Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2003.00152.
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 2026-08-11T23:11:11.669446Z
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
79
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 09832495-5396-4aff-8ca4-883daf11dea3 · inbound
Batch Normalization Decomposed cites this paper.
Batch Normalization Decomposed Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T23:11:11.669446Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9968d47b-c5c8-454f-909d-34a8af192974 · inbound
FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning cites this paper.
FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T12:20:30.283095Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 601b06f2-3d82-4f96-8ad9-089d502390c7 · inbound
HyperCLIP: Adapting Vision-Language models with Hypernetworks cites this paper.
HyperCLIP: Adapting Vision-Language models with Hypernetworks Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T10:19:24.025816Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd8354bc-2234-4c36-a7ff-ce0144ef3c9a · inbound
Training Hybrid Neural Networks with Multimode Optical Nonlinearities Using Digital Twins cites this paper.
Training Hybrid Neural Networks with Multimode Optical Nonlinearities Using Digital Twins Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:34:51.038999Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e6dbd324-2154-495d-8a5f-e29076fdcf7b · inbound
15,500 Seconds: Lean UAV Classification Using EfficientNet and Lightweight Fine-Tuning cites this paper.
15,500 Seconds: Lean UAV Classification Using EfficientNet and Lightweight Fine-Tuning Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:11:30.222662Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 803712bd-e059-4807-8bc7-ec547d522980 · inbound
From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices cites this paper.
From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:41:43.313947Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1f27c3b1-7ce0-4804-9225-f20fdc648295 · inbound
DoSReMC: Domain Shift Resilient Mammography Classification using Batch Normalization Adaptation cites this paper.
DoSReMC: Domain Shift Resilient Mammography Classification using Batch Normalization Adaptation Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T22:11:52.465050Z
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 1e710cf6-c949-4f3a-b88c-6e5f74034a55 · inbound
Enhancing Novel View Synthesis from extremely sparse views with SfM-free 3D Gaussian Splatting Framework cites this paper.
Enhancing Novel View Synthesis from extremely sparse views with SfM-free 3D Gaussian Splatting Framework Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:56:51.731405Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 294e0897-6b51-483f-82a3-20c3a159ec62 · inbound
AlphaWiSE: Adaptive Weight Interpolation for Continual Multimodal Representation Learning cites this paper.
AlphaWiSE: Adaptive Weight Interpolation for Continual Multimodal Representation Learning Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T00:14:56.764678Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.