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Paper Citation Record · LEDGER

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity

As of 7 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 1 inbound Pith citation observation for arXiv:2507.15601.

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

pith.paper-citation-record.v1
2507.15601 v2

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:37:01.189240Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T15:24:04.079011Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T15:26:33.774099Z

Reference resolution

49 of 49 outbound references displayed

  • verified exact2
  • verified fuzzy35
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f8dcb94b-6176-49e4-8fd5-1b38cab95f8a · outbound

This paper cites A vision of 6G wireless systems: Applications, trends, technologies, and open research problems,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity A vision of 6G wireless systems: Applications, trends, technologies, and open research problems,

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.387683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:00.914700Z digest=sha256:ab1e49528f745710f0912c9cb9e24bb22622f694ce75e8d88e44977be70f6b59

Observation 9cabefea-bf88-48c6-af11-107dce834990 · outbound

This paper cites Integrated Sensing and Edge AI: Realizing Intelligent Perception in 6G.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Integrated Sensing and Edge AI: Realizing Intelligent Perception in 6G

Reference 2

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unresolved
no resolver link, observed 2026-08-06T15:37:00.920375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:37:00.920375Z digest=sha256:f0dfbd31752cb1571b24f2087811402414baa39bea24d073295d5c9059f1a099

Observation 498a4135-4849-4737-9270-f9c32238130e · outbound

This paper cites Space–ground fluid AI for 6G edge intelligence,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Space–ground fluid AI for 6G edge intelligence,

Reference 3

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raw_fallback, observed 2026-08-06T15:37:02.372930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:00.929395Z digest=sha256:4d647fa79a83e7ad2ba3bf0a3fb15cf2986745954d5aa155ee76cfc049e7579e

Observation c8cccb3b-c307-4cea-97aa-0c8081ea06a7 · outbound

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

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Communication-efficient learning of deep networks from decentralized data,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.356360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:00.935843Z digest=sha256:173ff1af0ecddd5f8733c3db20d996eb2349d1783937a8ec2cbb90f6ea083ef8

Observation 7a2debfd-8e32-42f9-8603-eb0251082c89 · outbound

This paper cites Federated machine learning: Concept and applications,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Federated machine learning: Concept and applications,

Reference 5

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no resolver link, observed 2026-08-06T15:37:00.941941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:37:00.941941Z digest=sha256:f31229968e5e8e872b1fb23a74a3d1363e88dc4bdf2a02bc8d37d6a9279925f3

Observation 353a3a87-7351-419c-99db-ee68d50fd2dd · outbound

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

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Advances and open problems in federated learning,

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.330975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:00.949478Z digest=sha256:fde85be79159b1ade5c06c7947ea8a57e0adc325f8f860f20223c411de33d7b6

Observation 7804f621-a3b6-4113-b99c-b9a0683be050 · outbound

This paper cites Fedhome: Cloud-edge based personalized federated learning for in-home health monitoring,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Fedhome: Cloud-edge based personalized federated learning for in-home health monitoring,

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.314298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:00.955106Z digest=sha256:598515b677ed6a255e68fa85b215e79f793dbcf9e33afd135f3ca176ace36a40

Observation ee05dba4-ee19-4c47-9041-90ba5f0527c0 · outbound

This paper cites GeFL: Gradient encryption- aided privacy preserved federated learning for autonomous vehicles,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity GeFL: Gradient encryption- aided privacy preserved federated learning for autonomous vehicles,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.298949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:00.962686Z digest=sha256:5e525e13cca05dc063c73f32ac7d3a981015229c5b69fc11cb156710f409ade1

Observation 42002947-c4fd-49ce-bd82-6a2b99bbf5a1 · outbound

This paper cites Federated Learning: Strategies for Improving Communication Efficiency.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Federated Learning: Strategies for Improving Communication Efficiency

Reference 9

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unresolved
no resolver link, observed 2026-08-06T15:37:00.967659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:37:00.967659Z digest=sha256:c67576571d4816f0ffc4113d7b8ef7e40b745028a5a17256612843e8a21e89bc

