Paper Citation Record · LEDGER

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients

As of 9 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2509.03503.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2509.03503 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:59:57.163858Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

13 of 13 outbound references displayed

verified exact2
verified fuzzy3
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 553782f1-621e-4dc0-9aab-f1cddcae824e · outbound

This paper cites Optimization without Backpropagation.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients Optimization without Backpropagation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T10:59:56.170025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6cba81b-ae3e-47d7-9a37-b44f895ca68a · outbound

This paper cites Cristiano Gratton, Naveen K.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients Cristiano Gratton, Naveen K

Reference 4

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T10:59:57.881652Z

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 634e1e70-bf53-42bd-a622-5bf6ff4daa37 · outbound

This paper cites Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun

Reference 5

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T10:59:57.642043Z

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 560da3f1-4c5b-400f-8ddb-f3a99df74fe2 · outbound

This paper cites Critical Learning Periods in Federated Learning.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients Critical Learning Periods in Federated Learning

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:59:57.405315Z

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 92ca0ac0-8cfd-4018-a0f4-ad66b029595f · outbound

This paper cites Federated Learning with Non-IID Data.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients Federated Learning with Non-IID Data

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T10:59:56.953435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 059722c0-de5f-48b2-8dfb-f0575400e967 · outbound

This paper cites The Rademacher distribution exhibits considerably lower variance and better overall accuracy than the Gaussian distribution.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients The Rademacher distribution exhibits considerably lower variance and better overall accuracy than the Gaussian distribution

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:59:58.252085Z

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 c06244c9-ddd9-4c71-97ba-b06d0d178b00 · outbound

This paper cites A Vaswani.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients A Vaswani

Reference 1992

Resolution: unresolved; no resolver link, observed 2026-08-05T10:59:56.741954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 308c911d-e79b-4961-ae02-36b73d28eb36 · outbound

This paper cites cs.toronto.edu/˜kriz/learning-features-2009-TR.pdf.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients cs.toronto.edu/˜kriz/learning-features-2009-TR.pdf

Reference 2009

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:59:58.567079Z

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 ff20ec9b-7256-4624-8176-23ad8325b2fe · outbound

This paper cites A Survey on Model-heterogeneous Federated Learning: Problems, Methods, and Prospects.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients A Survey on Model-heterogeneous Federated Learning: Problems, Methods, and Prospects

Reference 2015

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:59:58.065420Z

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 0158103e-9795-4759-885f-5fbc015ae4a9 · outbound

This paper cites Understanding Why ViT Trains Badly on Small Datasets: An Intuitive Perspective.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients Understanding Why ViT Trains Badly on Small Datasets: An Intuitive Perspective

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-05T10:59:57.055832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ded39750-3699-413d-942e-3d6148f3e185 · outbound

This paper cites Zhong Long, Yuling Chen, Hui Dou, Yun Luo, Chaoyue Tan, and Yancheng Sun.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients Zhong Long, Yuling Chen, Hui Dou, Yun Luo, Chaoyue Tan, and Yancheng Sun

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:59:58.409231Z

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 69195c1a-e38f-43ff-8b31-9b081e54dad6 · outbound

This paper cites A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-05T10:59:56.235507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1424e056-fe05-4ebf-8095-88f9e974123e · outbound

This paper cites ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-05T10:59:56.662419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.