Paper Citation Record · LEDGER

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

As of 13 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 2026-08-13T06:32:02.005865+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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:54.441492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:54.288486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:45:49.172649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:54.127644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-06T21:45:46.454001Z

Source-reported events for the cited work

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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

Resolution: verified exact; raw_fallback, observed 2026-08-06T21:45:49.004062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:53.935865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-06T21:45:46.639702Z

Source-reported events for the cited work

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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

Resolution: unresolved; no resolver link, observed 2026-08-06T21:45:46.703680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:53.776402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:53.563581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-06T21:45:46.880146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:53.416685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:53.245187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:53.000941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-06T21:45:47.128602Z

Source-reported events for the cited work

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:52.842257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:52.685878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-06T21:45:47.296289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:52.492168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:52.297566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:52.124763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:51.984526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:51.870985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:51.685267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:51.536621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:51.383031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:51.236530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:51.081966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:50.935765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:50.764619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:50.611825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:45:50.429545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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

Resolution: verified fuzzy; 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 2026-08-13T06:32:02.005865+00:00.

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 2026-08-13T06:32:02.005865+00:00.

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 2026-08-13T06:32:02.005865+00:00.

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 2026-08-13T06:32:02.005865+00:00.

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 2026-08-13T06:32:02.005865+00:00.

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 2026-08-13T06:32:02.005865+00:00.

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 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.