predictive Power
Reference 85
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T14:22:17.411147Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation ce435bf0-88e9-4a1c-a465-2b0ae007bc2a · inbound
Revisiting Bayesian Model Averaging in the Era of Foundation Models cites this paper.
Revisiting Bayesian Model Averaging in the Era of Foundation Models Learning Robust Global Representations by Penalizing Local Predictive Power
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:25:04.097282Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a29d9b32-b042-40c7-9fe7-aeaccd0e0cee · inbound
Scaling Laws for Robust Comparison of Open Foundation Language-Vision Models and Datasets cites this paper.
Scaling Laws for Robust Comparison of Open Foundation Language-Vision Models and Datasets Learning Robust Global Representations by Penalizing Local Predictive Power
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:45:57.234629Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 400bd100-a8de-4056-bfb9-6b860918779c · inbound
Not Too Generative, Not Too Discriminative: The Human Alignment Sweet Spot cites this paper.
Not Too Generative, Not Too Discriminative: The Human Alignment Sweet Spot Learning Robust Global Representations by Penalizing Local Predictive Power
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:25:19.599224Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 66151ac0-a63a-4e50-b8ed-77201f025e21 · inbound
Attributes Should Come from Images, Not Class Names: Distribution-Conditioned Attribute Selection for Vision-Language Models cites this paper.
Attributes Should Come from Images, Not Class Names: Distribution-Conditioned Attribute Selection for Vision-Language Models Learning Robust Global Representations by Penalizing Local Predictive Power
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T14:41:35.945242Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.