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Paper Citation Record · LEDGER

Sparse Autoencoder Insights on Voice Embeddings

As of 10 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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:10:32.727453Z digest=sha256:597ffaa7b2c526aa80933f8142b55f92039ba49f1e8f77814216a7266a48de39

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=sha256:66993599aaeae53c71b6aaa42c535d26d57ca2a6422a1799db472630bf9d1e00

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=sha256:041ac057a1986c557de35edc17c16c1efc06750e2ad7015ca2c292a9ee5e6fc0

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=sha256:00aca2e7ecba5a41272f61bd811af17e2838834832e050d034c2d7a435aaa5a2

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:b74a249267a25852a52ef835c5a7ad28cba657a87749f2cc8ff382c16dfbe1c9

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:b1e91bb7d8cfa833ab3d8b15b175cd4eea43fae48d7b8e41e0060cafd0ad2eb2

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:e921686335c3b19be6e6b13fa7ee0554f050dd9e41bcce4548f3021652dd8e6e

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:10:32.769041Z digest=sha256:1b18b1016194fe23f817a24ada91e9e87dc88025607c865005c16a14c8106ad8

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:10:32.774112Z digest=sha256:7b05aa2e23f1b3ef53eb61777bc3d5f9cef5cbd08efd916b5809307e405220fc

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=sha256:47674378e66687f1699909e96e7127e2edc775eaf676a919ecbfc419f01113ba

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:10:32.784094Z digest=sha256:2739e9c74f9072fdd39738c76236b0dca5fdaa0a5f1918cdad20e8a68e035f66

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=sha256:41a30eda653407800032513ac558ca5ac631c28a0e0a62703966b1fa65647f45

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:10:32.800288Z digest=sha256:87345c24eee08a63ed705fcd1202fc7348773bb384d0625c97bd8c68bbd5b226

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=sha256:6db6ccf0180452e75871d47cb7185b91bfefc9509f65029541f1e54723ab1fa2

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=sha256:7dc744f0165d18183f943b5b075e6036c52daccbd57a8f55458ad99d0179614f

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-18T01:56:50.978054Z digest=sha256:457ad97c94df9038a266f128ddceee6401affe66e37664ab10b735073b9e8af5

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.

source=arxiv_source observed=2026-08-04T00:23:29.977813Z digest=sha256:abe30bfba9bc460dd66d4771b79ce7b9149849a4442c4e583658bd8581b99e60