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Paper Citation Record · LEDGER

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks

As of 9 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2505.23801.

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

pith.paper-citation-record.v1
2505.23801 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:58:01.093776Z

measured 23 of 23 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

23 of 23 outbound references displayed

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  • verified fuzzy14
  • unresolved9
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aa378dea-f2c8-4699-8f0b-9c1f8e11f178 · outbound

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

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Communication- efficient learning of deep networks from decentralized data,

Reference 1

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raw_fallback, observed 2026-08-07T13:58:04.585498Z

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.

source=pdf_text observed=2026-08-07T13:57:59.576651Z digest=sha256:3a80af37eff266f0ac9cbe3659e404404d151011b06cd6d5c5116e6741f31248

Observation 5e7a41e7-cc99-401e-88b5-abc3ca8253c3 · outbound

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

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Advances and open problems in federated learning,

Reference 2

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raw_fallback, observed 2026-08-07T13:58:04.381159Z

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.

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Observation 667ff839-7794-4135-a3f6-3d6acb82f4ce · outbound

This paper cites FedNLP: Benchmarking federated learning methods for natural language pro- cessing tasks,.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks FedNLP: Benchmarking federated learning methods for natural language pro- cessing tasks,

Reference 3

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raw_fallback, observed 2026-08-07T13:58:04.105034Z

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.

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Observation 3ac7f8a2-e8ec-4c0c-b8da-df5053a5a7cb · outbound

This paper cites Federated learning for speaker recognition based on self-attention mechanism,.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Federated learning for speaker recognition based on self-attention mechanism,

Reference 4

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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.

source=pdf_text observed=2026-08-07T13:57:59.692780Z digest=sha256:058f49b50b5e117e547844d36f10b9ac789c49931d8b17e67d74661a430504d7

Observation 9623322d-4b24-4ff1-818c-c0d67abeefe9 · outbound

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

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Federated Learning: Strategies for Improving Communication Efficiency

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:57:59.794589Z digest=sha256:8fb9b35978b915c5fc55d1832d244fe5577f85aa8419366d8e4d63e86dd710d7

Observation 1c26bd91-4bd3-4f35-bc7b-3414f264b1ca · outbound

This paper cites Federated Learning with Non-IID Data.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Federated Learning with Non-IID Data

Reference 6

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:57:59.877362Z digest=sha256:bd5a6a52877853c82c61477d61a81e9412310544e1287735fa0856ddde85033b

Observation ffcc9dc1-d55b-4d05-b5fa-2aa53bba70ce · outbound

This paper cites A joint learning and communica- tions framework for federated learning over wireless networks,.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks A joint learning and communica- tions framework for federated learning over wireless networks,

Reference 7

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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.

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Observation 7aa82d1f-beb6-4e6b-8311-6762bf6dd012 · outbound

This paper cites Federated optimization in heterogeneous networks,.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Federated optimization in heterogeneous networks,

Reference 8

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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.

source=pdf_text observed=2026-08-07T13:57:59.985885Z digest=sha256:e5f0a6a116e45edc2450b3b1a4c06daadd869b6cf1fad75e1cf5627be7ce411d

Observation c25115c0-37ec-4bf7-a528-67bafb015823 · outbound

This paper cites Adaptive federated learning in resource constrained edge computing systems,.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Adaptive federated learning in resource constrained edge computing systems,

Reference 9

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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.

source=pdf_text observed=2026-08-07T13:58:00.065530Z digest=sha256:793ed8f93e9a486983109b8c6c45b578d62e1a8a08312a615cf489c76563f29a

Observation ad4ac7f3-c4e4-409a-9ca3-648eff18f344 · outbound

This paper cites HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients

Reference 10

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:58:00.108600Z digest=sha256:7ddd9f0432c78a1402b6962fc787bfb91a795d59f4a9d295da285a4fd05b1c65

Observation 148e3c95-ec75-47ba-a9f0-a07fa1352d2f · outbound

This paper cites Federated Optimization in Heterogeneous Networks.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Federated Optimization in Heterogeneous Networks

Reference 11

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source=pdf_text observed=2026-08-07T13:58:00.158497Z digest=sha256:1de91053b3e7ea3efdd0aeec5b9aec44a2c723ea0361f15ef9507d158a473c51

Observation 4ab672e2-b73c-454d-ab97-e4fb6e5ee5bf · outbound

This paper cites Tackling the objective inconsistency problem in heterogeneous federated opti- mization,.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Tackling the objective inconsistency problem in heterogeneous federated opti- mization,

