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Paper Citation Record · LEDGER

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective

As of 21 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2507.02911.

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

pith.paper-citation-record.v1
2507.02911 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:02:15.045500Z

measured 38 of 38 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 2026-08-06T23:02:14.896688Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T23:02:15.149755Z

Reference resolution

37 of 37 outbound references displayed

  • verified exact1
  • verified fuzzy23
  • unresolved11
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3a6afb51-3522-48b2-9ef2-524ff1942b0f · outbound

This paper cites teacher” model to a smaller “student.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective teacher” model to a smaller “student

Reference 1

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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.

source=pdf_text observed=2026-08-06T23:02:14.891728Z digest=sha256:39950679a04018a4b2e785d721bc6db8c21953201f1a2fd765e6afbe3fd443aa

Observation adebe8ba-b18a-4d03-aa85-766b948601ee · outbound

This paper cites DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective

Reference 2

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local_arxiv, observed 2026-08-06T23:02:15.156368Z

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

source=pdf_text observed=2026-08-06T23:02:14.896688Z digest=sha256:49e13a7853e1d2b86c41a1eed1ac9ff8bfee997f8ad10cd5b51c8d92b0553866

Observation 8db71925-ca7e-4575-b4b8-61316bff930a · outbound

This paper cites an unresolved cited work.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Unresolved cited work

Reference 3

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source=pdf_text observed=2026-08-06T23:02:14.901825Z digest=sha256:25ce2be47cdaca05cf35bd771817f46c82a253fa1a72526d2e493ed762643ae5

Observation f3c16daa-8d5d-435e-807e-eb8075bff7af · outbound

This paper cites an unresolved cited work.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Unresolved cited work

Reference 4

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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.

source=pdf_text observed=2026-08-06T23:02:14.906036Z digest=sha256:0a930282f9d563d872041ea376f7a47bfd08f4024dd77fcd851e853d4150e637

Observation d07dd902-c37d-48d0-9278-b1377e2c51a0 · outbound

This paper cites an unresolved cited work.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Unresolved cited work

Reference 5

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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.

source=pdf_text observed=2026-08-06T23:02:14.910853Z digest=sha256:cfe9095db125f7a27fcee2df9039cf1cbaabc0600223ac1c1bdefdf9f06875a7

Observation 5ea88b41-84a7-495c-9e09-7233a3e3800b · outbound

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

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective wav2vec 2.0: A framework for self-supervised learning of speech repre- sentations,

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:02:14.915251Z digest=sha256:5ae2c040a8c59e91ce11dabe6a28b4907768a7061f409d7ee205c0d0fa7003ee

Observation bf25a9db-d4ad-4017-b32a-95c7144fc6d2 · outbound

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

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Hubert: Self-supervised speech represen- tation learning by masked prediction of hidden units,

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:02:14.919529Z digest=sha256:8dae649943855bca77319007e976b35524c074c0c7ad6f97435026a9aec042e5

Observation 9c45acdc-6447-4222-a9a4-30e448fac80a · outbound

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

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Wavlm: Large-scale self- supervised pre-training for full stack speech processing,

Reference 8

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:02:14.923621Z digest=sha256:8051d5dc22038613d29d99efb18864aadae8db74b05a34e43408ca67d90331b9

Observation dad648f9-9aa1-4934-b17b-0668ee6d121e · outbound

This paper cites XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale

Reference 9

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:02:14.927874Z digest=sha256:c45215e9aad780afc5d0e5b5c71bec3bc4e06c943d325828bc1a6d7485018c96

Observation 38cd7e67-71b7-409c-9f31-de8c7d8cfe8c · outbound

This paper cites Speech-xlnet: Unsupervised acoustic model pretraining for self- attention networks,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Speech-xlnet: Unsupervised acoustic model pretraining for self- attention networks,

Reference 10

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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.

source=pdf_text observed=2026-08-06T23:02:14.932690Z digest=sha256:49c8a520c1cd7a628241ed038803f89b74545342d6a7815bc740adf0682fe897

