Paper Citation Record · LEDGER

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models

As of 8 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:2505.21237.

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

pith.paper-citation-record.v1
2505.21237 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

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measured 56 of 56 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:43:07.380177Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T13:43:11.971534Z

Reference resolution

55 of 55 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a01e73e8-971b-4289-ba77-49917627baa8 · outbound

This paper cites Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models

Reference 1

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Observation e8216090-5335-4d83-8319-5e46171442fb · outbound

This paper cites an unresolved cited work.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Unresolved cited work

Reference 2

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Observation 04ca0274-f973-4fbb-a149-601eb63d885e · outbound

This paper cites layers” and “blocks.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models layers” and “blocks

Reference 3

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Observation bc15c7df-9463-4229-8440-51046a599862 · outbound

This paper cites Experimental Setup Models and Data.For supervised learning, we take Conformer AED system configured with the ESPnet [45] recipe2.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Experimental Setup Models and Data.For supervised learning, we take Conformer AED system configured with the ESPnet [45] recipe2

Reference 4

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Observation 4fa7592e-8a24-4a51-80aa-8cf15a16c188 · outbound

This paper cites an unresolved cited work.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Unresolved cited work

Reference 5

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Observation 6715130b-38a3-41be-9bf1-f435b6e1cae8 · outbound

This paper cites 14200220, 14200021, 14200324, Innovation Technology Fund grant No.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models 14200220, 14200021, 14200324, Innovation Technology Fund grant No

Reference 6

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Observation d897bbf7-c59a-4fc6-8e58-48a795dff800 · outbound

This paper cites 2-bit conformer quantization for automatic speech recognition,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models 2-bit conformer quantization for automatic speech recognition,

Reference 7

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Observation 19ee9b6d-04ab-4134-bf12-eb8638c5e798 · outbound

This paper cites 2 and 3), and the 8-layer system that trained at the unfolded depth of 12 that can not be folded back (i.e., Sys.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models 2 and 3), and the 8-layer system that trained at the unfolded depth of 12 that can not be folded back (i.e., Sys

Reference 8

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Observation c1b064d0-5332-4ef2-96ee-b3c3304d02c9 · outbound

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

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models wav2vec 2.0: A framework for self- supervised learning of speech representations,

Reference 9

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Observation dacc2fed-c0d5-44d4-a08c-c941a5027e9b · outbound

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

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models HuBERT: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 10

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Observation 9d77b614-38e7-470b-8a2a-0af15030a474 · outbound

This paper cites Data2vec: A general framework for self-supervised learning in speech, vision and language,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Data2vec: A general framework for self-supervised learning in speech, vision and language,

Reference 11

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Observation e2bb097f-33a2-464a-8de2-ba22feb3b4fe · outbound

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

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models WavLM: Large-scale self-supervised pre-training for full stack speech processing,

Reference 12

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Observation 9dbdde20-340c-47ae-826e-4fbbf3ee65ff · outbound

This paper cites 4-bit conformer with native quan- tization aware training for speech recognition,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models 4-bit conformer with native quan- tization aware training for speech recognition,

Reference 13

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Observation c0d14317-719a-43ac-85a9-6432039bfaea · outbound

This paper cites Integer-only zero-shot quantization for efficient speech recognition,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Integer-only zero-shot quantization for efficient speech recognition,

Reference 14

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Observation ef536f06-bcd0-4c70-adf9-26ed315da8b1 · outbound

This paper cites Effective and efficient mixed precision quan- tization of speech foundation models,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Effective and efficient mixed precision quan- tization of speech foundation models,

Reference 15

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Observation 6d5209bc-e6ae-430f-9414-4baef42eccec · outbound

This paper cites Multi-stage progressive com- pression of conformer transducer for on-device speech recogni- tion,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Multi-stage progressive com- pression of conformer transducer for on-device speech recogni- tion,

Reference 16

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Observation 0f7550c7-1ad4-4e2f-b85c-44054cafcafb · outbound

This paper cites DistilHuBERT: Speech represen- tation learning by layer-wise distillation of hidden-unit bert,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models DistilHuBERT: Speech represen- tation learning by layer-wise distillation of hidden-unit bert,

Reference 17

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Observation af473499-aff0-4bf7-b9db-09305326defa · outbound

This paper cites FitHuBERT: Going thinner and deeper for knowledge distillation of speech self-supervised learning,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models FitHuBERT: Going thinner and deeper for knowledge distillation of speech self-supervised learning,

