Paper Citation Record · LEDGER

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech

As of 23 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:2501.07726.

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

pith.paper-citation-record.v1
2501.07726 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:39:45.359064Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:57:26.736848Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:57:26.818962Z

Reference resolution

36 of 36 outbound references displayed

verified exact1
verified fuzzy29
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c5e19437-cccf-42d4-b9f4-3b7a205c99d1 · outbound

This paper cites Ciwgan and fiwgan: Encoding information in acoustic data to model lexical learning with generative adversarial networks.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Ciwgan and fiwgan: Encoding information in acoustic data to model lexical learning with generative adversarial networks

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.865020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5d8bb708-392b-4f56-a29d-688588d7a35c · outbound

This paper cites Generative adversarial networks.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Generative adversarial networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T20:39:44.984006Z

Source-reported events for the cited work

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Observation 6da1cc61-613f-4194-b565-72093be04f8f · outbound

This paper cites Modeling unsupervised phonetic and phonological learning in generative adversarial phonology.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Modeling unsupervised phonetic and phonological learning in generative adversarial phonology

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.788113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 12633571-9f31-4f0e-b08d-3bd906c634b7 · outbound

This paper cites Exploring How Generative Adversarial Networks Learn Phonological Representations.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Exploring How Generative Adversarial Networks Learn Phonological Representations

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T20:39:45.002850Z

Source-reported events for the cited work

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Observation eb7cac6d-58d0-4d27-b8ec-7f02aa64532f · outbound

This paper cites Linguistic generalization and compositionality in modern artificial neural networks.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Linguistic generalization and compositionality in modern artificial neural networks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.753535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9f754725-7d0f-490c-a009-307d020004aa · outbound

This paper cites Analyzing hidden representations in end-to-end automatic speech recognition systems.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Analyzing hidden representations in end-to-end automatic speech recognition systems

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.712896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6811f861-0956-4831-8ac3-136186c5457b · outbound

This paper cites The influence of categories on perception: explaining the perceptual magnet effect as optimal statistical inference.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech The influence of categories on perception: explaining the perceptual magnet effect as optimal statistical inference

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.687023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 00e74d62-0345-4311-88fe-5eebbae01759 · outbound

This paper cites V owel normalization as perceptual constancy.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech V owel normalization as perceptual constancy

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.660222Z

Source-reported events for the cited work

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Observation a93d229a-5e53-4b36-bc1c-0f9abb5f8ac4 · outbound

This paper cites Systematicity, but not compositionality: Examining the emergence of linguistic structure in children and adults using iterated learning.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Systematicity, but not compositionality: Examining the emergence of linguistic structure in children and adults using iterated learning

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.628409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 158d98f1-056f-4733-ae0e-27f34fc0e538 · outbound

This paper cites Statistical learning of tone sequences by human infants and adults.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Statistical learning of tone sequences by human infants and adults

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.582213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e72ef22e-3c98-4196-a99b-68bf2c76d880 · outbound

This paper cites Categorization of speech by infants: Support for speech-sound prototypes.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Categorization of speech by infants: Support for speech-sound prototypes

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.542200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 82b3a774-8dde-4e6c-ad94-1568a644471e · outbound

This paper cites Acquiring language from speech by learning to remember and predict.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Acquiring language from speech by learning to remember and predict

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.507414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e40de2c9-e8b4-4d7c-b560-7939a161af5b · outbound

This paper cites Cnn-generated images are surprisingly easy to spot.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Cnn-generated images are surprisingly easy to spot

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.454126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 403e7122-7db0-4429-b58b-2553d6958e57 · outbound

This paper cites Unsupervised Cross-Domain Image Generation.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Unsupervised Cross-Domain Image Generation

Reference 14

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Source-reported events for the cited work

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Observation eb485e0e-3f9d-4576-b67e-bc5832ca7474 · outbound

This paper cites Unsupervised modeling of vowel harmony using wavegan.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Unsupervised modeling of vowel harmony using wavegan

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.420046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 301e6b31-05b3-42e1-af41-61a723c242b4 · outbound

This paper cites Identity-based patterns in deep convolutional networks: Generative adversarial phonology and reduplication.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Identity-based patterns in deep convolutional networks: Generative adversarial phonology and reduplication

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.373433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 49486aa1-9dec-48e8-a162-24a3984df563 · outbound

This paper cites Articulation GAN: Unsupervised modeling of articulatory learning.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Articulation GAN: Unsupervised modeling of articulatory learning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.346589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 69d15ea1-34a0-4f6e-9703-d443363d9327 · outbound

This paper cites Measuring the perceptual availability of phonological features during language acquisition using unsupervised binary stochastic autoencoders.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Measuring the perceptual availability of phonological features during language acquisition using unsupervised binary stochastic autoencoders

