Paper Citation Record · LEDGER

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition

As of 16 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2412.08548.

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

pith.paper-citation-record.v1
2412.08548 v1

Coverage vector

measured 46 of 46 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-11T17:51:21.424253Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

46 of 46 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f6a7f468-cd77-4a62-8fc8-4db1692c914b · outbound

This paper cites Deep learning,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Deep learning,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.990365Z

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

Observation 0343b3a1-0a43-4464-b881-be62478a7363 · outbound

This paper cites Deep neural networks for acoustic modeling in speech recognition,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Deep neural networks for acoustic modeling in speech recognition,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.977533Z

Source-reported events for the cited work

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Observation 9c235cbb-dd50-46e3-80a6-6a83432a25ec · outbound

This paper cites Toward human parity in conversational speech recognition,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Toward human parity in conversational speech recognition,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.963114Z

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Observation 9a6460a5-b641-4049-8a8c-ea15ed724053 · outbound

This paper cites English conversational telephone speech recognition by humans and machines,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition English conversational telephone speech recognition by humans and machines,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.950652Z

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Observation c401266a-5799-450d-8e3a-dabf70e416b3 · outbound

This paper cites Lessons from building acoustic models with a million hours of speech,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Lessons from building acoustic models with a million hours of speech,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.937765Z

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Observation cf9a674b-9eb6-47cd-9343-b84d20dc746f · outbound

This paper cites Re- alizing petabyte scale acoustic modeling,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Re- alizing petabyte scale acoustic modeling,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.925256Z

Source-reported events for the cited work

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Observation 47997ff3-c4d2-465c-9a23-f1a8312f07bb · outbound

This paper cites New types of deep neural network learning for speech recognition and related applications: An overview,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition New types of deep neural network learning for speech recognition and related applications: An overview,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.912664Z

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Observation f73d5b1f-11ef-4532-a430-e588e16558cd · outbound

This paper cites vq-wav2vec: Self-Supervised Learning of Discrete Speech Representations.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition vq-wav2vec: Self-Supervised Learning of Discrete Speech Representations

Reference 8

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Observation 8fbda2a7-1f52-4416-9ca5-2d0c068aa9dc · outbound

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

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 9

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Source-reported events for the cited work

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Observation 5dc547f1-c00f-4065-9c64-1dd91f61674d · outbound

This paper cites Hubert: Self-supervised speech representation learning by masked prediction of hidden units,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Hubert: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T17:51:21.283045Z

Source-reported events for the cited work

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Observation ea0eeab2-1364-4dab-afb1-a0030d3f66c0 · outbound

This paper cites Self-supervised learning with random-projection quantizer for speech recognition,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Self-supervised learning with random-projection quantizer for speech recognition,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.883405Z

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 2c5784ef-7efc-4a90-aa9c-c729208011cf · outbound

This paper cites To transfer or not to transfer,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition To transfer or not to transfer,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.870289Z

Source-reported events for the cited work

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Observation 4c4578d0-7bc2-4aa2-b4df-bd51857e920c · outbound

This paper cites A survey on transfer learning,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition A survey on transfer learning,

Reference 13

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Source-reported events for the cited work

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Observation cef5f45e-ca6b-462d-8943-b3686ccf5306 · outbound

This paper cites Characterizing and avoiding negative transfer,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Characterizing and avoiding negative transfer,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.849551Z

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Observation c9a16cbf-51a2-46f3-ad47-0fe650b854ec · outbound

This paper cites The loss surfaces of multilayer networks,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition The loss surfaces of multilayer networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.837295Z

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Observation ba1d3a6d-bbed-4d15-a4e4-2b44903041a1 · outbound

This paper cites Investigating bi- level optimization for learning and vision from a unified perspective: A survey and beyond,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Investigating bi- level optimization for learning and vision from a unified perspective: A survey and beyond,

Reference 16

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Observation 890f50ce-65c7-4d8e-88ec-5b0a82d6a155 · outbound

This paper cites Bilevel methods for image reconstruc- tion,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Bilevel methods for image reconstruc- tion,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.818280Z

Source-reported events for the cited work

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Observation 2b674403-1580-46a8-9f71-33ecede2bb0e · outbound

This paper cites Learning with limited samples: Meta-learning and applications to com- munication systems,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Learning with limited samples: Meta-learning and applications to com- munication systems,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.805726Z

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Observation 8af13cfd-c5cc-45d5-88d3-a6a6e0c048a7 · outbound

This paper cites Meta-DAG: Meta causal discovery via bilevel optimization,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Meta-DAG: Meta causal discovery via bilevel optimization,

Reference 19

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Observation ed5442bb-ae75-4301-ac00-6f40eebea4f5 · outbound

This paper cites Bilevel programming for hyperparameter optimization and meta-learning,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Bilevel programming for hyperparameter optimization and meta-learning,

Reference 20

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Observation 6b3cb39a-ca9e-45a6-8c5b-96d13fb37b00 · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Model-agnostic meta-learning for fast adaptation of deep networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.768843Z

Source-reported events for the cited work

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Observation c92c7f43-e7b4-4cf0-a0c3-b99ab4d29d23 · outbound

This paper cites On Penalty-based Bilevel Gradient Descent Method.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition On Penalty-based Bilevel Gradient Descent Method

