Paper Citation Record · LEDGER

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling

As of 9 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 1 inbound Pith citation observation for arXiv:2602.15537.

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

pith.paper-citation-record.v1
2602.15537 v2

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T22:51:44.257192Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T22:51:39.700059Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

verified exact0
verified fuzzy0
unresolved39
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5a2724dc-84b1-4933-b7fe-c1c7311ad345 · outbound

This paper cites an unresolved cited work.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:39.638708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b5cc2af-be8c-460a-b457-bc1102c3223c · outbound

This paper cites ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:39.700059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92db26e8-beb5-42a4-9182-7b9685a6fda5 · outbound

This paper cites an unresolved cited work.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:39.771347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec4fd5b6-ea07-43fc-ba21-10a347b6c0d8 · outbound

This paper cites manufacturer,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling manufacturer,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:39.844483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e05fd215-dba4-4471-88b0-8974fa6a0e51 · outbound

This paper cites an unresolved cited work.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:39.941788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a30aede-289b-4651-a82b-34ac4138aaf9 · outbound

This paper cites By leveraging feature norms from a frozen SSL model (WavLM Large), ZeroSyl eliminates the complex multi-stage methods required by prior state-of-the-art syllabic tokenizers.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling By leveraging feature norms from a frozen SSL model (WavLM Large), ZeroSyl eliminates the complex multi-stage methods required by prior state-of-the-art syllabic tokenizers

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:40.096092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b11c5d75-e945-452c-a0e7-673b2a08cbfb · outbound

This paper cites an unresolved cited work.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:40.232329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 569f43d8-3730-4256-8f51-f15529dc1e9a · outbound

This paper cites Self-Supervised Speech Representation Learning: A Review,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Self-Supervised Speech Representation Learning: A Review,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:40.378773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 908e30d1-0baf-4d96-ae02-b90bea9e758b · outbound

This paper cites Self-Supervised Lan- guage Learning From Raw Audio: Lessons From the Zero Re- source Speech Challenge,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Self-Supervised Lan- guage Learning From Raw Audio: Lessons From the Zero Re- source Speech Challenge,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:40.439700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddc974b0-e493-466c-80e5-82770f1dcff9 · outbound

This paper cites On Generative Spoken Language Modeling from Raw Audio,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling On Generative Spoken Language Modeling from Raw Audio,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:40.575509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32cccbc6-6e68-4d98-a2c4-657dc92d64eb · outbound

This paper cites AudioLM: A Language Modeling Approach to Audio Generation,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling AudioLM: A Language Modeling Approach to Audio Generation,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:40.729931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d607a998-43ce-4bd6-b252-28fd86e25d33 · outbound

This paper cites w2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Training,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling w2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Training,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:40.824151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45d80510-7194-4ff1-ba8f-eacc82b5147e · outbound

This paper cites Scaling Properties of Speech Language Models,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Scaling Properties of Speech Language Models,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:41.017062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71cc6aa4-dd04-4e29-b051-ca84f09a0588 · outbound

This paper cites SpidR: Learning Fast and Stable Linguistic Units for Spoken Language Models Without Supervision,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling SpidR: Learning Fast and Stable Linguistic Units for Spoken Language Models Without Supervision,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:41.124518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 634142eb-3115-4a54-baff-2656e5238e47 · outbound

This paper cites Generative Spoken Language Model Based on Continuous Word-Sized Audio Tokens,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Generative Spoken Language Model Based on Continuous Word-Sized Audio Tokens,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:41.236292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3087aa99-0c39-492e-a3c1-32453587d80c · outbound

This paper cites Spoken Language Modeling with Duration-Penalized Self-Supervised Units,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Spoken Language Modeling with Duration-Penalized Self-Supervised Units,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:41.325306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74d9ad02-41cb-49ec-a1f3-e0048a743bc9 · outbound

This paper cites Sylber: Syllabic Embedding Repre- sentation of Speech from Raw Audio,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Sylber: Syllabic Embedding Repre- sentation of Speech from Raw Audio,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:41.513349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfa2ee3e-09a2-42c7-8e80-23e1283fb2cd · outbound

This paper cites SyllableLM: Learning Coarse Semantic Units for Speech Language Models,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling SyllableLM: Learning Coarse Semantic Units for Speech Language Models,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:41.620796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36bf79a9-56e0-4c2e-a5e8-5c98b6828845 · outbound