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.322806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 58c588fe-0841-4123-abdc-469785cf219e · outbound

This paper cites How Familiar Does That Sound? Cross-Lingual Representational Similarity Analysis of Acoustic Word Embeddings.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech How Familiar Does That Sound? Cross-Lingual Representational Similarity Analysis of Acoustic Word Embeddings

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T20:39:45.134239Z

Source-reported events for the cited work

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Observation ffe71371-0fee-40e1-9748-8ade4215fc15 · outbound

This paper cites Disentanglement in a gan for unconditional speech synthesis.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Disentanglement in a gan for unconditional speech synthesis

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.284859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0be6cbfd-1e20-4930-8926-ee3b750234c3 · outbound

This paper cites Interpreting intermediate convolutional layers in unsupervised acoustic word classification.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Interpreting intermediate convolutional layers in unsupervised acoustic word classification

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.226982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e5766f95-bd5d-4e2f-8c4b-d1a638db56e3 · outbound

This paper cites Interpreting intermediate convolutional layers of generative cnns trained on waveforms.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Interpreting intermediate convolutional layers of generative cnns trained on waveforms

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.182661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c15c63de-2059-4db2-a045-6cdccc04982a · outbound

This paper cites Local and non-local dependency learning and emergence of rule-like representations in speech data by deep convolutional generative adversarial networks.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Local and non-local dependency learning and emergence of rule-like representations in speech data by deep convolutional generative adversarial networks

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.143963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 63f637f6-ce08-4de6-91af-26f5ff77ca26 · outbound

This paper cites Modeling speech recognition and synthesis simultaneously: Encoding and decoding lexical and sublexical semantic information into speech with no direct access to speech data.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Modeling speech recognition and synthesis simultaneously: Encoding and decoding lexical and sublexical semantic information into speech with no direct access to speech data

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.098017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e413d756-2625-4745-8110-76a09edb6222 · outbound

This paper cites Adversarial Audio Synthesis.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Adversarial Audio Synthesis

Reference 25

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Source-reported events for the cited work

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Observation 5d111ec2-9776-4343-a870-ee11a83d7b36 · outbound

This paper cites InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.058438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation acbc4d89-ec1e-4dd4-9f4b-c70ab388b5f8 · outbound

This paper cites Timit acoustic-phonetic continuous speech corpus.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Timit acoustic-phonetic continuous speech corpus

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:46.016432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a0fd20b8-95a9-413b-8cdb-63f88880183f · outbound

This paper cites Weiss, Samy Bengio, and Aäron van den Oord.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Weiss, Samy Bengio, and Aäron van den Oord

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:45.986635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e0441da4-c919-4a4d-b64c-9ea2607b33f3 · outbound

This paper cites Visualizing and understanding convolutional networks, 2013.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Visualizing and understanding convolutional networks, 2013

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T20:39:45.270122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2100c28-356b-4fa7-ac12-8ee4ab2cde46 · outbound

This paper cites Approaching an unknown communication system by latent space exploration and causal inference.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Approaching an unknown communication system by latent space exploration and causal inference

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:45.909443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0db2c885-76a6-49fc-90fb-504a21ee4e41 · outbound

This paper cites Speech perception without speaker normalization: An exemplar model.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Speech perception without speaker normalization: An exemplar model

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:45.863583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bed87472-9a70-45e5-81b7-4280fdff4566 · outbound

This paper cites Exemplar dynamics: Word frequency, lenition, and contrast.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Exemplar dynamics: Word frequency, lenition, and contrast

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:45.820472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cdac44a9-b0e1-4bbe-ad1d-3e7cc2a1fea0 · outbound

This paper cites Advancement of phonetics in the 21st century: Exemplar models of speech production.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Advancement of phonetics in the 21st century: Exemplar models of speech production

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:45.755841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 03fdceb2-430f-4def-abc2-e529471285e0 · outbound

This paper cites The representation of speech variability and variation in deep neural networks.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech The representation of speech variability and variation in deep neural networks

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:45.724174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fc35d412-43bd-4c77-b67a-5dee1cda5eee · outbound

This paper cites Walking the Tightrope: An Investigation of the Convolutional Autoencoder Bottleneck.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Walking the Tightrope: An Investigation of the Convolutional Autoencoder Bottleneck

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:39:45.490393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 331d903c-cc72-4f14-8876-5c75f3b75bee · outbound

This paper cites Christina Zhao.

Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Christina Zhao

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:39:45.685004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

Observation 538aa9d0-f15b-4545-97bc-8b56d6b23d06 · inbound

A Technique for Isolating Lexically-Independent Phonetic Dependencies in Generative CNNs cites this paper.

A Technique for Isolating Lexically-Independent Phonetic Dependencies in Generative CNNs Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:57:26.825304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.