Observation a025ef31-7fdb-4005-b42f-2af2692303f6 · outbound

This paper cites Investigating self-supervised learning for speech enhancement and separation,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Investigating self-supervised learning for speech enhancement and separation,

Reference 11

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source=pdf_text observed=2026-08-06T23:02:14.938262Z digest=sha256:88fe27f4bcad3bdb1909512671fbadc6e411161a095e2ba42340118f780cb04a

Observation d15c7076-8889-4b63-b7ec-50ffb23f0608 · outbound

This paper cites An explo- ration of self-supervised pretrained representations for end-to-end speech recognition,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective An explo- ration of self-supervised pretrained representations for end-to-end speech recognition,

Reference 12

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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.

source=pdf_text observed=2026-08-06T23:02:14.942450Z digest=sha256:94093e3a91cdc8c7b1d78a83b07649d942b66cacdfcfb8864693b7d2c431add7

Observation 49378fce-3db4-4907-b404-2cbade93abc3 · outbound

This paper cites W2v-bert: Combining contrastive learning and masked language modeling for self-supervised speech pre-training,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective W2v-bert: Combining contrastive learning and masked language modeling for self-supervised speech pre-training,

Reference 13

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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.

source=pdf_text observed=2026-08-06T23:02:14.946669Z digest=sha256:ab5dc6684e273059a17e40e3c6e30903ad32125a9ec2471b1459397cd8e88dd1

Observation 7c2e5a89-e08f-49d3-a8b9-d888ad0ce4d2 · outbound

This paper cites Convolutional neural networks for small-footprint keyword spotting.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Convolutional neural networks for small-footprint keyword spotting

Reference 14

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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.

source=pdf_text observed=2026-08-06T23:02:14.950898Z digest=sha256:8fc298659fbd83454b2df0b0b5a209b11a28822f3cfd2dd625c6aca0cc016365

Observation faaf83ea-c45b-4794-ba55-a531a3903d5e · outbound

This paper cites Monophone-based background modeling for two-stage on-device wake word de- tection,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Monophone-based background modeling for two-stage on-device wake word de- tection,

Reference 15

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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.

source=pdf_text observed=2026-08-06T23:02:14.955053Z digest=sha256:64cc9dc32cafe810873553171f7db631edd9a42baedb98056f6f6f8883efc094

Observation 5029e2bd-efd8-4670-9e0c-79d26d42a387 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Distilling the Knowledge in a Neural Network

Reference 16

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source=pdf_text observed=2026-08-06T23:02:14.959185Z digest=sha256:0e9683e4959c4a202279145e1b4d6c73e5f1f2f820cdf066cbd1d709861b6bcc

Observation e0ce6d4d-8ccb-47a0-ba3a-7530cf893636 · outbound

This paper cites Knowledge distilla- tion: A survey,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Knowledge distilla- tion: A survey,

Reference 17

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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.

source=pdf_text observed=2026-08-06T23:02:14.963512Z digest=sha256:f0c5637046d85d6a763a6242cc396b3d129d0b393511aa809871ab6284c9729f

Observation 85530ea5-dd52-45de-b1f8-f9d11d07d229 · outbound

This paper cites Do deep nets really need to be deep?.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Do deep nets really need to be deep?

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.

source=pdf_text observed=2026-08-06T23:02:14.967538Z digest=sha256:158b025cf310b5e743b763ee186c03500a54c3de78f50b6f338bd9de75f8fa86

Observation b74e7579-cc6b-47ae-8b5d-f6f27d76040e · outbound

This paper cites Learn- ing efficient object detection models with knowledge distillation,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Learn- ing efficient object detection models with knowledge distillation,

Reference 19

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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.

source=pdf_text observed=2026-08-06T23:02:14.971207Z digest=sha256:5e13503580a089ec23b88b28e173fd1167db3e0f254e500e39602f79cfeaeb7f

Observation 83f49035-54e2-47c9-b4c9-93a36e4a0a5d · outbound

This paper cites Knowledge distillation across ensembles of multilingual mod- els for low-resource languages,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Knowledge distillation across ensembles of multilingual mod- els for low-resource languages,

Reference 20

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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.