Reference 18

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Observation c11cc13c-c2b7-4506-a5c2-1c4bab1fc1c8 · outbound

This paper cites Deep versus wide: An analysis of student architectures for task-agnostic knowledge distillation of self-supervised speech models,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Deep versus wide: An analysis of student architectures for task-agnostic knowledge distillation of self-supervised speech models,

Reference 19

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Observation 1700499c-873e-4142-85f3-a4d25961bcbb · outbound

This paper cites DistillW2V2: A Small and Streaming Wav2vec 2.0 Based ASR Model.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models DistillW2V2: A Small and Streaming Wav2vec 2.0 Based ASR Model

Reference 20

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Observation 45225458-cd02-4995-a8a1-f81ed1e40c72 · outbound

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Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Distilling HuBERT with LSTMs via decoupled knowledge distillation,

Reference 21

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Observation 6bcd0f5c-197d-43de-82e1-e02a86acd0ee · outbound

This paper cites Conformer-based on-device streaming speech recognition with KD compression and two-pass architec- ture,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Conformer-based on-device streaming speech recognition with KD compression and two-pass architec- ture,

Reference 22

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Observation 0f532c98-5325-407a-9be6-0c6cb3f3b3f6 · outbound

This paper cites Dynamic sparsity neural networks for au- tomatic speech recognition,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Dynamic sparsity neural networks for au- tomatic speech recognition,

Reference 23

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Observation 655fb50f-5a43-4f44-bdf8-657e410785f2 · outbound

This paper cites PARP: Prune, adjust and re-prune for self-supervised speech recognition,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models PARP: Prune, adjust and re-prune for self-supervised speech recognition,

Reference 24

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This paper cites Layer pruning on demand with intermediate ctc,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Layer pruning on demand with intermediate ctc,

Reference 25

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Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models DPHuBERT: Joint distillation and prun- ing of self-supervised speech models,

Reference 26

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This paper cites Accurate and structured pruning for efficient automatic speech recognition,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Accurate and structured pruning for efficient automatic speech recognition,

Reference 27

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Observation fefd0017-24ea-4caa-9826-b891d1be1345 · outbound

This paper cites PADA: Pruning assisted domain adaptation for self-supervised speech representations,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models PADA: Pruning assisted domain adaptation for self-supervised speech representations,

Reference 28

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Observation 875650d8-cb07-4942-bafa-8dc7b4e8ea48 · outbound

This paper cites Structured pruning of self-supervised pre-trained models for speech recognition and understanding,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Structured pruning of self-supervised pre-trained models for speech recognition and understanding,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:17.545328Z

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Observation 7d9d327d-2ca1-4463-a4db-665476dc0bd1 · outbound

This paper cites Task-agnostic structured pruning of speech representation models,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Task-agnostic structured pruning of speech representation models,

Reference 30

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This paper cites SparseW A V: Fast and accurate one-shot un- structured pruning for large speech foundation models,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models SparseW A V: Fast and accurate one-shot un- structured pruning for large speech foundation models,

Reference 31

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This paper cites Semi-orthogonal low-rank matrix fac- torization for deep neural networks,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Semi-orthogonal low-rank matrix fac- torization for deep neural networks,

Reference 32

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This paper cites Neural architecture search for LF-MMI trained time delay neural networks,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Neural architecture search for LF-MMI trained time delay neural networks,

Reference 33

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This paper cites Efficient conformer-based speech recognition with linear attention,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Efficient conformer-based speech recognition with linear attention,

Reference 34

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This paper cites Lossless 4-bit quantization of architecture compressed conformer asr systems on the 300-hr switchboard cor- pus,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Lossless 4-bit quantization of architecture compressed conformer asr systems on the 300-hr switchboard cor- pus,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:16.383257Z

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This paper cites ALBERT: A lite bert for self-supervised learning of language representations,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models ALBERT: A lite bert for self-supervised learning of language representations,

Reference 36

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Observation 212d1c2b-b4b2-430c-a7d7-2deeeffdf259 · outbound

This paper cites Extremely low footprint end-to-end asr system for smart device,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Extremely low footprint end-to-end asr system for smart device,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:16.023507Z

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Observation 9b3f8fd7-4e57-4fe6-9507-ca76f74dc3de · outbound

This paper cites Weight-sharing supernet for searching specialized acoustic event classification networks across device constraints,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Weight-sharing supernet for searching specialized acoustic event classification networks across device constraints,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:15.822574Z

