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Paper Citation Record · LEDGER

Sparse Autoencoder Insights on Voice Embeddings

As of 11 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 2 inbound Pith citation observations for arXiv:2502.00127.

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

pith.paper-citation-record.v1
2502.00127 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T20:10:32.806282Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T00:23:29.977813Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T02:00:39.965426Z

Reference resolution

15 of 15 outbound references displayed

  • verified exact1
  • verified fuzzy4
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b4f9b47-391e-4114-978e-6f75979a60c8 · outbound

This paper cites One pixel attack for fooling deep neural networks,.

Sparse Autoencoder Insights on Voice Embeddings One pixel attack for fooling deep neural networks,

Reference 1

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-09T20:10:33.202248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-09T20:10:32.727453Z digest=sha256:78a3c1e3dd7fc1076eec06869d41ef3964febf5d50244beab3970cad85ff4eb8

Observation 665b226e-caf0-472c-bd81-64b3edb7fdb9 · outbound

This paper cites "Why Should I Trust You?": Explaining the Predictions of Any Classifier.

Sparse Autoencoder Insights on Voice Embeddings "Why Should I Trust You?": Explaining the Predictions of Any Classifier

Reference 2

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unresolved
no resolver link, observed 2026-08-09T20:10:32.733356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T20:10:32.733356Z digest=sha256:7b0ef2eaaf7a8687a43c453454e40f5cb4abf0e779ae82e4ba929d6c02a877b0

Observation 4d8a665e-af38-497a-bdf8-af09304e972f · outbound

This paper cites DLIME: A Deterministic Local Interpretable Model-Agnostic Explanations Approach for Computer-Aided Diagnosis Systems.

Sparse Autoencoder Insights on Voice Embeddings DLIME: A Deterministic Local Interpretable Model-Agnostic Explanations Approach for Computer-Aided Diagnosis Systems

Reference 3

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unresolved
no resolver link, observed 2026-08-09T20:10:32.739873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T20:10:32.739873Z digest=sha256:101e2afcb01bc44657d5cc2659aa1de90c95e4174dfb00014c9615a60a7aa9ea

Observation 73815af4-05a9-46db-90c7-7a20e3a5a11e · outbound

This paper cites Learning Important Features Through Propagating Activation Differences.

Sparse Autoencoder Insights on Voice Embeddings Learning Important Features Through Propagating Activation Differences

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-09T20:10:32.746028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T20:10:32.746028Z digest=sha256:fc94558644e8c380d36e6ab42761da2ae066cd33e5137282d914ab147ea25ddb

Observation 927d94e1-2872-437d-be14-d8f3c53dc986 · outbound

This paper cites Axiomatic Attribution for Deep Networks.

Sparse Autoencoder Insights on Voice Embeddings Axiomatic Attribution for Deep Networks

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-09T20:10:32.752155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T20:10:32.752155Z digest=sha256:98a5d6e212d64e11a39b466594106faf5504fbe2321ea5312223eff8e9aa4a2e

Observation 9e67e06d-e4fd-441d-8879-ed54c7800046 · outbound

This paper cites Leveraging speaker attribute information using multi task learning for speaker verification and diarization.

Sparse Autoencoder Insights on Voice Embeddings Leveraging speaker attribute information using multi task learning for speaker verification and diarization

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-09T20:10:32.757999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T20:10:32.757999Z digest=sha256:5befd7c4210b70181137b7a3f436d02d4fad378095452d87950753cff89ae6c6

Observation 9159050e-be9e-4ff1-ac5d-123ad43fa879 · outbound

This paper cites Explainable Attribute-Based Speaker Verification.

Sparse Autoencoder Insights on Voice Embeddings Explainable Attribute-Based Speaker Verification

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-09T20:10:32.763898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T20:10:32.763898Z digest=sha256:47c473dd8215f147b1c7a2a605485cd2e90f813d95d16f14ee2f3b1d0f6ef01c

Observation 894797c4-4280-41d3-91ef-903123e3bd0b · outbound

This paper cites Towards monosemanticity: Decomposing language models with dictionary learning,.