source=pdf_text observed=2026-08-06T23:02:14.975001Z digest=sha256:6a93534eb1d3342acbeef224f7fc8fcb2af5df452e5e7c96de2c790d29aa35b0

Observation 35f36f3d-81f0-4208-bdb4-c5b827fd40c5 · outbound

This paper cites Distilling knowl- edge from graph convolutional networks,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Distilling knowl- edge from graph convolutional networks,

Reference 21

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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.

source=pdf_text observed=2026-08-06T23:02:14.978976Z digest=sha256:b2d64b23186fb6164d0990bc02e5d45e6b4ac92acad02e3eddb2be9e472811be

Observation 4c33b322-66ed-410b-af0c-fbe8acddfcf5 · outbound

This paper cites Domain adaptation of dnn acoustic models using knowledge distillation,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Domain adaptation of dnn acoustic models using knowledge distillation,

Reference 22

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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.

source=pdf_text observed=2026-08-06T23:02:14.983229Z digest=sha256:6a0ee429688630fe313d1b1f7fb2a78970395ce3b70e497c3e10fc7d60739394

Observation f76cbfe7-9c57-407a-9615-11a4097f5250 · outbound

This paper cites Distil-Whisper: Robust Knowledge Distillation via Large-Scale Pseudo Labelling.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Distil-Whisper: Robust Knowledge Distillation via Large-Scale Pseudo Labelling

Reference 23

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:02:14.987091Z digest=sha256:bc9fa386fa2a975a53883310f546348794bfa61928100ea1484d3091fa10d6eb

Observation c16bc0d9-e53c-4773-9639-dceb94f881c7 · outbound

This paper cites Knowledge distillation with the reused teacher classifier,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Knowledge distillation with the reused teacher classifier,

Reference 24

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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.

source=pdf_text observed=2026-08-06T23:02:14.991101Z digest=sha256:278fb7eeb58dfb92e7d4b8bbfc65cc7895c6695e91cc21133af63ce5ae966e04

Observation 678df10f-7153-460b-9e92-3080dc8b01f3 · outbound

This paper cites Dphubert: Joint distillation and pruning of self-supervised speech models,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Dphubert: Joint distillation and pruning of self-supervised speech models,

Reference 25

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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.

source=pdf_text observed=2026-08-06T23:02:14.994963Z digest=sha256:2c2d3ab0020f6f8dced956bb7343247e1a81345b1e141476f12dc61513f15a22

Observation b68ebff5-62c0-407e-8452-9c51f580626d · outbound

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

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Fithubert: Going thinner and deeper for knowledge distillation of speech self-supervised learning,

Reference 26

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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.

source=pdf_text observed=2026-08-06T23:02:14.998823Z digest=sha256:4ccc3d5561b78c97909370ef9aff5c9f6fbb5774a687506a3fb3ff66ea9ac906

Observation a32c2a67-dfa8-47fb-86cd-7e7432146212 · outbound

This paper cites Su- perb: Speech processing universal performance benchmark,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Su- perb: Speech processing universal performance benchmark,

Reference 27

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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.

source=pdf_text observed=2026-08-06T23:02:15.028402Z digest=sha256:67166629e9123ee1839208e223662036f9894eb805a3029dd735671d92de8cfa

Observation eb311ea3-0036-4b7c-9294-d8798a8246fc · outbound

This paper cites Recycle-and-distill: Universal compression strategy for transformer-based speech ssl models with attention map reusing and masking distillation,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Recycle-and-distill: Universal compression strategy for transformer-based speech ssl models with attention map reusing and masking distillation,

Reference 28

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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.

source=pdf_text observed=2026-08-06T23:02:15.007350Z digest=sha256:5ff168fd1dc22acb9b246236f4e560c970fb14aa2851889d3583079724cdbbc3

Observation 6662c183-0b9c-411f-ba0e-d0975716468c · outbound

This paper cites Distilhubert: Speech representation learning by layer-wise distillation of hidden-unit bert,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Distilhubert: Speech representation learning by layer-wise distillation of hidden-unit bert,

Reference 29

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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.