This paper cites WavLM: Large-Scale Self- Supervised Pre-Training for Full Stack Speech Processing,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling WavLM: Large-Scale Self- Supervised Pre-Training for Full Stack Speech Processing,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:41.743514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80dcf8b2-1ed9-4bd5-9ff9-e2271e83f1b9 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling OPT: Open Pre-trained Transformer Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:41.884430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5244a5d-c6a9-4d7d-bf7f-20bab8e9abe9 · outbound

This paper cites On The Landscape of Spoken Language Models: A Comprehensive Sur- vey,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling On The Landscape of Spoken Language Models: A Comprehensive Sur- vey,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:41.994416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6389fb6-729c-4ed1-898d-2643d3c68e04 · outbound

This paper cites The Zero Resource Speech Challenge 2021: Spoken language modelling,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling The Zero Resource Speech Challenge 2021: Spoken language modelling,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:42.141907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80109e63-1e86-4912-b113-114f201ff291 · outbound

This paper cites Textually Pretrained Speech Language Models,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Textually Pretrained Speech Language Models,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:42.260479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbd0c015-949c-492d-8beb-dfef5a38e36c · outbound

This paper cites SD-HuBERT: Sentence-Level Self-Distillation In- duces Syllabic Organization in HuBERT,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling SD-HuBERT: Sentence-Level Self-Distillation In- duces Syllabic Organization in HuBERT,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:42.457422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20a65383-33bf-49b6-8e53-45620eee2b40 · outbound

This paper cites HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:42.548204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5335851a-71ee-4d93-a9f2-de01830d88dd · outbound

This paper cites What Do Self- Supervised Speech Models Know About Words?.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling What Do Self- Supervised Speech Models Know About Words?

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:42.654043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0c58d39-254d-4147-a4f8-6c619a44f3d5 · outbound

This paper cites A Computational Model for Unsuper- vised Word Discovery,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling A Computational Model for Unsuper- vised Word Discovery,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:42.771487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41072480-7c04-4fc0-8890-61b690f5aa2b · outbound

This paper cites Unsupervised Word Discovery: Boundary Detection with Clustering vs. Dynamic Pro- gramming,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Unsupervised Word Discovery: Boundary Detection with Clustering vs. Dynamic Pro- gramming,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:42.912427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ec74310-3cdb-4aec-b1cb-b84f63f40ed8 · outbound

This paper cites Should Top-Down Clustering Affect Boundaries in Unsupervised Word Discovery?.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Should Top-Down Clustering Affect Boundaries in Unsupervised Word Discovery?

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:43.039657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a46740af-3a65-4d40-a6a9-919448b5c92f · outbound

This paper cites Comparative layer-wise analysis of self-supervised speech models,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Comparative layer-wise analysis of self-supervised speech models,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:43.152010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58bab7bd-af8c-40c8-84e2-08472bda94e7 · outbound

This paper cites LibriSpeech: An ASR corpus based on public domain audio books,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling LibriSpeech: An ASR corpus based on public domain audio books,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:43.310477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcbe4188-94dd-482b-90cd-8be818211d98 · outbound

This paper cites The Faiss library,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling The Faiss library,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:43.507048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 644889f1-3634-4fff-8eb7-eddb31f40b7b · outbound

This paper cites Libri-Light: A Benchmark for ASR with Limited or No Supervi- sion,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Libri-Light: A Benchmark for ASR with Limited or No Supervi- sion,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:43.697544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bc85b8e-b30e-43db-ab9e-836171c13406 · outbound

This paper cites Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:43.800836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3023e730-9ab6-4b94-a863-8880220d9770 · outbound

This paper cites Python module for syllabifying English ARPABET transcriptions,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling Python module for syllabifying English ARPABET transcriptions,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:43.899621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3e5fd01-f8f5-4690-bde1-31c4a5fcdb8a · outbound

This paper cites An improved speech segmentation quality measure: the R-value,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling An improved speech segmentation quality measure: the R-value,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:44.025746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a8a7031-b2e1-449b-b163-449ae689dd00 · outbound

This paper cites On the robust automatic segmentation of spontaneous speech,.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling On the robust automatic segmentation of spontaneous speech,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:44.118442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0905b55d-e95d-4f7f-be9b-717b67a9e59b · outbound

This paper cites data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:44.257192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bd3368c-f93f-452e-bbe2-67be22b86ee2 · outbound

This paper cites The Faiss library.

ZeroSyl: Simple Zero-Resource Syllable Tokenization for Spoken Language Modeling The Faiss library

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:43.594317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 9b5cc2af-be8c-460a-b457-bc1102c3223c · inbound