Observation 7316513a-b46a-4541-928c-93c17e83b864 · outbound

This paper cites Model pruning enables efficient federated learning on edge devices,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Model pruning enables efficient federated learning on edge devices,

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.283901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:00.972864Z digest=sha256:252b7a4a0b88c932519ea4dba3633ffbbca7bc64a5739e1203d3840f41c97ca8

Observation 23ca3f55-0c6e-4fe5-b358-5d3372cf3a4e · outbound

This paper cites Deploying federated learning in large-scale cellular networks: Spatial convergence analysis,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Deploying federated learning in large-scale cellular networks: Spatial convergence analysis,

Reference 11

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raw_fallback, observed 2026-08-06T15:37:02.268906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:00.978036Z digest=sha256:10aca862492c763270828a227e87621077f8372c30984785930beb07050e80ad

Observation 14f4e6db-155d-4301-bfea-de9e28571a0c · outbound

This paper cites UVeQFed: Universal vector quantization for federated learning,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity UVeQFed: Universal vector quantization for federated learning,

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.254445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:00.983173Z digest=sha256:ec024cae7c3c044cb156d022984628e5d0d295552b5e9789f1bbca4c423e2aa6

Observation 643f8d89-45e3-469a-a11b-4bac4179648c · outbound

This paper cites Communication-Efficient Federated Learning with Dual-Side Low-Rank Compression.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Communication-Efficient Federated Learning with Dual-Side Low-Rank Compression

Reference 13

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local_arxiv, observed 2026-08-06T15:37:01.641832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:00.987955Z digest=sha256:77598ba4f55386f058d3d952d914bab318d56e6844cec71fe26415d41ad0e6c5

Observation b87be946-3699-41e0-88a2-3bf53d95cca4 · outbound

This paper cites Splitfed: When federated learning meets split learning,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Splitfed: When federated learning meets split learning,

Reference 14

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unresolved
no resolver link, observed 2026-08-06T15:37:00.994277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:37:00.994277Z digest=sha256:51f7a62c1b2e9f357ca2394db58ca37d1e7138dbc9fd3256d862f044238cddc3

Observation 520cbb0d-d066-4cfe-92ba-88feda161fee · outbound

This paper cites Broadband analog aggregation for low-latency federated edge learning,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Broadband analog aggregation for low-latency federated edge learning,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.229138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:00.999196Z digest=sha256:b2d9d5077ed561ff31835a6ab7ddfc68ce139f14254b8fd1a092b3c139cfbbc8

Observation 256c6687-38c7-49d3-85ff-02037b01ba0d · outbound

This paper cites Federated learning via over- the-air computation,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Federated learning via over- the-air computation,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.215352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.007857Z digest=sha256:f2439f3ccb2c009a5b94983670f9cffb8b2adddf5c3dfe2648d83d10ecb06665

Observation b56b1464-ce1a-4d39-9158-79d24ec68518 · outbound

This paper cites Spectrum breathing: Protecting over-the-air federated learning against interference,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Spectrum breathing: Protecting over-the-air federated learning against interference,

Reference 17

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raw_fallback, observed 2026-08-06T15:37:02.199963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.013355Z digest=sha256:c4e114dbc9e7e806cf5e921de1274a993d69ec4198a07857a9e25e82553d53bf

Observation ddf4775f-0d03-48ee-a573-a9581e925782 · outbound

This paper cites Airbreath sensing: Protecting over-the-air distributed sensing against interference,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Airbreath sensing: Protecting over-the-air distributed sensing against interference,

Reference 18

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no resolver link, observed 2026-08-06T15:37:01.018242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:37:01.018242Z digest=sha256:f382e1b3d279c96cf09f539d757c9c7c5753870c4a28c58463c6399bf48fc459

Observation 8d02eb3f-1305-4fc7-b705-7603c7ac9d1c · outbound

This paper cites Federated learning over wireless fading channels,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Federated learning over wireless fading channels,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.184339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.024023Z digest=sha256:920670fc2935d0ae1d22b9e83d8f8a9a555e91683f3d16a967679524030960c9

