Paper Citation Record · LEDGER

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models

As of 18 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 1 inbound Pith citation observation for arXiv:2504.14915.

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

pith.paper-citation-record.v1
2504.14915 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:42:07.085502Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T19:11:30.638672Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-09T06:00:36.639385Z

Reference resolution

26 of 26 outbound references displayed

verified exact0
verified fuzzy15
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a5a8eb55-ff0d-4063-b2a5-b54e1759d17e · outbound

This paper cites Self-supervised speech representation learning: A review,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Self-supervised speech representation learning: A review,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.339733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d4f59699-dcd6-4f5c-b511-45be4aaca0ab · outbound

This paper cites Superb: Speech processing universal performance benchmark,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Superb: Speech processing universal performance benchmark,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.328329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bf767cda-9e10-494e-a422-4853b5efe0f6 · outbound

This paper cites wav2vec: Unsupervised pre-training for speech recognition,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models wav2vec: Unsupervised pre-training for speech recognition,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.315835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c595eeb8-83ec-4711-b402-b17da2a131d3 · outbound

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

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Investigating self-supervised learning for speech enhance- ment and separation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.305660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c04d4fc0-c0e4-4c95-8bb6-625982bed397 · outbound

This paper cites Speak, read and prompt: High-fidelity text-to-speech with minimal supervision,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Speak, read and prompt: High-fidelity text-to-speech with minimal supervision,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.296236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a0440ced-9165-4b4f-b51d-b539e67a8a47 · outbound

This paper cites Soundstream: An end-to-end neural audio codec,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Soundstream: An end-to-end neural audio codec,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.286882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a65a2eb1-72ec-4394-a8e9-851666874b82 · outbound

This paper cites Attention is all you need,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Attention is all you need,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T11:42:07.014087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37915717-0c6b-48bb-ba2b-fb3cefae99b1 · outbound

This paper cites A survey of quantization methods for efficient neural network inference,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models A survey of quantization methods for efficient neural network inference,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.270157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2a9c125e-9ca4-4548-a300-7ba9ff50634e · outbound

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

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Distilhubert: Speech representation learning by layer-wise distillation of hidden-unit bert,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.258297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 143acf95-4ac8-42b3-ba5d-da81fad61cf5 · outbound

This paper cites LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERT,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERT,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.247450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4b39369f-af44-4459-b3bc-736d11cc5a3c · outbound

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

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Structured pruning of self-supervised pre-trained models for speech recognition and understanding,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.236201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 367b09fa-e3d2-450a-8fa5-173f30fa0ce8 · outbound

This paper cites BERT: Pre-training of deep bidirectional transformers for language understanding,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models BERT: Pre-training of deep bidirectional transformers for language understanding,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T11:42:07.037472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9fc4e7c-9d38-487f-95f3-ac1c32a1f95c · outbound

This paper cites Post training 4-bit quantization of convolutional networks for rapid-deployment,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Post training 4-bit quantization of convolutional networks for rapid-deployment,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.220113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 98736cc4-3aea-45a5-a25e-27d6ca0f3a33 · outbound

This paper cites Zeroq: A novel zero shot quantization framework,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Zeroq: A novel zero shot quantization framework,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.208109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8d044992-bb6d-4df3-8fb8-6636fa6d0f19 · outbound

This paper cites A White Paper on Neural Network Quantization.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models A White Paper on Neural Network Quantization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T11:42:07.047575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e0edb2f-a286-43c7-aeab-568741dace22 · outbound

This paper cites The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T11:42:07.051525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26ddb28f-58cb-49b1-95a2-bee32adddd56 · outbound

This paper cites SmoothQuant: Accurate and efficient post-training quantization for large language models,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models SmoothQuant: Accurate and efficient post-training quantization for large language models,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.198044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d5b1794b-50b5-4236-9bf3-6c8dbcddf977 · outbound

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

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Wavlm: Large-scale self-supervised pre-training for full stack speech processing,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T11:42:07.058867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9160d7c-4f90-4fd1-a032-f5d7390fd62a · outbound

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

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T11:42:07.061984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a6d02ca-e010-4808-9dc2-eaf19f887c4b · outbound

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

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Hubert: Self- supervised speech representation learning by masked prediction of hidden units,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T11:42:07.065278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef5ab67d-5e72-4411-83d0-734ef4bafde1 · outbound

This paper cites Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T11:42:07.068365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4010acd7-a3e4-4547-8d80-274e7c18f35b · outbound

This paper cites Quantizing deep convolutional networks for efficient inference: A whitepaper.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Quantizing deep convolutional networks for efficient inference: A whitepaper

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T11:42:07.071963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd48c13d-3f0d-4bc4-a046-6c810df77cb1 · outbound

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

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Libri-light: A benchmark for asr with limited or no supervision,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.171029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2ffd5827-8467-4250-8a33-e61739eb3fa1 · outbound

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

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Librispeech: an asr corpus based on public domain audio books,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T11:42:07.078922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2aabeec9-133b-4779-aed9-a1759bf3141a · outbound

This paper cites 8-bit inference with tensorrt,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models 8-bit inference with tensorrt,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:42:07.153539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0c5adc04-9e41-4bc1-ba3b-8c79a923a695 · outbound

This paper cites Up or down? adaptive rounding for post- training quantization,.

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models Up or down? adaptive rounding for post- training quantization,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T11:42:07.085502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 6c025041-dbd4-4503-ae07-5aff78fe95f6 · inbound

Mixed-Precision Information Bottlenecks for On-Device Trait-State Disentanglement in Bipolar Agitation Detection cites this paper.

Mixed-Precision Information Bottlenecks for On-Device Trait-State Disentanglement in Bipolar Agitation Detection StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:00:36.640956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.