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Paper Citation Record · LEDGER

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data

As of 12 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 1 inbound Pith citation observation for arXiv:2506.01439.

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

pith.paper-citation-record.v1
2506.01439 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:52:13.429143Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:52:11.502278Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T11:52:13.916425Z

Reference resolution

39 of 39 outbound references displayed

  • verified exact3
  • verified fuzzy24
  • unresolved10
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a252876d-78d3-4a80-840d-ecb6af7f9330 · outbound

This paper cites Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:52:13.943649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:11.502278Z digest=sha256:288f954c0798ae8aba0ee9b88015478d5fddd899b336c2d16865a26929f741c4

Observation 0f77035d-0147-4b16-baad-e1fd041d2959 · outbound

This paper cites Next, acoustic features are extracted via SSL, w2v-BERT [18].

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Next, acoustic features are extracted via SSL, w2v-BERT [18]

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:16.978017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:11.547934Z digest=sha256:9f5f0358c0178974b85ebf0bc853b8771cd7902da6131a25c732ddb21a106e71

Observation 2f9d5ede-8e03-4a08-92ef-592195b8e6d6 · outbound

This paper cites Training environments The training of the Whale model was conducted on an inter- nal server infrastructure.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Training environments The training of the Whale model was conducted on an inter- nal server infrastructure

Reference 3

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malformed identifier
raw_fallback, observed 2026-08-07T11:52:16.830710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:11.605647Z digest=sha256:c3966670586933fe33743452d6420c98f4543832eb73a825941100fe485260d2

Observation 3433c08c-7cc0-4712-b862-592fbe1d45be · outbound

This paper cites Our experiments compare Whale against state-of-the-art systems such as Whis- per [14], OWSM [15], and OWSM CTC [17].

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Our experiments compare Whale against state-of-the-art systems such as Whis- per [14], OWSM [15], and OWSM CTC [17]

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:16.736939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:11.643182Z digest=sha256:647143023cd7ad294423e64b5ecffe33a1ac9d157e1d22c1b8da3fbfece4fd33

Observation 1417886d-095d-4671-90cd-e6b61244d221 · outbound

This paper cites Through extensive experiments, we demonstrated that Whale achieves highly competitive performance on four benchmarks.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Through extensive experiments, we demonstrated that Whale achieves highly competitive performance on four benchmarks

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-07T11:52:16.636351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:11.720267Z digest=sha256:44600efc84d529ae333bee6114c3b3fc3053e1c9bbf9c42d4b22a3a62a4d8e68

Observation bc8a5bb4-9708-468d-9cd0-81121f30004f · outbound

This paper cites Common V oice: A Massively-Multilingual Speech Corpus,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Common V oice: A Massively-Multilingual Speech Corpus,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:16.513195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:11.799504Z digest=sha256:02328ef861b0d88315c710244eeb3026266dcc5ad945dc264361be68b8fb992d

Observation 9a9c02f2-0d4f-409a-88b5-5148b6a2e0c6 · outbound

This paper cites MUST-C: a multilingual speech translation corpus,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data MUST-C: a multilingual speech translation corpus,

Reference 7

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raw_fallback, observed 2026-08-07T11:52:16.435266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:11.841152Z digest=sha256:45962f9122bc68ba1f188fe50cdbf70d19368e0cc38c9a284b6aceddb342223e

Observation 2f0bcc1e-e966-47a4-af83-e2e4a12150fe · outbound

This paper cites The Multilingual TEDx Corpus for Speech Recognition and Translation,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data The Multilingual TEDx Corpus for Speech Recognition and Translation,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:16.351072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:11.886282Z digest=sha256:ae541dc1fbc7af790397712dbd1e52a66187d4577152305d9e6ec7ffc4cde911

Observation f1adea2b-c5bf-46b2-bfae-55fb7b7d90ea · outbound

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

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data MLS: A Large-Scale Multilingual Dataset for Speech Research,

Reference 9

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raw_fallback, observed 2026-08-07T11:52:16.249441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:11.943874Z digest=sha256:585e03ca2c6884ff248b988595e867efa6f30ba58f7177e6e08c6ad172e1e380