Observation 13cba22f-359a-4214-8435-9befa4382cb2 · outbound

This paper cites Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Reference 20

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no resolver link, observed 2026-08-06T15:37:01.029636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:37:01.029636Z digest=sha256:6a47bff21506d27fbb642ef6d9da63cc95bada6e405dcc0a7bf1d03fefcd6897

Observation 0b646557-2f4e-46f5-85b6-35e92d26514d · outbound

This paper cites To talk or to work: Dynamic batch sizes assisted time efficient federated learning over future mobile edge devices,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity To talk or to work: Dynamic batch sizes assisted time efficient federated learning over future mobile edge devices,

Reference 21

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raw_fallback, observed 2026-08-06T15:37:02.166172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.035876Z digest=sha256:8dc3d64436d53e268b646da02f47a842cdcdb0713cfafad1196b46b86bc73438

Observation 95f586ac-404e-4741-8d95-46c4d8caa8d9 · outbound

This paper cites ARM Cortex-M7 Processor Datasheet,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity ARM Cortex-M7 Processor Datasheet,

Reference 22

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raw_fallback, observed 2026-08-06T15:37:02.149470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.041445Z digest=sha256:9e410e44e13ce410947551d03f6b00dd312d5095bd4952608f8e0e83116e00cf

Observation efec4618-3dd3-49c5-a1c1-ef2d0cffb553 · outbound

This paper cites Apple A18 Pro Chip Specifications,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Apple A18 Pro Chip Specifications,

Reference 23

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raw_fallback, observed 2026-08-06T15:37:02.131528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.046432Z digest=sha256:f51f000b28a6ca3c966d16f6e53f421784312f2edf00967204d6800a9e8e2257

Observation 0ca72c45-a87b-4f0e-8314-4d845f85de04 · outbound

This paper cites Asynchronous Federated Optimization.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Asynchronous Federated Optimization

Reference 24

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no resolver link, observed 2026-08-06T15:37:01.051178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:37:01.051178Z digest=sha256:cb1ac66a7181620eaf0149c841d1c62669eadfa50fd62ef2766a033f7f0ee8c2

Observation a3aa833a-7a25-4f85-aed1-0d3a3890abb5 · outbound

This paper cites Asynchronous federated learning over wireless communication networks,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Asynchronous federated learning over wireless communication networks,

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.103001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.057160Z digest=sha256:9f8d43f23c4fcc1efe481978697fba9bd4e09736deb2b5256f9c476e0d0dd59f

Observation 26ca3aca-d19a-4896-9643-96a6009e38bc · outbound

This paper cites Asynchronous federated learning on heterogeneous devices: A survey,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Asynchronous federated learning on heterogeneous devices: A survey,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.083582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.061927Z digest=sha256:c72e0dc113aa5e654689db03ea6272e17aed635f94e5306153d4dc50bdacface

Observation 334d32d9-8901-44ac-967a-5e338c80dbe9 · outbound

This paper cites Revisiting Distributed Synchronous SGD.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Revisiting Distributed Synchronous SGD

Reference 27

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unresolved
no resolver link, observed 2026-08-06T15:37:01.067056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:37:01.067056Z digest=sha256:c16bc6e6388791014747db4097094b5c2b8854dff55779baf5840e8c91e53be3

Observation 80f15f1f-8c58-4b4c-9879-a8db5137a6ee · outbound

This paper cites Bandwidth allocation for multiple federated learning services in wireless edge networks,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Bandwidth allocation for multiple federated learning services in wireless edge networks,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.061378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.073703Z digest=sha256:f0093ec8cca4122118bda774d555954e31fe7bbd6846777aafa0e4b0a67a0c2e

Observation 234950dc-ef25-45dc-9ef0-a160114cc7a7 · outbound

This paper cites Client selection and bandwidth allocation in wireless federated learning networks: A long-term perspective,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Client selection and bandwidth allocation in wireless federated learning networks: A long-term perspective,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.044580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.079851Z digest=sha256:d66b7ec33cd960c6b79d74ec5231c9f3ba7a29d5030d75df7771b51243aa20d9

