Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2011.11588.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:15:44.865712Z
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 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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.