Paper Citation Record · LEDGER

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting

As of 8 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 3 inbound Pith citation observations for arXiv:2506.11096.

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

pith.paper-citation-record.v1
2506.11096 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:19:25.703024Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:19:22.892740Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T09:11:27.109005Z

Reference resolution

21 of 21 outbound references displayed

verified exact0
verified fuzzy15
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 69884584-f5e9-4aef-9aa3-cf62c69a44db · outbound

This paper cites an unresolved cited work.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:19:29.189506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1a21a1f0-b391-4f7b-8eb0-68a8aa8b7a17 · outbound

This paper cites Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:22.892740Z

Source-reported events for the cited work

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Observation 52ed3488-3741-4166-aa29-86eb54316ead · outbound

This paper cites Keyword spotting refers to the task of detecting specific words or phrases within an audio corpus with- out requiring full transcription.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Keyword spotting refers to the task of detecting specific words or phrases within an audio corpus with- out requiring full transcription

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:28.929471Z

Source-reported events for the cited work

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Observation 894416b7-7ae5-406e-9c32-0e9f82995e7a · outbound

This paper cites These dimensions exhibit exceptionally large magnitudes and high variance, dominating cosine similarity computations and skewing the overall distribution of representations.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting These dimensions exhibit exceptionally large magnitudes and high variance, dominating cosine similarity computations and skewing the overall distribution of representations

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:29.044232Z

Source-reported events for the cited work

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Observation f94eb722-22b2-4baa-b2c0-bf6229f10c25 · outbound

This paper cites This suggests that these representations capture high-level phonetic structures that generalize well across speakers, making them ro- bust for computational documentary linguistics.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting This suggests that these representations capture high-level phonetic structures that generalize well across speakers, making them ro- bust for computational documentary linguistics

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:28.809987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6561afae-952e-4379-89e7-eb95a7e119cc · outbound

This paper cites an unresolved cited work.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:19:28.722002Z

Source-reported events for the cited work

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Observation cc8fa39b-52f3-42fd-a0d8-15532d3d4215 · outbound

This paper cites wav2vec 2.0: a framework for self-supervised learning of speech representa- tions,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting wav2vec 2.0: a framework for self-supervised learning of speech representa- tions,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:23.373661Z

Source-reported events for the cited work

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Observation c1b42a0a-0dbd-45b2-84fb-329b37aaacdb · outbound

This paper cites Hubert: Self-supervised speech representation learning by masked prediction of hidden units,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Hubert: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:23.594444Z

Source-reported events for the cited work

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Observation b2d17e8d-f1e4-41e0-a891-0626db980773 · outbound

This paper cites Representation degeneration problem in training natural language generation models,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Representation degeneration problem in training natural language generation models,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:28.540081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1efde071-8ac0-47e0-b892-efdb0b3dcdf8 · outbound

This paper cites All bark and no bite: Rogue dimensions in transformer language models obscure representational quality,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting All bark and no bite: Rogue dimensions in transformer language models obscure representational quality,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:28.438029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation aab7b9d3-045d-4af2-84b0-30d04e537a48 · outbound

This paper cites How does fine-tuning affect the geometry of embedding space: A case study on isotropy,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting How does fine-tuning affect the geometry of embedding space: A case study on isotropy,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:28.257978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d54008ec-be38-4ec4-bf1a-fe0933eab539 · outbound

This paper cites Is anisotropy truly harmful? a case study on text clustering,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Is anisotropy truly harmful? a case study on text clustering,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:28.089993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5ade663a-b4df-47e9-a34e-d024d548ec8a · outbound

This paper cites Anisotropy is inherent to self-attention in transformers,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Anisotropy is inherent to self-attention in transformers,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:27.880103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 315b24f7-9ea2-4fdf-a162-8d39f438e6d4 · outbound

This paper cites How contextual are contextualized word representations? Comparing the geometry of BERT, ELMo, and GPT-2 embeddings,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting How contextual are contextualized word representations? Comparing the geometry of BERT, ELMo, and GPT-2 embeddings,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:27.690363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6762c3f4-76bf-4884-88d7-16a90872b99f · outbound

This paper cites Dissecting contextual word embeddings: Architecture and representation,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Dissecting contextual word embeddings: Architecture and representation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:27.453238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1cf1f181-069a-46d3-8933-2a5bb33e3387 · outbound

This paper cites Unsupervised cross-lingual representation learning for speech recognition,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Unsupervised cross-lingual representation learning for speech recognition,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:27.186502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eda76fdb-323b-41a1-9e17-13ac8a784476 · outbound

This paper cites Automatic speech recognition and query by example for creole languages documentation,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Automatic speech recognition and query by example for creole languages documentation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:26.924084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d880e569-7fa6-441e-8d2b-40d814c270a6 · outbound

This paper cites M ¨uller, Fundamentals of Music Processing: Audio, Analysis, Algorithms, Applications, 1st ed.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting M ¨uller, Fundamentals of Music Processing: Audio, Analysis, Algorithms, Applications, 1st ed

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:26.671520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 89b022a5-e761-4042-b39b-1129f73f19f4 · outbound

This paper cites Common voice: A massively-multilingual speech corpus,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Common voice: A massively-multilingual speech corpus,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:25.399110Z

Source-reported events for the cited work

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Observation 3f034a3b-483c-4444-87c9-70a8eec41e2e · outbound

This paper cites Montreal forced aligner: Trainable text-speech align- ment using kaldi,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Montreal forced aligner: Trainable text-speech align- ment using kaldi,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:26.409939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bcfbf275-439b-41dc-b40b-d41274e2ab5e · outbound

This paper cites Guillotine regularization: Why removing layers is needed to improve generalization in self-supervised learning,.

Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting Guillotine regularization: Why removing layers is needed to improve generalization in self-supervised learning,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:26.120765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation 1a21a1f0-b391-4f7b-8eb0-68a8aa8b7a17 · inbound