Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2006.07322.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:58:32.170891Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T07:59:39.539689Z
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 6319a30f-9398-474a-b399-15d694efbeb3 · inbound
Next Token Perception Score: Analytical Assessment of your LLM Perception Skills cites this paper.
Next Token Perception Score: Analytical Assessment of your LLM Perception Skills Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:58:32.170891Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation be5a1427-8941-4aea-acae-2396b19dbd6a · inbound
Generative Cross-Entropy: A Strictly Proper Loss for Data-Efficient Classification cites this paper.
Generative Cross-Entropy: A Strictly Proper Loss for Data-Efficient Classification Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T23:55:50.740214Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 93c9774e-31ab-4082-84f5-e6f79d2cf131 · inbound
Generative Cross-Entropy: A Strictly Proper Loss for Data-Efficient Classification cites this paper.
Generative Cross-Entropy: A Strictly Proper Loss for Data-Efficient Classification Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T08:01:31.131248Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 1037f654-b5b0-4af6-910f-226ed96f87c1 · inbound
Alternate loss functions and regression models that achieve robustness to outliers by modulating the learning rate cites this paper.
Alternate loss functions and regression models that achieve robustness to outliers by modulating the learning rate Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T07:59:39.541186Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation f6e20bd6-705d-418f-95bd-41a4febb7e08 · inbound
Robustness of neural networks to random noise perturbations of their inputs cites this paper.
Robustness of neural networks to random noise perturbations of their inputs Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T09:35:40.969796Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.