Observation 98fe1142-8d90-4b5c-9864-114a16c15be5 · outbound

This paper cites YODAS: YouTube-oriented dataset for audio and speech,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data YODAS: YouTube-oriented dataset for audio and speech,

Reference 10

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raw_fallback, observed 2026-08-07T11:52:16.131035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:11.987325Z digest=sha256:d1229f3bcad3801cab29b0e08a96784d86a740228e8bfea1c5944949c5a36ab7

Observation 6b362eb3-980c-4b06-9e84-72d49be6ac16 · outbound

This paper cites FLEURS: Few-shot learn- ing evaluation of universal representations of speech,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data FLEURS: Few-shot learn- ing evaluation of universal representations of speech,

Reference 11

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raw_fallback, observed 2026-08-07T11:52:16.043916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:12.044617Z digest=sha256:ce7fa5773cee799a7f8560bb29a18b318eacff44dad2e3e6f6fab21ec517ef4e

Observation 73f4e7b9-83cf-4188-a662-2f5856a3235e · outbound

This paper cites JTubeSpeech: corpus of Japanese speech collected from YouTube for speech recognition and speaker verification.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data JTubeSpeech: corpus of Japanese speech collected from YouTube for speech recognition and speaker verification

Reference 12

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unresolved
no resolver link, observed 2026-08-07T11:52:12.107639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:52:12.107639Z digest=sha256:a3349faa4f38e66cd865c12618a603cc291e9aebd432c1085c62e2c878160c0c

Observation 650a4083-b23e-48c1-b995-12d781bcf2ab · outbound

This paper cites CSTR VCTK Corpus: English Multi-speaker Corpus for CSTR V oice Cloning Toolkit,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data CSTR VCTK Corpus: English Multi-speaker Corpus for CSTR V oice Cloning Toolkit,

Reference 13

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doi_truncated, observed 2026-08-07T11:52:13.540449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:12.188880Z digest=sha256:022c4a03519f7527481b32778f7ddbd6ad002187ee470096d3c7e1bcc4efe7b7

Observation 78e257a2-8c00-4ad1-b187-59b56b892abb · outbound

This paper cites Multilingual speech recognition with a single end-to-end model,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Multilingual speech recognition with a single end-to-end model,

Reference 14

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raw_fallback, observed 2026-08-07T11:52:15.911834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:12.220385Z digest=sha256:070a579450f7d01e091fa70cc8be22988309edc8af36ea433ef17166dbc8a3b4

Observation fa894e38-556e-40b8-99e1-a2f9d11da06f · outbound

This paper cites Bytes are all you need: End-to-end multilingual speech recognition and synthe- sis with bytes,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Bytes are all you need: End-to-end multilingual speech recognition and synthe- sis with bytes,

Reference 15

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raw_fallback, observed 2026-08-07T11:52:15.841719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:12.267009Z digest=sha256:d0ef119f95cc4fa06bf6fa7b45184194593f176624bdcb5dd46d4af75ba66d84

Observation 5bfcfb12-120f-4947-b09e-cd170152f762 · outbound

This paper cites An end-to-end language-tracking speech recognizer for mixed- language speech,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data An end-to-end language-tracking speech recognizer for mixed- language speech,

Reference 16

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raw_fallback, observed 2026-08-07T11:52:15.766281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:12.301077Z digest=sha256:5d1d20763ee14ee2b7a0cbb1fe4e22cf7afcf8704fd4e4609276dc24c7fdc18f

Observation 311203d9-ad28-40e3-9bf6-0d263da0384b · outbound

This paper cites Scaling speech technology to 1,000+ languages,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Scaling speech technology to 1,000+ languages,

Reference 17

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raw_fallback, observed 2026-08-07T11:52:15.610423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:12.341225Z digest=sha256:d8ccd7eaf1ff71260ab00b4f1c2dac076c7f3d571672ab454286afca3c8ca18e

Observation 2563d107-58fd-442a-a3a4-0dafbc238378 · outbound

This paper cites Less is More: Accu- rate Speech Recognition & Translation without Web-Scale Data,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Less is More: Accu- rate Speech Recognition & Translation without Web-Scale Data,

Reference 18

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raw_fallback, observed 2026-08-07T11:52:15.517326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:12.393041Z digest=sha256:605f6e4704be61e74dd3222d4cacc24b64c444391fbc48c0ab8d806b2e902aea

