Paper Citation Record · LEDGER

The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2011.11588.

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

pith.paper-citation-record.v1
2011.11588 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:47:31.070249Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T05:56:39.904416Z

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 bfb1fe08-fcc6-41ce-9e91-c31be9a47baf · inbound

fastabx: A library for efficient computation of ABX discriminability cites this paper.

fastabx: A library for efficient computation of ABX discriminability The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T00:47:31.070249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3dfe765-ef91-4123-97e4-f790772ba959 · inbound

A Variational Framework for Improving Naturalness in Generative Spoken Language Models cites this paper.

A Variational Framework for Improving Naturalness in Generative Spoken Language Models The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:44.865712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2d0db29-082a-4ab4-8bf5-da843b7777f7 · inbound

Representing Speech Through Autoregressive Prediction of Cochlear Tokens cites this paper.

Representing Speech Through Autoregressive Prediction of Cochlear Tokens The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-05T19:54:58.706814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9eaf1bc-9078-4e9a-8637-9485b5aaa5c9 · inbound

An Empirical Analysis of Discrete Unit Representations in Speech Language Modeling Pre-training cites this paper.

An Empirical Analysis of Discrete Unit Representations in Speech Language Modeling Pre-training The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T10:53:40.660528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ded4574-17ce-4d57-b7d3-62ec30590cf5 · inbound

SpidR-Adapt: A Universal Speech Representation Model for Few-Shot Adaptation cites this paper.

SpidR-Adapt: A Universal Speech Representation Model for Few-Shot Adaptation The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-16T19:58:23.053629Z

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.

Observation 1cf0b13d-8547-4997-a1b9-3e0731721a88 · inbound

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning cites this paper.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling

Reference 141

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.905861Z

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.