Paper Citation Record · LEDGER

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models

As of 20 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2508.13625.

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

pith.paper-citation-record.v1
2508.13625 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:03:19.904535Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

24 of 24 outbound references displayed

verified exact2
verified fuzzy18
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9672b4b6-f93b-4428-bef0-47a27839893a · outbound

This paper cites Language models are few-shot learners,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Language models are few-shot learners,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.392150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 225dccbb-4f41-482f-8732-4eaa6ea91ea0 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T19:03:19.829855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc2a2468-f0d9-4f71-ba79-b151832eb187 · outbound

This paper cites Why do larger models generalize better? A theoretical perspective via the XOR problem,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Why do larger models generalize better? A theoretical perspective via the XOR problem,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.382993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 59955804-643a-42ea-917a-4615943927a7 · outbound

This paper cites an unresolved cited work.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-05T19:03:20.373578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2dfdc053-076f-4180-aced-07d0edb6a011 · outbound

This paper cites Advances and open problems in federated learning,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Advances and open problems in federated learning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.364100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d8e4fd4a-fe97-4d31-bba8-b32e8f016ac3 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Communication-efficient learning of deep networks from decentralized data,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.354848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 04eea3a3-41dc-4a79-b488-20d0c19c2ef2 · outbound

This paper cites Federated optimization in heterogeneous networks,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Federated optimization in heterogeneous networks,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.345258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fc34996f-03d9-4990-a1c3-058e56e33a27 · outbound

This paper cites FLaaS6G: Federated learning as a service in 6G using distributed data management architec- ture,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models FLaaS6G: Federated learning as a service in 6G using distributed data management architec- ture,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.227966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b84e3eea-ef9a-48a3-86c3-f5f507d49e14 · outbound

This paper cites Advancing federated learning in 6G: A trusted architecture with graph-based analysis,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Advancing federated learning in 6G: A trusted architecture with graph-based analysis,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.218542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d4c9a823-6692-476d-9c32-13beb5a04937 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Distilling the Knowledge in a Neural Network

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T19:03:19.858079Z

Source-reported events for the cited work

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Observation 51f196be-1700-4fb3-bb01-913540997caf · outbound

This paper cites Het- erogeneous ensemble knowledge transfer for training large models in federated learning,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Het- erogeneous ensemble knowledge transfer for training large models in federated learning,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.182185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ae8d8092-2cfc-4bf8-94ef-4bf63b23aa5d · outbound

This paper cites Fedgems: Federated learning of larger server models via selective knowledge fusion,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Fedgems: Federated learning of larger server models via selective knowledge fusion,

Reference 12

Resolution: verified exact; raw_fallback, observed 2026-08-05T19:03:20.049049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 23048c17-7fd6-4df0-8ed6-12e61f9d47bd · outbound

This paper cites Ensemble distillation for robust model fusion in federated learning,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Ensemble distillation for robust model fusion in federated learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.171558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5c3c104f-0869-4745-a76f-cc28d91a9f11 · outbound

This paper cites Not all knowledge is created equal: Mutual distillation of confident knowledge,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Not all knowledge is created equal: Mutual distillation of confident knowledge,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.161807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 44d6bf26-38a3-4b86-ad3b-c1c0c1d0c3d2 · outbound

This paper cites Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-05T19:03:19.949842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cfc9bfef-ced3-438a-b364-c641d8f5e56b · outbound

This paper cites A hierarchical knowledge transfer framework for heterogeneous federated learning,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models A hierarchical knowledge transfer framework for heterogeneous federated learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.152685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d58f7418-c4ba-403d-b315-fc7b99f090c6 · outbound

This paper cites One-Shot Federated Learning.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models One-Shot Federated Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T19:03:19.882018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e2db379-3fb8-4141-9cb7-fda0566cac02 · outbound

This paper cites Dense: Data-free one-shot federated learning,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Dense: Data-free one-shot federated learning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.143687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation aa004ce5-43a6-4af0-80a6-3598d35a5d7d · outbound

This paper cites Towards addressing label skews in one-shot federated learning,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Towards addressing label skews in one-shot federated learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.134761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 536242f1-4276-42e4-a492-dd427749d616 · outbound

This paper cites Semi-supervised learning by entropy minimization,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Semi-supervised learning by entropy minimization,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.124786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 32593e39-70d5-40ab-a73a-5a458eef73d0 · outbound

This paper cites Self-paced curriculum learning,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Self-paced curriculum learning,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.114600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8067f7a3-a238-4a8f-9d5f-e2000d556e21 · outbound

This paper cites Nlnl: Negative learning for noisy labels,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Nlnl: Negative learning for noisy labels,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.103590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 308f3e33-3b55-4708-8e05-b95150749613 · outbound

This paper cites Federated learning on non-iid data silos: An experimental study,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Federated learning on non-iid data silos: An experimental study,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.092820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b87d17cf-9659-4b3a-aafd-276cfdba3b29 · outbound

This paper cites Practical one-shot federated learning for cross-silo setting,.

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models Practical one-shot federated learning for cross-silo setting,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:03:20.082412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.