Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2110.02095.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
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 2026-08-07T13:01:06.827148Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T22:56:53.133697Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation fdd2f264-e713-4ecc-a805-a541387c8870 · inbound
Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks Exploring the Limits of Large Scale Pre-training
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 24a0ee2a-be06-4e0c-ab17-dac540d80973 · inbound
A Theory of Inference Compute Scaling: Reasoning through Directed Stochastic Skill Search Exploring the Limits of Large Scale Pre-training
Reference 65
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0806bbc1-6085-4f1f-81eb-fd3649b9f651 · inbound
PaCo-FR: Patch-Pixel Aligned End-to-End Codebook Learning for Facial Representation Pre-training Exploring the Limits of Large Scale Pre-training
Reference 1
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 e666ca99-7e60-4aa2-9256-418dae342f36 · inbound
CCoMAML: Efficient Cattle Identification Using Cooperative Model-Agnostic Meta-Learning Exploring the Limits of Large Scale Pre-training
Reference 2021
Source-reported events for the cited work
Unavailable: canonical work link unavailable.