Reference 22

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Source-reported events for the cited work

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Observation 3ff71bd3-b266-4976-8531-c48ee785fb11 · outbound

This paper cites Joint unsupervised and supervised training for multilingual ASR,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Joint unsupervised and supervised training for multilingual ASR,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.756390Z

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Observation 5eb65b4c-773c-4330-b951-86f256da7db8 · outbound

This paper cites Iterative pseudo-labeling for speech recognition,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Iterative pseudo-labeling for speech recognition,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.743298Z

Source-reported events for the cited work

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Observation e8da4158-f7d9-43a3-aae5-e996c3b3b857 · outbound

This paper cites Joint unsupervised and supervised training for automatic speech recognition via bilevel optimization,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Joint unsupervised and supervised training for automatic speech recognition via bilevel optimization,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.731342Z

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Observation 55165faf-ac5e-4cf7-b0cd-5e896c997f60 · outbound

This paper cites Towards Principled Unsupervised Learning.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Towards Principled Unsupervised Learning

Reference 26

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Observation 50c85391-7f6f-4374-b01e-31bf35d53e52 · outbound

This paper cites An introduction to bilevel optimization: Foundations and applications in signal processing and machine learning,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition An introduction to bilevel optimization: Foundations and applications in signal processing and machine learning,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.718621Z

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Observation 943d0f42-9945-418b-89a9-351c840c5ad2 · outbound

This paper cites First-order penalty methods for bilevel optimization,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition First-order penalty methods for bilevel optimization,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.706743Z

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Observation 0036967a-bafa-4606-9a22-68e48a2c4055 · outbound

This paper cites On penalty methods for nonconvex bilevel optimization and first-order stochastic approxima- tion,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition On penalty methods for nonconvex bilevel optimization and first-order stochastic approxima- tion,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.694398Z

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Observation bf118848-2abe-4a53-9ae3-8efdb0a631ac · outbound

This paper cites Optimization methods for large- scale machine learning,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Optimization methods for large- scale machine learning,

Reference 30

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Observation dae702b4-aa12-4983-8f1d-61301ef606eb · outbound

This paper cites Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages

Reference 31

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Observation f52d87e6-5f82-47f2-9451-42220449a44c · outbound

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

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Librispeech: an asr corpus based on public domain audio books,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.674819Z

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Observation 1c62c306-b6e2-4cbb-acc7-975765ff2061 · outbound

This paper cites Conformer: Convolution- augmented transformer for speech recognition,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Conformer: Convolution- augmented transformer for speech recognition,

Reference 33

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Observation 3eb7a9e6-bfcc-4613-aba8-22c4665e9f2e · outbound

This paper cites SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing

Reference 34

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Observation 933cb2e3-7e9a-4033-8e76-44222224a6d8 · outbound

This paper cites SpecAugment: A simple data augmentation method for automatic speech recognition,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition SpecAugment: A simple data augmentation method for automatic speech recognition,

Reference 35

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Observation a92f3315-df5c-4d40-a60f-cc03d2d7edd3 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Representation Learning with Contrastive Predictive Coding

Reference 36

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This paper cites Connection- ist temporal classification: labelling unsegmented sequence data with recurrent neural networks,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Connection- ist temporal classification: labelling unsegmented sequence data with recurrent neural networks,

Reference 37

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Observation d916afd0-0280-4918-8f67-1d6bfa5a7c88 · outbound

This paper cites Sequence Transduction with Recurrent Neural Networks.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Sequence Transduction with Recurrent Neural Networks

Reference 38

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This paper cites Speech recognition with deep recurrent neural networks,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Speech recognition with deep recurrent neural networks,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.635479Z

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This paper cites Advancing RNN transducer technology for speech recognition,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Advancing RNN transducer technology for speech recognition,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.623842Z

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Observation b307aad7-347a-45ce-ad87-0a300227557b · outbound

This paper cites Improving RNN transducer modeling for end-to-end speech recognition,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Improving RNN transducer modeling for end-to-end speech recognition,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.610973Z

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Observation ae5b782d-3c52-4bf3-956b-79939d0662d8 · outbound

This paper cites Sequence noise injected training for end-to-end speech recognition,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Sequence noise injected training for end-to-end speech recognition,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.597084Z

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Observation e1ed922b-53d6-439a-8a43-690d5f38d971 · outbound

This paper cites Regularization of neural networks using DropConnect,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Regularization of neural networks using DropConnect,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.584286Z

Source-reported events for the cited work

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Observation e0147293-98e5-4030-b4c6-4e79180de1de · outbound

This paper cites Alignment-length synchronous decoding for RNN transducer,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Alignment-length synchronous decoding for RNN transducer,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.569187Z

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Observation 0d9bf4ed-2e9f-48b4-ab5f-d32eb3545a65 · outbound

This paper cites ADAM: a method for stochastic optimiza- tion,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition ADAM: a method for stochastic optimiza- tion,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.555767Z

Source-reported events for the cited work

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Observation 9d4cc652-bc68-4167-9de6-d40e97926c15 · outbound

This paper cites Super-convergence: very fast training of neural networks using large learning rates,.

Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition Super-convergence: very fast training of neural networks using large learning rates,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:51:21.543268Z

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.

Pith citing papers

No inbound Pith citation observations are available.