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Observation baf31a38-c01c-4a99-a3c7-dbd7dfc6602d · outbound

This paper cites Sharing low rank conformer weights for tiny always-on ambient speech recognition models,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Sharing low rank conformer weights for tiny always-on ambient speech recognition models,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:15.593433Z

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Observation 7b5fc68d-63df-4c61-8371-05dbbfc6e238 · outbound

This paper cites ResidualTransformer: Residual low-rank learning with weight-sharing for transformer layers,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models ResidualTransformer: Residual low-rank learning with weight-sharing for transformer layers,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:15.400104Z

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Observation 952352c2-cc15-40f7-ae5d-09782935b63f · outbound

This paper cites Once for all: Train one network and spe- cialize it for efficient deployment,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Once for all: Train one network and spe- cialize it for efficient deployment,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:15.150055Z

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Observation 892d5b50-6082-499b-a623-cc2a0ee53a2f · outbound

This paper cites Universally slimmable networks and im- proved training techniques,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Universally slimmable networks and im- proved training techniques,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:14.968833Z

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Observation bf643f84-bf20-46cb-894b-b1d88708889b · outbound

This paper cites Self-distillation: Towards efficient and compact neural networks,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Self-distillation: Towards efficient and compact neural networks,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:14.781678Z

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Observation 248ef7cf-cf00-4c26-b8df-68d2e4778aed · outbound

This paper cites Collaborative training of acoustic en- coders for speech recognition,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Collaborative training of acoustic en- coders for speech recognition,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:14.626532Z

Source-reported events for the cited work

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Observation d2ebdf17-9c94-43ee-9996-8a67960f0a2a · outbound

This paper cites LightHuBERT: Lightweight and con- figurable speech representation learning with once-for-all hidden- unit bert,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models LightHuBERT: Lightweight and con- figurable speech representation learning with once-for-all hidden- unit bert,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:14.447473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 32cb1af8-aab7-48b7-b9e6-86df7896fba3 · outbound

This paper cites One-pass multiple conformer and foundation speech systems compression and quantization using an all-in-one neural model,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models One-pass multiple conformer and foundation speech systems compression and quantization using an all-in-one neural model,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:14.257772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 74e735e2-aa56-4fc9-869e-2a4625078488 · outbound

This paper cites Small-footprint slimmable networks for keyword spotting,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Small-footprint slimmable networks for keyword spotting,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:14.000088Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7e2a922d-55dc-44b6-8fab-daa672eba023 · outbound

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

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Conformer: Convolution-augmented transformer for speech recognition,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:13.683737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 157f47f6-e3bd-42f3-8115-acf55a4e457c · outbound

This paper cites Hybrid CTC/attention architecture for end-to-end speech recognition,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Hybrid CTC/attention architecture for end-to-end speech recognition,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:13.323439Z

Source-reported events for the cited work

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Observation fc00da22-5a94-4337-b17d-9ad461cfba72 · outbound

This paper cites Improving transformer-based speech recognition systems with compressed structure and speech at- tributes augmentation.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Improving transformer-based speech recognition systems with compressed structure and speech at- tributes augmentation

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:13.034065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ea74fb35-6bd4-4177-ba4b-c64c5093a18e · outbound

This paper cites Non-autoregressive asr with self-conditioned folded encoders,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Non-autoregressive asr with self-conditioned folded encoders,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:12.720401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ca7c6e29-cd31-43fa-a06d-6804a150a26c · outbound

This paper cites ESPnet: End-to-End Speech Processing Toolkit.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models ESPnet: End-to-End Speech Processing Toolkit

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T13:43:11.622366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20cbcf8d-b378-45a9-a1c1-9809e1611514 · outbound

This paper cites SWITCHBOARD: Tele- phone speech corpus for research and development,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models SWITCHBOARD: Tele- phone speech corpus for research and development,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:12.444631Z

Source-reported events for the cited work

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Observation 32db411a-7660-45ac-bd1d-59cd30072332 · outbound

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

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models LibriSpeech: an asr corpus based on public domain audio books,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:12.251585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5697be6e-e07b-438a-be74-12a188469a03 · outbound

This paper cites Some statistical issues in the comparison of speech recognition algorithms,.

Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models Some statistical issues in the comparison of speech recognition algorithms,

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T13:43:11.818073Z

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Pith citing papers

Observation a01e73e8-971b-4289-ba77-49917627baa8 · inbound