source=pdf_text observed=2026-08-06T23:02:15.011458Z digest=sha256:e31a280c336c21013c508649d850ea0a3b02f7397f829736d88a199ac8499ac6

Observation b6efb47a-37b4-4762-83ae-846b70c82b78 · outbound

This paper cites Star: Distilling speech temporal relation for lightweight speech self-supervised learning models,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Star: Distilling speech temporal relation for lightweight speech self-supervised learning models,

Reference 30

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raw_fallback, observed 2026-08-06T23:02:15.250530Z

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.

source=pdf_text observed=2026-08-06T23:02:15.015989Z digest=sha256:f373fa2b732fbde9313f3eb22238078462db0087cae24b0fe5287001af4a1512

Observation d019be5a-8daa-4956-a46b-efa26358faa4 · outbound

This paper cites Lighthubert: Lightweight and configurable speech representation learning with once-for-all hidden-unit bert,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Lighthubert: Lightweight and configurable speech representation learning with once-for-all hidden-unit bert,

Reference 31

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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.

source=pdf_text observed=2026-08-06T23:02:15.020117Z digest=sha256:b6d26e3baf0f9965c5feb27f9286d25040b040949257f962e905e1414296370c

Observation e19e009b-2d7f-4fa7-b2d9-55ee9bfd87e1 · outbound

This paper cites k-means++: The advantages of careful seeding,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective k-means++: The advantages of careful seeding,

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:02:15.024246Z digest=sha256:2d5698fba93aabddadfe7e0d09e0fb6206d70e72f27424c8f3a3527567992427

Observation 2d34d833-c5b0-4df4-b593-401c4785403a · outbound

This paper cites Why distillation helps: a statistical perspective.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Why distillation helps: a statistical perspective

Reference 34

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source=pdf_text observed=2026-08-06T23:02:15.032524Z digest=sha256:17e573b9a26995a4e6736ba797ae383d33cd9527056fb868dd9de2042edbeca6

Observation 51874dd6-4f8a-42a5-a457-39f10ea7f287 · outbound

This paper cites Lib- rispeech: an asr corpus based on public domain audio books,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Lib- rispeech: an asr corpus based on public domain audio books,

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:02:15.037372Z digest=sha256:064fda8422af245b21f8bd0957d8b7658122ae1454445743cc6c66c299839697

Observation 8e7d4ec9-c039-4081-9eae-aa8a09edb638 · outbound

This paper cites Exploring prediction targets in masked pre-training for speech foundation models,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Exploring prediction targets in masked pre-training for speech foundation models,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:02:15.186259Z

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.

source=pdf_text observed=2026-08-06T23:02:15.041444Z digest=sha256:30b0d17697050598d3ff9403d74a11ebbb5f431270c02da9c27df6c49c9f313e

Observation 98f32520-c1c1-4447-b015-251fb824154c · outbound

This paper cites Libri-light: A benchmark for asr with limited or no supervision,.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective Libri-light: A benchmark for asr with limited or no supervision,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:02:15.172182Z

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.

source=pdf_text observed=2026-08-06T23:02:15.045500Z digest=sha256:62a4dd7e28e59de60dcde434476886835423c5409f6f8c2cd1045994bf541995

Observation e086fa7e-127a-4f6e-b60c-e2cf4f84b0e6 · outbound

This paper cites 3588–3592.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective 3588–3592

Reference 2022

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:02:15.293580Z

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.

source=pdf_text observed=2026-08-06T23:02:15.003147Z digest=sha256:54d0cb1704a99d8140762b7178ea1adb72edd91fade2b09c78b14cf84ec2a725

Pith citing papers

Observation adebe8ba-b18a-4d03-aa85-766b948601ee · inbound

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective cites this paper.

DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective DiceHuBERT: Distilling HuBERT with a Self-Supervised Learning Objective

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:02:15.156368Z

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.

source=pdf_text observed=2026-08-06T23:02:14.896688Z digest=sha256:49e13a7853e1d2b86c41a1eed1ac9ff8bfee997f8ad10cd5b51c8d92b0553866