Paper Citation Record · LEDGER

SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2104.02133.

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

pith.paper-citation-record.v1
2104.02133 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:58:16.267337Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T14:49:36.377185Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 318d479a-1e71-4f16-bf20-8941f98c3830 · inbound

High-precision medical speech recognition through synthetic data and semantic correction: UNITED-MEDASR cites this paper.

High-precision medical speech recognition through synthetic data and semantic correction: UNITED-MEDASR SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-12T13:48:38.785927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d76a4ec-b7cf-4bbe-82ce-6e655527bbe9 · inbound

Self-Supervised Convolutional Audio Models are Flexible Acoustic Feature Learners: A Domain Specificity and Transfer-Learning Study cites this paper.

Self-Supervised Convolutional Audio Models are Flexible Acoustic Feature Learners: A Domain Specificity and Transfer-Learning Study SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-09T12:27:19.487461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20938b80-b402-493f-9ead-0c73bb27d241 · inbound

LegoSLM: Connecting LLM with Speech Encoder using CTC Posteriors cites this paper.

LegoSLM: Connecting LLM with Speech Encoder using CTC Posteriors SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:16.267337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc3ba030-0bf9-4472-86b6-df1c827b9927 · inbound

Loquacious Set: 25,000 Hours of Transcribed and Diverse English Speech Recognition Data for Research and Commercial Use cites this paper.

Loquacious Set: 25,000 Hours of Transcribed and Diverse English Speech Recognition Data for Research and Commercial Use SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T13:49:20.806789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77bf07e5-9d02-4ed0-a257-5038fcbd6f38 · inbound

OWSM v4: Improving Open Whisper-Style Speech Models via Data Scaling and Cleaning cites this paper.

OWSM v4: Improving Open Whisper-Style Speech Models via Data Scaling and Cleaning SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T12:12:19.793022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 730e33a4-5b91-4288-80a0-6faee9c852fa · inbound

Analyzing and Fine-Tuning Whisper Models for Multilingual Pilot Speech Transcription in the Cockpit cites this paper.

Analyzing and Fine-Tuning Whisper Models for Multilingual Pilot Speech Transcription in the Cockpit SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T22:18:12.145519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58438ae6-60c1-4a4a-816c-8a3a60247d81 · inbound

CAM\~OES: A Comprehensive Automatic Speech Recognition Benchmark for European Portuguese cites this paper.

CAM\~OES: A Comprehensive Automatic Speech Recognition Benchmark for European Portuguese SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T15:39:21.241548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45cc14a7-fb7e-4e29-a232-d72a61ef2a0d · inbound

OLMoASR: Open Models and Data for Training Robust Speech Recognition Models cites this paper.

OLMoASR: Open Models and Data for Training Robust Speech Recognition Models SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-05T14:49:36.379813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.