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Paper Citation Record · LEDGER

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission

As of 15 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2507.00082.

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

pith.paper-citation-record.v1
2507.00082 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:45:48.692295Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

40 of 40 outbound references displayed

  • verified exact2
  • verified fuzzy32
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8e9458d5-ebee-4517-88be-589336bdbebe · outbound

This paper cites Split Federated Learning-Empowered Energy-Efficient Mobile Traffic Prediction Over UA Vs ,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Split Federated Learning-Empowered Energy-Efficient Mobile Traffic Prediction Over UA Vs ,

Reference 1

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation cc50b633-301f-41c5-a741-60e91b48b010 · outbound

This paper cites Federated Learning- Empowered Mobile Network Management for 5G and Beyond Net- works: From Access to Core,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Federated Learning- Empowered Mobile Network Management for 5G and Beyond Net- works: From Access to Core,

Reference 2

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raw_fallback, observed 2026-08-06T21:45:54.288486Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T21:45:46.306892Z digest=sha256:502f67b492eb511cd29da77a606a017099052bfcebe16ea606a01e955015e58c

Observation 920d04da-6072-4aa3-acf8-a35fc91dddfa · outbound

This paper cites Division-of-Thoughts: Harnessing Hybrid Language Model Synergy for Efficient On-Device Agents.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Division-of-Thoughts: Harnessing Hybrid Language Model Synergy for Efficient On-Device Agents

Reference 3

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local_arxiv, observed 2026-08-06T21:45:49.172649Z

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Observation e6d01f87-fe73-44ce-9e73-9cfbe25714e2 · outbound

This paper cites Heterogeneous Privacy Level- Based Client Selection for Hybrid Federated and Centralized Learning in Mobile Edge Computing,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Heterogeneous Privacy Level- Based Client Selection for Hybrid Federated and Centralized Learning in Mobile Edge Computing,

Reference 4

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T21:45:46.417197Z digest=sha256:ade6a3679c47a4b39efc9be4936023b2c182d134d51f35024634e80ece445018

Observation a275d5bf-fd63-44f0-8cfd-76bbae4caefb · outbound

This paper cites Token Communications: A Large Model-Driven Framework for Cross-modal Context-aware Semantic Communications.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Token Communications: A Large Model-Driven Framework for Cross-modal Context-aware Semantic Communications

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:45:46.454001Z digest=sha256:66f8033753e36815ee69747101bbfdb5f425ababa7c261298b996372b95f0940

Observation 8cc3b186-c93c-4ed4-a718-aa548b712872 · outbound

This paper cites QoSBERT: An Uncertainty- Aware Approach based on Pre-trained Language Models for Service Quality Prediction,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission QoSBERT: An Uncertainty- Aware Approach based on Pre-trained Language Models for Service Quality Prediction,

Reference 6

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T21:45:46.504545Z digest=sha256:b92babe03f953b6dbdb2272a44ee4cec507ce86991c7e48a00b1843966193784

Observation 201238ac-f1b0-4334-8f42-a25426d69151 · outbound

This paper cites PromptFL: Let Federated Participants Cooperatively Learn Prompts Instead of Models – Federated Learning in Age of Foundation Model,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission PromptFL: Let Federated Participants Cooperatively Learn Prompts Instead of Models – Federated Learning in Age of Foundation Model,

Reference 7

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T21:45:46.597804Z digest=sha256:7fd6a0368326f0f91014bed0e8a903a6ad8e90e70ae8f1a59ad25fed66f4b27a

Observation e9521812-fc4f-4d41-9a8b-a549617802f1 · outbound

This paper cites Communication-Efficient Learning of Deep Networks from Decentralized Data.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 8

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source=pdf_text observed=2026-08-06T21:45:46.639702Z digest=sha256:9f47811f5cb4962df65ffda3807f4757bb587e6d549b036231a30ca77551cbe4

Observation 23118c12-9483-4a14-a174-eae6d6c7d1f0 · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Efficiently Modeling Long Sequences with Structured State Spaces

Reference 9

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source=pdf_text observed=2026-08-06T21:45:46.703680Z digest=sha256:c45e26286d05225476a4a7a1e7cf1a785d1aade570785bf43827d87455027b63

Observation 00697f54-1dc8-452c-9cb8-e8623308706e · outbound

This paper cites Speculative Decoding for Neural Sequence Models,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Speculative Decoding for Neural Sequence Models,