Observation 3265a550-d7cc-4745-8430-3c2bfaacfb83 · outbound

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

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Robust speech recognition via large-scale weak supervision,

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:52:12.424757Z digest=sha256:aac2705e19800a73e72971a8988478d60742e15f77c275458d991f6016ed6b7a

Observation 605a18c1-61fa-42f9-94ba-d87ffb96b2bc · outbound

This paper cites OWSM v3.1: Better and Faster Open Whisper-Style Speech Models based on E-Branchformer.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data OWSM v3.1: Better and Faster Open Whisper-Style Speech Models based on E-Branchformer

Reference 20

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no resolver link, observed 2026-08-07T11:52:12.485510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:52:12.485510Z digest=sha256:d472e10b3ec86de1fc3f2ccd10334c607da51a91e5f9842c38b0c08fdb6688d5

Observation fc862e2b-0f58-424c-aa00-ae35ff0b686e · outbound

This paper cites Reproducing whisper-style train- ing using an open-source toolkit and publicly available data,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Reproducing whisper-style train- ing using an open-source toolkit and publicly available data,

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-07T11:52:15.403774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:12.552905Z digest=sha256:76c3516950e8047532f447ca89153d70b5dc236cc4a95a026336e8be30a0ff86

Observation 50267203-235d-4053-ad36-6890cc280f96 · outbound

This paper cites OWSM-CTC: An Open Encoder-Only Speech Foundation Model for Speech Recognition, Translation, and Language Identification.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data OWSM-CTC: An Open Encoder-Only Speech Foundation Model for Speech Recognition, Translation, and Language Identification

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T11:52:12.584687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:52:12.584687Z digest=sha256:fba41118b54f0d5eecde76883eabcec3db36b7659d1a07999275727dc9e7de1b

Observation f10c69b4-4f34-4a7e-b299-239bd01d81d7 · outbound

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

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data W2v-BERT: Combin- ing contrastive learning and masked language modeling for self- supervised speech pre-training,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:15.277095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:12.616796Z digest=sha256:c7e21b0d1b24e58b12bec3274a5dd9db4cf35bfb1310d836232f5efbb76e61f7

Observation 392efdd9-04e1-45a4-a835-f1609dda7824 · outbound

This paper cites E-Branchformer: Branchformer with enhanced merging for speech recognition,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data E-Branchformer: Branchformer with enhanced merging for speech recognition,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:15.070525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:12.663181Z digest=sha256:b4a2c988813d26e190a52ac8697fa11924ce70e2ae556b5cec85978e71abb385

Observation 76402194-0a96-4528-ae06-4065c2867c11 · outbound

This paper cites Joint CTC-attention based end-to-end speech recognition using multi-task learning,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Joint CTC-attention based end-to-end speech recognition using multi-task learning,

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:52:12.696914Z digest=sha256:5deaaa744c02071b8ac0212844fa6d81f155e6309d6c7205eb708f5f8356fa85

Observation fe796955-e6fc-4b6c-9fa6-174890ae8a31 · outbound

This paper cites Joint CTC/attention decoding for end-to-end speech recognition,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Joint CTC/attention decoding for end-to-end speech recognition,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:14.920584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:12.731205Z digest=sha256:87be36e7b5c6aeb61329e68a962fb11dad78158288a8cf619ba7906dc4586f4c

Observation f7885cbb-39de-4366-a5d4-ac178db87a6d · outbound

This paper cites Curricu- lum learning,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Curricu- lum learning,

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:52:12.768004Z digest=sha256:d210a7da3b10704eb8f23788836eb1a7436755456fd814bb47b38eeb3d8c7459

Observation bfe986cd-b310-4754-9f27-fa52c31e4d7e · outbound

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

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Lib- rispeech: an asr corpus based on public domain audio books,

Reference 28

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no resolver link, observed 2026-08-07T11:52:12.818208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:52:12.818208Z digest=sha256:42ccf44321ae5c3458e590a1860494199f2a2adb71b234b0f66d629aea665fd2

Observation e35690d9-1d5c-4bae-9702-28be96da4503 · outbound

This paper cites Corpus of Spontaneous Japanese: Its design and evaluation,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Corpus of Spontaneous Japanese: Its design and evaluation,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:14.805916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:12.868330Z digest=sha256:eff5d23bbfad0cc5f1c6fca711851d234cce0f43fdd6628968648d05b8276ecc