Reference 12

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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.

source=pdf_text observed=2026-08-07T13:58:00.192295Z digest=sha256:43a059a111cd5f2da76d80ff4c7be7891d72444cee0040f0f17483601f9db726

Observation 4a138edc-3637-4bdd-b3e3-05fe24fe21bf · outbound

This paper cites Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:58:00.222082Z digest=sha256:59f86a12d870fa3768deb0e92b1cecf07df280479775c32972c4a30fd8dcc50d

Observation 0d0d7a85-ba4b-4973-a221-90d1e51d3b7f · outbound

This paper cites Model Pruning Enables Efficient Federated Learning on Edge Devices.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Model Pruning Enables Efficient Federated Learning on Edge Devices

Reference 14

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source=pdf_text observed=2026-08-07T13:58:00.260183Z digest=sha256:65d725a1f3cb1c19cef986717170b53a39ae1e151bc581f83cdbe6d264b5df3f

Observation 84335d19-2e7e-4332-b0c3-81c476722d00 · outbound

This paper cites QSGD: Communication-efficient SGD via gradient quantization and encoding,.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks QSGD: Communication-efficient SGD via gradient quantization and encoding,

Reference 15

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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.

source=pdf_text observed=2026-08-07T13:58:00.285423Z digest=sha256:dd6b0b886dec6c8914840f1f3cba7167c9bbb67bd526d7b69384e08a09dbb230

Observation 709c9f1b-eb4a-481c-923e-c6bc7544eb05 · outbound

This paper cites Deep neural networks with massive learned knowledge,.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Deep neural networks with massive learned knowledge,

Reference 16

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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.

source=pdf_text observed=2026-08-07T13:58:00.385797Z digest=sha256:a4eb60eccbede7df2ad9bf57666aceda63a23a9e7efbbc8572dec5692a3ba54c

Observation f948481e-a079-468b-a164-6c946a6d5bb7 · outbound

This paper cites A secure federated learning framework for 5G networks,.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks A secure federated learning framework for 5G networks,

Reference 17

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:58:00.510648Z digest=sha256:903a90fddb70adabf92a4fb50ea1a22945cdd5a68ad07c415fd0a96bc9bc0316

Observation e510edee-786e-439e-845a-a7415818972f · outbound

This paper cites MobileBERT: a compact task- agnostic BERT for resource-limited devices,.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks MobileBERT: a compact task- agnostic BERT for resource-limited devices,

Reference 18

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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.

source=pdf_text observed=2026-08-07T13:58:00.621483Z digest=sha256:3998d27b7483e7286ee96c833f9582d2efac5f09c6bcc1e863404f5220a5135b

Observation 96d0ae08-156b-49f3-9da1-80f3cf31229c · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 19

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source=pdf_text observed=2026-08-07T13:58:00.701352Z digest=sha256:c7a69798152132abda6232a9a31fa697fab746d1cbbd8ed1acda084bced92c8e

Observation 06505bbb-163b-41d9-ad26-d46938c17af7 · outbound

This paper cites TinyBERT: Distilling BERT for Natural Language Understanding.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks TinyBERT: Distilling BERT for Natural Language Understanding

Reference 20

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source=pdf_text observed=2026-08-07T13:58:00.809775Z digest=sha256:b1c88b57ad0b2f6c143bd4a4a642f89b2cdc1681671aadec2eaf27cddc2bdb14

Observation 0c833a7a-7c81-4444-95f5-b1f4b7f12ec0 · outbound

This paper cites FedMD: Heterogenous Federated Learning via Model Distillation.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks FedMD: Heterogenous Federated Learning via Model Distillation

Reference 21

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:58:00.936539Z digest=sha256:fe8380076e06e8bb7f069d9f6c84c3a942e76d9500bb640bab05476dce99f39f

Observation ce5ecf7f-861c-4cbf-87ab-d14321a5e26c · outbound

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

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Ensemble distillation for robust model fusion in federated learning,

Reference 22

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:58:01.030017Z digest=sha256:59832aaa5ae734b95cbd4fca20bf5ad6db84587aee0169d19852663bb579af2f

Observation adf7da23-d7b8-423f-a721-c940faaef51c · outbound

This paper cites Client selection for federated learning with heterogeneous resources in mobile edge,.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks Client selection for federated learning with heterogeneous resources in mobile edge,

Reference 23

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Pith citing papers

No inbound Pith citation observations are available.