Reference 10

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source=pdf_text observed=2026-08-06T21:45:46.780674Z digest=sha256:14eb4195f09469df617a95d47165558dcb64b4cd04358ac4f86feffed98d9e9b

Observation 2251e002-1a79-43dc-b92f-0c5931e4c2ed · outbound

This paper cites Hybrid SLM and LLM for Edge-Cloud Collaborative Inference,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Hybrid SLM and LLM for Edge-Cloud Collaborative Inference,

Reference 11

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source=pdf_text observed=2026-08-06T21:45:46.827691Z digest=sha256:76da22e12f956886ff4bc4fbeda24abd62808317197fea79cbf525f6a98a103e

Observation e69cb184-527a-476b-a3f4-5f6b4658ccff · outbound

This paper cites HLM-Cite: Hybrid Language Model Workflow for Text-based Scientific Citation Prediction.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission HLM-Cite: Hybrid Language Model Workflow for Text-based Scientific Citation Prediction

Reference 12

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source=pdf_text observed=2026-08-06T21:45:46.880146Z digest=sha256:75f21eaff0955b8b895ae85f2fd80471842b43caf8c286e80fe4914d6b19241a

Observation 2cde85a1-7444-4730-b1f8-bb84247624e9 · outbound

This paper cites Decentralizing large-scale natural language processing with federated learning,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Decentralizing large-scale natural language processing with federated learning,

Reference 13

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source=pdf_text observed=2026-08-06T21:45:46.979511Z digest=sha256:2fbd112d63ae0a3122f231412745b8e56b48bec0fe75e043c353b368689b47f6

Observation b4bf532c-c99a-4362-b8c0-60e17dd7686d · outbound

This paper cites Federated Learning: Strategies for Improving Communica- tion Efficiency,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Federated Learning: Strategies for Improving Communica- tion Efficiency,

Reference 14

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source=pdf_text observed=2026-08-06T21:45:47.042948Z digest=sha256:5af3d7dddd33d93c84760eda29344927e8eaf39a96cf7264c145514f33e78b43

Observation d6c38f6f-9e89-4d7b-8827-8ee9243835c8 · outbound

This paper cites Decentralized Training of Foundation Models in Heterogeneous Environments,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Decentralized Training of Foundation Models in Heterogeneous Environments,

Reference 15

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source=pdf_text observed=2026-08-06T21:45:47.066790Z digest=sha256:7fd133079b03c1b2796539cb054851b081fc7ccfafedc7472387c01e303554b4

Observation 6b0cb917-7ae5-4375-a2ae-73365aec915d · outbound

This paper cites FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks

Reference 16

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source=pdf_text observed=2026-08-06T21:45:47.128602Z digest=sha256:8c037b413f57000001867dc4ad66131f3633bdf95ad316d3379e94c4be6d1be2

Observation 8d8996cb-8b09-458f-a71d-a2c65367a14d · outbound

This paper cites Federated Few-Shot Learning for Mobile NLP,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Federated Few-Shot Learning for Mobile NLP,

Reference 17

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source=pdf_text observed=2026-08-06T21:45:47.179755Z digest=sha256:bc0eb740415099a2ad8fec39807332d4010e6f63d59688bcc7ba7f7007c2ce85

Observation 3612ff31-3b53-4001-a26b-e22a1e85f596 · outbound

This paper cites Efficient Federated Learning for Modern NLP,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Efficient Federated Learning for Modern NLP,

Reference 18

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d072e635-a15e-4167-973f-4ed594d51b58 · outbound

This paper cites Federated Learning Meets Natural Language Processing: A Survey.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Federated Learning Meets Natural Language Processing: A Survey

Reference 19

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source=pdf_text observed=2026-08-06T21:45:47.296289Z digest=sha256:1e7dc4e96b0bfe90b993322052ada4d7a2e554648193b051f7ec35badef1b152

Observation 0b678ef2-2489-425c-a2df-bd605d3bf6ce · outbound

This paper cites TITANIC: Towards Production Federated Learning with Large Language Models,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission TITANIC: Towards Production Federated Learning with Large Language Models,

Reference 20

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source=pdf_text observed=2026-08-06T21:45:47.384466Z digest=sha256:3bf3e4337eb79b29b48410bee36f3279a217bd02d3081322d9d79b02e8e31193

