Paper Citation Record · LEDGER

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints

As of 21 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2508.19990.

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

pith.paper-citation-record.v1
2508.19990 v2

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:53:27.990523Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:53:26.923284Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T16:53:28.432777Z

Reference resolution

32 of 32 outbound references displayed

verified exact1
verified fuzzy22
unresolved8
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aa2e8c3a-2c9f-40d2-8bc4-7af211768fc8 · outbound

This paper cites In speech related applications, self-supervised pre-training has been actively investigated and broadly used [1–4].

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints In speech related applications, self-supervised pre-training has been actively investigated and broadly used [1–4]

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:30.486186Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 13537c91-af0c-4c4b-9a31-624b4b1ca999 · outbound

This paper cites Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-15T16:53:28.472624Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 60a1e15a-e158-4757-b7f0-c33d0c08197b · outbound

This paper cites an unresolved cited work.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Unresolved cited work

Reference 3

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Observation da312a5a-189b-4277-a7c0-ed896029e1e5 · outbound

This paper cites We then expand eachϕi k with its gradient descent update in Eq.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints We then expand eachϕi k with its gradient descent update in Eq

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:30.245982Z

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Observation 2cf95f3a-2851-4c98-9524-4788cad73c6b · outbound

This paper cites 3.1 and 3.2, the pseudo-code imple- mentation of PTLOC is given in Algorithm 1.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints 3.1 and 3.2, the pseudo-code imple- mentation of PTLOC is given in Algorithm 1

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:30.213492Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 07ef60d9-c897-4965-9f06-46901429b0f7 · outbound

This paper cites One is a self-supervised English acoustic model pre-training using speech data from multiple domains based on BEST-RQ [4].

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints One is a self-supervised English acoustic model pre-training using speech data from multiple domains based on BEST-RQ [4]

Reference 6

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T16:53:30.176456Z

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Observation 98f8c1a9-6101-469b-8dc3-b78b5f4ae36e · outbound

This paper cites Local constraints are imposed to ensure that the models optimize each data source to its local optimum after K- step gradient descent initialized from the model.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Local constraints are imposed to ensure that the models optimize each data source to its local optimum after K- step gradient descent initialized from the model

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:30.108634Z

Source-reported events for the cited work

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Observation 3d42f6fe-bbc3-447c-92a1-b6a758faf5cf · outbound

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

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints vq-wav2vec: Self-Supervised Learning of Discrete Speech Representations

Reference 8

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Observation 530ca13e-ac86-44d8-9b88-e7432ca9e6f8 · outbound

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

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T16:53:27.183695Z

Source-reported events for the cited work

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Observation a7d8d868-f04c-4104-aca3-9ecc50b6e819 · outbound

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

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Hubert: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:29.980541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 027d4a0d-781a-42b2-9afa-c30e0a6dda6a · outbound

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

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Self-supervised learning with random-projection quantizer for speech recog- nition,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:29.849709Z

Source-reported events for the cited work

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Observation f45f4d54-0d63-48a3-a76c-4a25277643b3 · outbound

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

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Investigating bi-level optimization for learning and vision from a unified perspective: A survey and beyond,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:29.743156Z

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Observation 1706a617-b4ab-45d8-a017-f98ddad2a765 · outbound

This paper cites Bilevel methods for image reconstruction,.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Bilevel methods for image reconstruction,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:29.706204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f6f75c60-0a8f-4cfb-9f6a-c0305bd3db0f · outbound

This paper cites Learning with lim- ited samples: Meta-learning and applications to communication systems,.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Learning with lim- ited samples: Meta-learning and applications to communication systems,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:29.680781Z

Source-reported events for the cited work

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Observation cfaf9b07-8fb5-4cc6-bdb4-2cf250863b9e · outbound

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

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Meta-DAG: Meta causal discovery via bilevel optimization,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:29.594335Z

Source-reported events for the cited work

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Observation bcff5843-b458-4973-a4e2-e2b252ac8062 · outbound