Observation 37dbb8db-67f1-4711-8ac4-9d6466e15797 · outbound

This paper cites Joint device schedul- ing and resource allocation for latency constrained wireless federated learning,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Joint device schedul- ing and resource allocation for latency constrained wireless federated learning,

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.026358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.084400Z digest=sha256:b2b4ee7a7f9e5503677525ff9d1481d64de2545c9b226ae3e9490cff645371b7

Observation f40c894f-96e0-4668-aefe-0d2dc5fb39e9 · outbound

This paper cites Wirelessly powered federated edge learning: Optimal tradeoffs between convergence and power transfer,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Wirelessly powered federated edge learning: Optimal tradeoffs between convergence and power transfer,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-06T15:37:02.007007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.090296Z digest=sha256:58aa331d6bac119f7f47aa8416373fe313c08cf267db8bdcf11cef5968d580e7

Observation f12bd5fe-d6ed-4d45-b9dc-b5e6c3a8f96a · outbound

This paper cites Adaptive batch size for federated learning in resource-constrained edge computing,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Adaptive batch size for federated learning in resource-constrained edge computing,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:01.987654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.095112Z digest=sha256:46e3a544f7dcce89ecd6d382fa3fc75fadb20e4020008700234f2cfe1162c46a

Observation 31f09d37-217f-4d6e-b29a-6bae404c6465 · outbound

This paper cites AMBLE: Adjusting mini-batch and local epoch for federated learning with heterogeneous devices,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity AMBLE: Adjusting mini-batch and local epoch for federated learning with heterogeneous devices,

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-06T15:37:01.963176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.104145Z digest=sha256:7ac44f32a8aa09970da2edbc81d2b0001e84c89485bddf419416483842ce52c3

Observation 52852d83-611c-4cfa-8634-415a8d04a318 · outbound

This paper cites Optimal batch allocation for wireless federated learning,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Optimal batch allocation for wireless federated learning,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:01.944062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.110360Z digest=sha256:72c00083e3bea25cc7068d6afae19cba581ddbdec196234a20292ff7e4842df7

Observation bcd4bf94-6cff-4eba-8045-ba7c8d010051 · outbound

This paper cites Accelerating DNN training in wireless federated edge learning systems,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Accelerating DNN training in wireless federated edge learning systems,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:01.924433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.116111Z digest=sha256:8ad4d5b9849ac828535a03659de2b54be7b3b5f90ccfc4d964c6cc268298eaa5

Observation 17772427-4c5b-47f2-9431-a6437275b40a · outbound

This paper cites Adaptive batchsize selection and gradient compression for wireless federated learning,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Adaptive batchsize selection and gradient compression for wireless federated learning,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:01.907488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.121906Z digest=sha256:8d89885e02a883f15d4a7b51aa652d45149596c5b7a57168aa9f8c82391e96c6

Observation 96e0fce2-d3a8-498f-baac-19dee4716782 · outbound

This paper cites DYNAMITE: Dynamic interplay of mini-batch size and aggregation frequency for federated learning with static and streaming datasets,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity DYNAMITE: Dynamic interplay of mini-batch size and aggregation frequency for federated learning with static and streaming datasets,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:01.888296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.127978Z digest=sha256:a6bc48daac412a0f2d76b87a4a54cd03b0200efc3527f3b2e31d3eee4a37dbea

Observation 03248b12-57f2-4bb7-8be2-3a3a0c57b694 · outbound

This paper cites On the convergence properties of a $K$-step averaging stochastic gradient descent algorithm for nonconvex optimization.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity On the convergence properties of a $K$-step averaging stochastic gradient descent algorithm for nonconvex optimization

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:37:01.451148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.133527Z digest=sha256:06560e5c84a7408e6a4098da8f54f64ace70160452cbf25853f47316170c8ece

Observation bcc73cc1-c011-4380-abfb-5ed1d73bd75a · outbound

This paper cites Parallel restarted SGD with faster con- vergence and less communication: Demystifying why model averaging works for deep learning,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Parallel restarted SGD with faster con- vergence and less communication: Demystifying why model averaging works for deep learning,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:01.867539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.138639Z digest=sha256:bae1a05faa917e57cadc459122fab281265ce6b9480270a6e1a80fa150eb5a6b