Observation bb889028-c4c4-4ff8-aa03-38e744412445 · outbound

This paper cites Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning,

Reference 21

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source=pdf_text observed=2026-08-06T21:45:47.438674Z digest=sha256:150bdadfd26b75a7734f2ab65050a6649ec6f9a32e345901ac805ceda49ddd6b

Observation d8764604-2b5a-482e-b112-dd78a8aee11c · outbound

This paper cites Uncertainty-Aware Deep Learning Models for Wireless Communication Systems,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Uncertainty-Aware Deep Learning Models for Wireless Communication Systems,

Reference 22

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Observation 1b80c502-3f8f-4fad-a59b-89efaa5bbae2 · outbound

This paper cites DropConnect is Effective in Modeling Uncertainty of Bayesian Deep Networks,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission DropConnect is Effective in Modeling Uncertainty of Bayesian Deep Networks,

Reference 23

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T21:45:47.548211Z digest=sha256:9646055199b5b60d6b6cbb0351f9e3f076471a2564fc7c1aee27e10fa11dd8d1

Observation 7a0d0016-5a5f-4a28-949a-78669f78b654 · outbound

This paper cites Survey of Dropout Methods for Deep Neural Networks,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Survey of Dropout Methods for Deep Neural Networks,

Reference 24

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source=pdf_text observed=2026-08-06T21:45:47.662671Z digest=sha256:0f7f6a77ea168d76fe62bbe1df773c1f842efbffed0dd790295468a858f383f7

Observation 7fff07b8-6887-4377-a8d2-2c8abe93ccb4 · outbound

This paper cites Active Learning Literature Survey,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Active Learning Literature Survey,

Reference 25

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source=pdf_text observed=2026-08-06T21:45:47.736623Z digest=sha256:166fadf17488e7fd2887faecfe5c8b398ad5f1c3bd2eeccdd9cbe4224098c348

Observation 5b37fb82-2c98-4374-8942-9a0a3cb8da21 · outbound

This paper cites Active Learning Using Uncertainty Informa- tion,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Active Learning Using Uncertainty Informa- tion,

Reference 26

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T21:45:47.787717Z digest=sha256:5f49906bb274d616287667150ed3a2dfffe385f801321820b1ed70c3b03cf859

Observation 387a0066-3b91-4547-80b6-e82709433485 · outbound

This paper cites Active Learning With Sampling by Uncertainty and Density for Data Annotations,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Active Learning With Sampling by Uncertainty and Density for Data Annotations,

Reference 27

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T21:45:47.862041Z digest=sha256:946af3a7c4ec7eb27cc5b305620de3e38be94480b010cc48c98cd515cd90345a

Observation cf0da691-99aa-4005-baf7-7a635aa595c6 · outbound

This paper cites How to Measure Uncertainty in Uncertainty Sampling for Active Learning,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission How to Measure Uncertainty in Uncertainty Sampling for Active Learning,

Reference 28

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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.

source=pdf_text observed=2026-08-06T21:45:47.969635Z digest=sha256:22f16c86463cb2e459e4d0c62a8c1c0e40886dcaa2efa632477e58b3abc56658

Observation bca219dd-98a6-4620-9087-f23e70a5c413 · outbound

This paper cites Confidence Estimation for Natural Language Processing: A Study on Machine Translation,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Confidence Estimation for Natural Language Processing: A Study on Machine Translation,

Reference 29

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source=pdf_text observed=2026-08-06T21:45:48.023187Z digest=sha256:9596245ae0de99de46da0a36ab4505b92a65da34887b54bc16e6b3c61badaf09

Observation 036e4195-0ac2-4c3f-8c67-b3b00357fb4b · outbound

This paper cites High-Confidence Classification of Partial Discharge Acoustic Signals Using Bayesian Networks for Uncertainty Quantifica- tion,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission High-Confidence Classification of Partial Discharge Acoustic Signals Using Bayesian Networks for Uncertainty Quantifica- tion,

Reference 30

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T21:45:48.072837Z digest=sha256:5616ab5f28425b234ba63528459214a9996113e7e32863a837c896e05dfc904d

Observation 3e383de1-01f3-4c20-937a-248dedcc1e00 · outbound

This paper cites SnapCFL: A Pre-clustering-based Clustered Federated Learning Framework for Data and System Heterogeneities,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission SnapCFL: A Pre-clustering-based Clustered Federated Learning Framework for Data and System Heterogeneities,