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

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Bilevel programming for hy- perparameter optimization and meta-learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:29.536100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3856152d-7c47-439d-bec4-a07a37241f98 · outbound

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

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Model- agnostic meta-learning for fast adaptation of deep networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:29.477892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 54be0bbd-ab29-4bb7-946d-8be5097003fa · outbound

This paper cites Truncated back-propagation for bilevel optimization,.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Truncated back-propagation for bilevel optimization,

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2f580466-e8dd-4c73-a0ab-afa1a37daa7e · outbound

This paper cites A generic first- order algorithmic framework for bi-level programming beyond lower-level singleton,.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints A generic first- order algorithmic framework for bi-level programming beyond lower-level singleton,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:29.227902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 76987803-76f1-4149-bd78-441c46a033a3 · outbound

This paper cites Memory-efficient gradient unrolling for large-scale bi-level optimization,.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Memory-efficient gradient unrolling for large-scale bi-level optimization,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:29.115378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a466031d-c062-4a4d-8ba9-c9db1c012278 · outbound

This paper cites Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond

Reference 21

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Observation 762fced8-b16d-4473-b927-00b69c7745da · outbound

This paper cites Sign-MAML: efficient model- agnostic meta-learning by SignSGD,.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Sign-MAML: efficient model- agnostic meta-learning by SignSGD,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:29.054960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 76f1edcd-e9a3-46b0-9f94-0758bb1cb6df · outbound

This paper cites Sharp- MAML: sharpness-aware model-agnostic meta learning,.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Sharp- MAML: sharpness-aware model-agnostic meta learning,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:29.000518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 040b708c-2ded-423e-bddd-4fcad9079395 · outbound

This paper cites Meta learning for end- to-end low-resource speech recognition,.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Meta learning for end- to-end low-resource speech recognition,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:28.957663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 41bf8ecb-d532-46dc-8e2f-08fd41855ce1 · outbound

This paper cites Mul- tilingual meta-transfer learning for low-resource speech recog- nition,.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Mul- tilingual meta-transfer learning for low-resource speech recog- nition,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:28.904742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 93e30e31-67b0-42e7-8bfa-0408df4bf597 · outbound

This paper cites Meta-learning for Indian languages: performance analysis and improvements with linguistic similarity measures,.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Meta-learning for Indian languages: performance analysis and improvements with linguistic similarity measures,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:28.778136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 729c4c7b-30de-4b3a-8e37-72610850a038 · outbound

This paper cites Model-agnostic meta-learning for fast text-dependent speaker embedding adaptation,.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Model-agnostic meta-learning for fast text-dependent speaker embedding adaptation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:28.634990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 792a916d-bf99-424e-b852-bbcdfa8fa2f1 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Representation Learning with Contrastive Predictive Coding

Reference 28

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Source-reported events for the cited work

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Observation 1d159405-ca92-42a3-b82d-8d9dcaaf4ebf · outbound

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

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Conformer: Convolution-augmented transformer for speech recognition,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T16:53:27.963670Z

Source-reported events for the cited work

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Observation 8d83a3db-ab78-4172-ac2a-d8aa1eb63352 · outbound

This paper cites Con- nectionist temporal classification: labelling unsegmented se- quence data with recurrent neural networks,.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints Con- nectionist temporal classification: labelling unsegmented se- quence data with recurrent neural networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:53:28.542525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ca738ea8-bf9e-4003-82e4-b8cf4373ac25 · outbound

This paper cites CoVoST 2 and Massively Multilingual Speech-to-Text Translation.

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints CoVoST 2 and Massively Multilingual Speech-to-Text Translation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T16:53:27.978382Z

Source-reported events for the cited work

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Observation f6bf4d09-d85d-45d8-8c31-590fa8396aaf · outbound

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

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T16:53:27.990523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 13537c91-af0c-4c4b-9a31-624b4b1ca999 · inbound