Observation 3697c5d3-97ab-4c57-95d5-efef034997a1 · outbound

This paper cites Better Intermediates Im- prove CTC Inference,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Better Intermediates Im- prove CTC Inference,

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-07T11:52:14.691919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:12.914300Z digest=sha256:2e689cd664ed1d1c12562989677d20fbbdca48b7f70efa972d9aea018bac4433

Observation 20437515-acb6-4b91-b9d7-5f37dc3b25b5 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 31

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no resolver link, observed 2026-08-07T11:52:12.946413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:52:12.946413Z digest=sha256:f6b95194149e8110e42a77b5403b4dbec051b0cdda3000b96df36beb62e0ad4e

Observation 99580925-0466-4f65-8f2b-596a39776f07 · outbound

This paper cites mHuBERT-147: A Compact Multilingual HuBERT Model.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data mHuBERT-147: A Compact Multilingual HuBERT Model

Reference 32

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no resolver link, observed 2026-08-07T11:52:13.029649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:52:13.029649Z digest=sha256:1f6ab0dafc88ce6ea77290319ac0da374ded5af2b00bf6bb54615395cebafd7a

Observation 1b7f548d-d52f-445d-a734-7b8eab3ee7e0 · outbound

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

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data WavLM: Large-scale self- supervised pre-training for full stack speech processing,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:14.569887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:13.100295Z digest=sha256:8499995b3c9d9da94bdc03de0f08095f531c279e27d681c1a5f45cad1020ef80

Observation ea4af69f-db0d-4996-b02e-a97bae4e6ee7 · outbound

This paper cites Rapid Language Adaptation for Multilingual E2E Speech Recognition Using Encoder Prompting.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Rapid Language Adaptation for Multilingual E2E Speech Recognition Using Encoder Prompting

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:52:13.768823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:13.181595Z digest=sha256:8b2a5b98d4ed2d278bb5cba6c109d3f90ebe278da49b1973b1707329d81f9d2e

Observation 90e0db55-7011-4431-a972-edaf52a54976 · outbound

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

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data ESPnet: End-to-End Speech Processing Toolkit,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:14.425893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:13.244378Z digest=sha256:d5f1798acbedfed25e6613633634335a0efad8b0e59cdc3ebb225b0fefe1d463

Observation 04f43e6e-ec3e-42fd-b475-676edde6c505 · outbound

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

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data VoxPopuli: A large-scale multilingual speech corpus for representation learning, semi- supervised learning and interpretation,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:14.303262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:13.283183Z digest=sha256:40f92ac510309ed11b129c71beb2a666f324bcf578c69f335564dc8893dae7d8

Observation ab385ad2-7bb1-4b5f-8866-364ceb3501c4 · outbound

This paper cites WenetSpeech: A 10000+ hours multi-domain mandarin corpus for speech recognition,.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data WenetSpeech: A 10000+ hours multi-domain mandarin corpus for speech recognition,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:14.075308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:13.348188Z digest=sha256:2e2299ad1d84ae5c089924abe7b2f0a2396436f124b26a0a95b08ece73278bd7

Observation 7b443f9f-0199-4440-9394-983dbf2e8ece · outbound

This paper cites The People's Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data The People's Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T11:52:13.381090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:52:13.381090Z digest=sha256:6681a2b02aa524220651b25dbad730dc436ac8b0b0db52d0f0fa5d1101e28173

Observation 91d8f7c5-bb41-4732-a8d5-9f66d7a0a411 · outbound

This paper cites The Norwegian Parliamentary Speech Corpus.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data The Norwegian Parliamentary Speech Corpus

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:52:13.658600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:13.429143Z digest=sha256:91b0ffd526ac57254a02cf0805e3a538467a3adb737e33172cc6049698d917d4

Pith citing papers

Observation a252876d-78d3-4a80-840d-ecb6af7f9330 · inbound

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data cites this paper.

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:52:13.943649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T11:52:11.502278Z digest=sha256:288f954c0798ae8aba0ee9b88015478d5fddd899b336c2d16865a26929f741c4