Reference 31

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T21:45:48.108898Z digest=sha256:49ba1b181a8b5fb62ae9a5e1c1a5f8f261e97ed9b9b57bd568a1209be2787b76

Observation f0e4838b-3e57-4d96-936f-721d7469318b · outbound

This paper cites On the Conver- gence of FedAvg on Non-IID Data,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission On the Conver- gence of FedAvg on Non-IID Data,

Reference 32

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T21:45:48.193719Z digest=sha256:eebf98a229488c8a5f2a7faf007179ab5387ed267bd73f444bb5dd649c220b8a

Observation 80123d39-6df2-4623-a523-df0d5cba8743 · outbound

This paper cites SCAFFOLD: Stochastic Controlled Averaging for Federated Learning,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission SCAFFOLD: Stochastic Controlled Averaging for Federated Learning,

Reference 33

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T21:45:48.268056Z digest=sha256:15733f8c5816d21287049d36379f9ff95a81f08fb1f5df31b418e91d39fff7b7

Observation 76a11141-a03f-4ac7-b2d7-b0d1797161cc · outbound

This paper cites Tighter Theory for Local SGD on Identical and Heterogeneous Data,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Tighter Theory for Local SGD on Identical and Heterogeneous Data,

Reference 34

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raw_fallback, observed 2026-08-06T21:45:50.310932Z

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.

source=pdf_text observed=2026-08-06T21:45:48.301240Z digest=sha256:cd80a56d9c0e4424c6908064e59323763fc62878087b106980121112982152c8

Observation 1ed2eace-6d1b-4475-b978-d9a7e2349f46 · outbound

This paper cites Federated Optimization in Heterogeneous Networks,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Federated Optimization in Heterogeneous Networks,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:45:50.201298Z

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.

source=pdf_text observed=2026-08-06T21:45:48.391943Z digest=sha256:36f0060b723326bfe6e6b3188fc454edad5f55e943406f5469c1ec0e8d1b3f73

Observation 986e36d8-0311-4bdb-a6fe-4d2dc2d7fe8b · outbound

This paper cites Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimiza- tion,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimiza- tion,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:45:50.056995Z

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.

source=pdf_text observed=2026-08-06T21:45:48.459877Z digest=sha256:9928dd47221cf81028a54031adcb9cfc19d9b85065826f68d4ba23b41161042f

Observation 434e8113-472a-4754-bc0b-22ed14b2a966 · outbound

This paper cites Character-level Convolutional Networks for Text Classification,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Character-level Convolutional Networks for Text Classification,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:45:49.952602Z

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.

source=pdf_text observed=2026-08-06T21:45:48.519854Z digest=sha256:f022c9a2a9c7ed8da16f867112a6b340ea8ff8b1366a246fb4c7c3642c67e3ae

Observation f34db915-347d-4c2d-a126-20386d8be42e · outbound

This paper cites BERT: Pre- Training of Deep Bidirectional Transformers for Language Understand- ing,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission BERT: Pre- Training of Deep Bidirectional Transformers for Language Understand- ing,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:45:49.794177Z

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.

source=pdf_text observed=2026-08-06T21:45:48.568165Z digest=sha256:41a44240ac52a85d282853b543bb7b1ea7337c86902ac3d0e625fdf00237ba05

Observation 902499c9-fbfd-4219-a15f-d1650ca6ec1b · outbound

This paper cites Transformers: State-of-the-Art Natural Language Processing,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Transformers: State-of-the-Art Natural Language Processing,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:45:49.645128Z

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.

source=pdf_text observed=2026-08-06T21:45:48.623887Z digest=sha256:54dd024ea83b7dd6614f3450012e7dd765d258199f00de1a40b865fb58e9e893

Observation f22e2d8e-d632-4c95-bd56-2c45ed45d4a2 · outbound

This paper cites Hybrid SLM and LLM for Edge-Cloud Collaborative Inference,.

Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission Hybrid SLM and LLM for Edge-Cloud Collaborative Inference,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:45:49.353955Z

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.

source=pdf_text observed=2026-08-06T21:45:48.692295Z digest=sha256:c40b2ab5b4d399b7f497efbb32848a185560e71b4cc0eaa5cb187d3592250b9e

Pith citing papers

No inbound Pith citation observations are available.