SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies | Paper Citation Record

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This paper cites Large language models: a comprehensive survey of its applications, challenges, limitations, and future prospects,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Large language models: a comprehensive survey of its applications, challenges, limitations, and future prospects,

Reference 1

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This paper cites Mm-llms: Recent advances in multimodal large language models,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Mm-llms: Recent advances in multimodal large language models,

Reference 2

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This paper cites Speech recognition meets large language model: Bench- marking, models, and exploration,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Speech recognition meets large language model: Bench- marking, models, and exploration,

Reference 3

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This paper cites SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings

Reference 4

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This paper cites Asr systems using llms a review,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Asr systems using llms a review,

Reference 5

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This paper cites LLM-PBE: Assessing Data Privacy in Large Language Models.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies LLM-PBE: Assessing Data Privacy in Large Language Models

Reference 6

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This paper cites Ethical considerations related to personal data collection and reuse: Trust and transparency in language and speech technologies,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Ethical considerations related to personal data collection and reuse: Trust and transparency in language and speech technologies,

Reference 7

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Observation 2e26dc6e-8c81-4df2-b269-50ea6e2799c6 · outbound

This paper cites Efl-peft: A communication efficient federated learning framework using peft sparsification for asr,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Efl-peft: A communication efficient federated learning framework using peft sparsification for asr,

Reference 8

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This paper cites Fed-ee: Federating hetero- geneous asr models using early-exit architectures,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Fed-ee: Federating hetero- geneous asr models using early-exit architectures,

Reference 9

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This paper cites Federating dynamic models using early-exit architectures for automatic speech recognition on het- erogeneous clients,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Federating dynamic models using early-exit architectures for automatic speech recognition on het- erogeneous clients,

Reference 10

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Observation 1a40ce22-658e-4c60-b5e1-51fbd97a791b · outbound

This paper cites Federated continual learning: Concepts, challenges, and solutions,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Federated continual learning: Concepts, challenges, and solutions,

Reference 11

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This paper cites A comparison of transformer and lstm encoder decoder models for asr,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies A comparison of transformer and lstm encoder decoder models for asr,

Reference 12

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This paper cites Improving scheduled sampling for neural transducer-based asr,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Improving scheduled sampling for neural transducer-based asr,

Reference 13

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This paper cites Conformer-based hybrid asr system for switchboard dataset,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Conformer-based hybrid asr system for switchboard dataset,

Reference 14

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This paper cites Long short-term memory recurrent neural network for automatic speech recognition,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Long short-term memory recurrent neural network for automatic speech recognition,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:28:37.283207Z

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This paper cites VoxPopuli: A large-scale multilingual speech corpus for representation learning, semi-supervised learning and interpretation,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies VoxPopuli: A large-scale multilingual speech corpus for representation learning, semi-supervised learning and interpretation,

Reference 16

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This paper cites Importance of smoothness induced by optimizers in fl4asr: Towards understanding federated learning for end-to-end asr,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Importance of smoothness induced by optimizers in fl4asr: Towards understanding federated learning for end-to-end asr,

Reference 17

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This paper cites Federated learning in ASR: Not as easy as you think,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Federated learning in ASR: Not as easy as you think,

Reference 18

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This paper cites A federated approach in training acoustic models.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies A federated approach in training acoustic models

Reference 19

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This paper cites Federated Self-supervised Speech Representations: Are We There Yet?.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Federated Self-supervised Speech Representations: Are We There Yet?

Reference 20

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This paper cites End-to-end speech recognition from feder- ated acoustic models,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies End-to-end speech recognition from feder- ated acoustic models,

Reference 21

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Observation 8df10243-3836-4766-b1a3-5c3ffac30e34 · outbound

This paper cites Federated learning for ASR based on Wav2vec 2.0,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Federated learning for ASR based on Wav2vec 2.0,

Reference 22

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Observation 3b75650e-5b1a-4be6-b877-91d180c1ff59 · outbound

This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representations,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 23

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Observation 8da2c1e8-9d38-4138-b2f7-efd97f29924f · outbound

This paper cites Federated Domain Adaptation for ASR with Full Self-Supervision.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Federated Domain Adaptation for ASR with Full Self-Supervision

Reference 24

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This paper cites Robust and communication-efficient federated learning from non-iid data,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Robust and communication-efficient federated learning from non-iid data,

Reference 25

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This paper cites To talk or to work: Flexible communication compression for energy efficient federated learning over heterogeneous mobile edge devices,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies To talk or to work: Flexible communication compression for energy efficient federated learning over heterogeneous mobile edge devices,