Observation 8ceca58d-6546-4941-8c1d-4bf53fa80b42 · outbound

This paper cites One-bit over-the-air aggregation for communication-efficient federated edge learning: Design and convergence analysis,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity One-bit over-the-air aggregation for communication-efficient federated edge learning: Design and convergence analysis,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:01.848904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.143287Z digest=sha256:410610231eacf2bed746caff780e4f9e3fd2bae04df19b50f01d42d3510f0705

Observation 3ba11c7a-060c-4bfc-98b7-a12bede51f12 · outbound

This paper cites A method for the solution of certain non-linear problems in least squares,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity A method for the solution of certain non-linear problems in least squares,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:01.828437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.149458Z digest=sha256:b706ada28b2d9e3d06c1b660b4d9860ebbfabe6354c44f3f351c60e685a15882

Observation 35267146-32a4-40d0-9aa0-211ff634e27a · outbound

This paper cites an unresolved cited work.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-06T15:37:01.796085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.154774Z digest=sha256:da425871426660eec4ef9ad052b91a8eed6499251987d827586d133b007b2ad8

Observation a08dc60b-0623-4f82-9f19-a6eebe39971e · outbound

This paper cites Ultra-Low-Latency Edge Inference for Distributed Sensing.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Ultra-Low-Latency Edge Inference for Distributed Sensing

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T15:37:01.159038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:37:01.159038Z digest=sha256:b9da4da74e9904e27f22a6368e9197fbf3fc6f5a0e7ac3ae3406d009a63fad27

Observation 369b842a-7cd4-4bde-aa8b-15eaa9d332ba · outbound

This paper cites Accessed: Oct.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Accessed: Oct

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:01.775272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.164377Z digest=sha256:afc04d0182f9a2546620d3e162dd9433aa1313c03b4eb51931a3cdb6f783849f

Observation 27152bde-f955-4963-8141-f277170a1c35 · outbound

This paper cites Accessed: Oct.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Accessed: Oct

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:01.757417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.169269Z digest=sha256:16283bb1256e941057ef5d93292afbcb1c75589436696410e5614409fef405b5

Observation 6886ecac-b194-4714-b23c-98da5447d332 · outbound

This paper cites Gradient-based learning applied to document recognition,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Gradient-based learning applied to document recognition,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:01.740111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.173898Z digest=sha256:a96fd046dfd31f81c187af95e9543bccd04606b4a94a9464647eeac78028aef9

Observation e7fc5793-0144-41a9-88b1-ccf635c80bd8 · outbound

This paper cites Learning multiple layers of features from tiny images,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Learning multiple layers of features from tiny images,

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T15:37:01.179690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:37:01.179690Z digest=sha256:b8ab2ac6f3d9b6b6ce86754b297c487f3f522b8759606868de9d8339a264bba4

Observation 37c2732d-6fc6-4b14-8db2-0fccb598c518 · outbound

This paper cites Deep residual learning for image recognition,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Deep residual learning for image recognition,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:37:01.711126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:37:01.184782Z digest=sha256:73455d91021ff69e0fac571f887180a6df915917abe17340851ac8aae10ccb61

Observation 3fca37bc-2096-4fc7-9a95-20d6a1d84b6f · outbound

This paper cites Revisiting outage for edge inference systems,.

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity Revisiting outage for edge inference systems,

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-06T15:37:01.189240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:37:01.189240Z digest=sha256:ae4f3b0695f3eb308b77c6776da8649953423bcd6c2197d3cc99f36b710c1793

Pith citing papers

Observation b85938c2-440d-4ebc-a1dd-467dd5a1bb8e · inbound

Optimizing Split Federated Learning with Unstable Client Participation cites this paper.

Optimizing Split Federated Learning with Unstable Client Participation Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-18T15:26:33.777262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T15:24:04.079011Z digest=sha256:6e73d5ceaf0ccadf4088c27c47929acf3247280ab6655f4a79dd86e5cb6ea83b