Sparse Autoencoder Insights on Voice Embeddings Towards monosemanticity: Decomposing language models with dictionary learning,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:10:33.282820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-09T20:10:32.769041Z digest=sha256:485af899c8564e80699cfd13ee12900ad3a148c64162d3e1951e801535a72e39

Observation c0f6393c-848d-41fb-a478-fffe6b3efbbc · outbound

This paper cites Scaling monosemanticity: Extracting interpretable features from claude 3 sonnet,.

Sparse Autoencoder Insights on Voice Embeddings Scaling monosemanticity: Extracting interpretable features from claude 3 sonnet,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:10:33.265790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-09T20:10:32.774112Z digest=sha256:ed4e828336475ba6e96eb2a082d8c98946d0ab9c80ef335ac3e48ca6cb615d35

Observation 06ea5279-a7d8-479e-b8a5-a33b986d2d74 · outbound

This paper cites Scaling and evaluating sparse autoencoders.

Sparse Autoencoder Insights on Voice Embeddings Scaling and evaluating sparse autoencoders

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-09T20:10:32.778903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T20:10:32.778903Z digest=sha256:73a7c39bacfe15df5d2e84e48c558c96847486764eda80803275aa28cd9a6948

Observation 468649fd-31d0-41be-a6ef-1d051061caf0 · outbound

This paper cites Gemma scope: Open sparse autoencoders everywhere all at once on gemma 2,.

Sparse Autoencoder Insights on Voice Embeddings Gemma scope: Open sparse autoencoders everywhere all at once on gemma 2,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:10:33.249319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-09T20:10:32.784094Z digest=sha256:1af740539402c89b00634dff2c9e977889e004ca46af35952200c900fbc964bd

Observation 2b7594a7-59f6-4735-b6aa-48d17cafefbc · outbound

This paper cites TitaNet: Neural Model for speaker representation with 1D Depth-wise separable convolutions and global context.

Sparse Autoencoder Insights on Voice Embeddings TitaNet: Neural Model for speaker representation with 1D Depth-wise separable convolutions and global context

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-09T20:10:32.795144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T20:10:32.795144Z digest=sha256:86a92b7bb2201349961155ab2ba24fa151e13096a2c371d101c4cedc850498b2

Observation 9b8782cd-32b0-42ac-8082-89382000a6c7 · outbound

This paper cites NeMo: a toolkit for Conversational AI and Large Language Models.

Sparse Autoencoder Insights on Voice Embeddings NeMo: a toolkit for Conversational AI and Large Language Models

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:10:33.231714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-09T20:10:32.800288Z digest=sha256:694bd59b41e467fd9c673cc8693e0557e7eaf15f35760347ecc79b3ae679c3e0

Observation 3c6c56c5-58c1-4b90-a799-88fa412ff859 · outbound

This paper cites Robust speech recognition via large-scale weak supervi- sion,.

Sparse Autoencoder Insights on Voice Embeddings Robust speech recognition via large-scale weak supervi- sion,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-09T20:10:32.806282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T20:10:32.806282Z digest=sha256:9eeea700041c285ccf2c61f42e2813bc30470856ad07b9c213902723d73a4305

Observation 295d5822-a12f-4c41-9406-d985907c68e6 · outbound

This paper cites Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2.

Sparse Autoencoder Insights on Voice Embeddings Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-09T20:10:32.789781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T20:10:32.789781Z digest=sha256:544b09484068d24f4cfe3926969f57f4b8771d3ebc037294c60cc7e1782bc9bc

Pith citing papers

Observation c09f40a4-8500-4931-bcc1-a2a08584e441 · inbound

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach cites this paper.

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach Sparse Autoencoder Insights on Voice Embeddings

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-18T02:00:39.967921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-18T01:56:50.978054Z digest=sha256:1131974e02691c9cac1649d2a4aa5e7cf775c8680840644fb87f03f27929b60e

Observation 4eedb172-729c-4e8b-ba19-7b5855550916 · inbound

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach cites this paper.

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach Sparse Autoencoder Insights on Voice Embeddings

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-04T00:23:29.977813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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