Reference 26

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This paper cites Sparsified SGD with memory,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Sparsified SGD with memory,

Reference 27

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This paper cites Neural network quantization in federated learning at the edge,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Neural network quantization in federated learning at the edge,

Reference 28

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This paper cites Communication-efficient personalized federated meta- learning in edge networks,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Communication-efficient personalized federated meta- learning in edge networks,

Reference 29

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SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Hierarchical federated learning with quantization: Convergence analysis and system design,

Reference 30

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This paper cites Data-free knowledge distillation for het- erogeneous federated learning,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Data-free knowledge distillation for het- erogeneous federated learning,

Reference 31

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This paper cites FedHM: Efficient Federated Learning for Heterogeneous Models via Low-rank Factorization.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies FedHM: Efficient Federated Learning for Heterogeneous Models via Low-rank Factorization

Reference 32

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This paper cites Federating Dynamic Models using Early-Exit Architectures for Automatic Speech Recognition on Heterogeneous Clients.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Federating Dynamic Models using Early-Exit Architectures for Automatic Speech Recognition on Heterogeneous Clients

Reference 33

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This paper cites Recurrent Early Exits for Federated Learning with Heterogeneous Clients.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Recurrent Early Exits for Federated Learning with Heterogeneous Clients

Reference 34

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This paper cites LoRA: Low-rank adaptation of large language models,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies LoRA: Low-rank adaptation of large language models,

Reference 35

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This paper cites Adaptive budget allocation for parameter-efficient fine- tuning,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Adaptive budget allocation for parameter-efficient fine- tuning,

Reference 36

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This paper cites Adapterfusion: Non-destructive task composition for transfer learning,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Adapterfusion: Non-destructive task composition for transfer learning,

Reference 37

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SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Parameter-efficient transfer learning for NLP,

Reference 38

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SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies LLaMA: Open and Efficient Foundation Language Models

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SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Gemini: A Family of Highly Capable Multimodal Models

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This paper cites Mistral 7B.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Mistral 7B

Reference 41

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This paper cites SLoRA: Federated parameter efficient fine-tuning of language models,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies SLoRA: Federated parameter efficient fine-tuning of language models,

Reference 42

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This paper cites Wavlm: Large-scale self-supervised pre-training for full stack speech processing,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Wavlm: Large-scale self-supervised pre-training for full stack speech processing,

Reference 43

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This paper cites Wavllm: Towards robust and adaptive speech large language model,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Wavllm: Towards robust and adaptive speech large language model,

Reference 44

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This paper cites Robust speech recognition via large-scale weak supervision,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Robust speech recognition via large-scale weak supervision,

Reference 45

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This paper cites TinyLlama: An Open-Source Small Language Model.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies TinyLlama: An Open-Source Small Language Model

Reference 46

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This paper cites Efficient and personalized mobile health event predic- tion via small language models,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Efficient and personalized mobile health event predic- tion via small language models,

Reference 47

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This paper cites When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 48

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This paper cites LoRA: Low-rank adaptation of large language models,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies LoRA: Low-rank adaptation of large language models,

Reference 49

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This paper cites How much knowledge can you pack into a lora adapter without harming llm?.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies How much knowledge can you pack into a lora adapter without harming llm?

Reference 50

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Observation ea45d728-05e1-417d-8815-83656a4f1f17 · outbound

This paper cites Slam-llm: A modular, open-source multimodal large language model framework and best practice for speech, language, audio and music processing,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Slam-llm: A modular, open-source multimodal large language model framework and best practice for speech, language, audio and music processing,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:28:36.162746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ba39f0cc-ee3f-4425-9aac-07938e29f97a · outbound

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

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Communication-efficient learning of deep networks from decentralized data,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:28:36.148490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3cd22959-d836-43ff-a555-1861104a6775 · outbound

This paper cites Librispeech: an asr corpus based on public domain audio books,.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Librispeech: an asr corpus based on public domain audio books,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:28:36.135769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 20b7887e-589c-459d-83a5-3e5988a4d3a4 · outbound

This paper cites MLS: A Large-Scale Multilingual Dataset for Speech Research.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies MLS: A Large-Scale Multilingual Dataset for Speech Research

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T15:28:35.707427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a05e9efe-9093-491f-97eb-0b48b8abf204 · outbound

This paper cites Flower: A Friendly Federated Learning Research Framework.

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies Flower: A Friendly Federated Learning Research Framework

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T15:28:35.711652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers