Paper Citation Record · LEDGER

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations

As of 10 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2603.05576.

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

pith.paper-citation-record.v1
2603.05576 v3

Coverage vector

measured 49 of 49 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-07-15T14:35:11.756852Z

measured 49 of 49 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

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Outbound references

Observation f17c9905-9f61-46fb-8a21-400a0fbf5e1b · outbound

This paper cites X-Vectors: Robust DNN Embeddings for Speaker Recognition,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations X-Vectors: Robust DNN Embeddings for Speaker Recognition,

Reference 1

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Observation 5fba192e-a6ee-4174-8cf4-f870c7831376 · outbound

This paper cites Ecapa-tdnn: Em- phasized channel attention, propagation and aggregation in tdnn based speaker verification,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Ecapa-tdnn: Em- phasized channel attention, propagation and aggregation in tdnn based speaker verification,

Reference 2

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Observation 623c63e5-3f36-458c-8090-078b96ad277e · outbound

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

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Hubert: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 3

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Observation eeed3424-4b86-4f3d-b7e4-115b03a7708f · outbound

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

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations WavLM: Large-Scale Self-Supervised Pre- Training for Full Stack Speech Processing,

Reference 4

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Observation 5775d35d-7f31-4f4c-a8fa-921b60452382 · outbound

This paper cites Unsupervised TTS Acoustic Modeling for TTS With Conditional Disentangled Sequential V AE,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Unsupervised TTS Acoustic Modeling for TTS With Conditional Disentangled Sequential V AE,

Reference 5

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Observation fc511d1e-61e0-4f16-beea-83b3d6511e9c · outbound

This paper cites Disentangling Speech Representations Learning With Latent Diffusion for Speaker Verification,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Disentangling Speech Representations Learning With Latent Diffusion for Speaker Verification,

Reference 6

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Observation 67389dc9-a967-4fb7-8c5b-95c5a7ad02d4 · outbound

This paper cites Rose,Forensic Speaker Identification.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Rose,Forensic Speaker Identification

Reference 7

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Observation 64bc1add-2d8c-4de4-a5b9-94784a6ba974 · outbound

This paper cites Disentangled Representation Learning,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Disentangled Representation Learning,

Reference 8

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Observation 1f5d34b3-ccd6-4002-983a-908f5238236b · outbound

This paper cites Auto-encoding variational bayes,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Auto-encoding variational bayes,

Reference 9

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Observation b48c6a76-55fb-4884-8fed-c865134be390 · outbound

This paper cites Challenging common assumptions in the unsupervised learning of disentangled representations,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Challenging common assumptions in the unsupervised learning of disentangled representations,

Reference 10

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Observation 5ac53122-99ad-4465-b7b9-4cdc15b0ab00 · outbound

This paper cites Neural discrete representation learning,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Neural discrete representation learning,

Reference 11

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Observation 1c975ed3-75b7-4101-ab78-f85ea1529322 · outbound

This paper cites Unsupervised learning of disentan- gled and interpretable representations from sequential data,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Unsupervised learning of disentan- gled and interpretable representations from sequential data,

Reference 12

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Observation f23d198c-c996-4b85-8e58-7359e1c4d907 · outbound

This paper cites Disentangled Sequential Autoencoder,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Disentangled Sequential Autoencoder,

Reference 13

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Observation adc47abf-2842-42d6-9ee7-6b11a4e9365e · outbound

This paper cites Hamiltonian Systems and Transformation in Hilbert Space,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Hamiltonian Systems and Transformation in Hilbert Space,

Reference 14

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Observation 7c3d4179-8a6d-4a2b-b0e7-beba6f8f9574 · outbound

This paper cites Spectral analysis of nonlinear flows,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Spectral analysis of nonlinear flows,

Reference 15

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Observation bc19f7d5-db05-4d79-b3a5-f835fceeb9c5 · outbound

This paper cites Instance Normalization: The Missing Ingredient for Fast Stylization.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Instance Normalization: The Missing Ingredient for Fast Stylization

Reference 16

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Observation 0e275bc6-7a01-4bb1-b834-83b40292cd6e · outbound

This paper cites One-shot voice conversion by separating speaker and content representations with instance normalization,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations One-shot voice conversion by separating speaker and content representations with instance normalization,

Reference 17

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Observation b99db861-6465-418b-abf4-b83c1ea063bb · outbound

This paper cites Again-vc: A one- shot voice conversion using activation guidance and adaptive instance normalization,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Again-vc: A one- shot voice conversion using activation guidance and adaptive instance normalization,

Reference 18

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Observation f7737f2b-74b3-46e0-9bd1-91f5a3aeb97b · outbound

This paper cites Unsupervised Representation Disentanglement Using Cross Domain Features and Adversarial Learning in Variational Au- toencoder Based V oice Conversion,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Unsupervised Representation Disentanglement Using Cross Domain Features and Adversarial Learning in Variational Au- toencoder Based V oice Conversion,

Reference 19

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Observation 43c97271-79ed-485a-87d0-d70da681a6b3 · outbound

This paper cites SpeechTripleNet: End-to-End Disentangled Speech Representation Learning for Content, Timbre and Prosody,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations SpeechTripleNet: End-to-End Disentangled Speech Representation Learning for Content, Timbre and Prosody,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-15T14:35:11.756852Z

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Observation be26720b-2f1a-4ee6-8e05-f5dd5a9efaf6 · outbound

This paper cites Disentangling prosody and timbre embeddings via voice conversion,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Disentangling prosody and timbre embeddings via voice conversion,

Reference 21

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Observation ffe8eef6-99ef-402c-8f5a-91540a892168 · outbound

This paper cites Robust Disentangled Variational Speech Representation Learning for Zero-Shot V oice Conversion,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Robust Disentangled Variational Speech Representation Learning for Zero-Shot V oice Conversion,

Reference 22

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Observation df8e660c-b5be-4d99-8e77-8c9047eecd73 · outbound

This paper cites Contrastively Disentangled Sequential Variational Autoencoder,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Contrastively Disentangled Sequential Variational Autoencoder,

Reference 23

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Observation ecbc9515-f0c9-481f-892f-395a9681a5f8 · outbound

This paper cites Unifying One-Shot V oice Conversion and Cloning with Disentangled Speech Representations,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Unifying One-Shot V oice Conversion and Cloning with Disentangled Speech Representations,

Reference 24

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Observation 85d0dec8-5dff-4801-847a-e85fb8acada1 · outbound

This paper cites Dynamic mode decomposition of numerical and experi- mental data,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Dynamic mode decomposition of numerical and experi- mental data,

Reference 25

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Observation 22bb37bd-60a4-4e91-998c-8881cee8671d · outbound

This paper cites A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition,

Reference 26

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Observation c2f48d12-f73b-4068-a823-9f1535ff9e3c · outbound

This paper cites Characterizing and correcting for the effect of sensor noise in the dynamic mode decomposition,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Characterizing and correcting for the effect of sensor noise in the dynamic mode decomposition,

Reference 27

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Observation 31f6e844-2167-4de3-b0ef-572f1802b466 · outbound

This paper cites Modern koopman theory for dynamical systems,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Modern koopman theory for dynamical systems,

Reference 28

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Observation 3490f646-3ae2-441f-b465-6dbf8ecac51c · outbound

This paper cites Learning Koopman invariant subspaces for dynamic mode decomposition,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Learning Koopman invariant subspaces for dynamic mode decomposition,

Reference 29

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This paper cites Deep learning for universal linear embeddings of nonlinear dynamics,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Deep learning for universal linear embeddings of nonlinear dynamics,

Reference 30

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Observation ee7c9db0-da4c-4801-8f3b-37d7704cd249 · outbound

This paper cites Forecasting sequential data using consistent koopman autoencoders,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Forecasting sequential data using consistent koopman autoencoders,

Reference 31

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Observation 4f7f68f4-cb2e-458a-ae1c-1722be1c2809 · outbound

This paper cites Transformers for Modeling Physical Sys- tems,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Transformers for Modeling Physical Sys- tems,

Reference 32

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Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors,

Reference 33

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Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Multifactor Sequential Disen- tanglement via Structured Koopman Autoencoders,

Reference 34

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Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Hierarchical Koopman Diffusion: Fast Generation with Interpretable Diffusion Trajectory,

Reference 35

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This paper cites Koopman Neural Forecaster for Time Series With Temporal Distribution Shifts,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Koopman Neural Forecaster for Time Series With Temporal Distribution Shifts,

Reference 36

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This paper cites Linearly recurrent autoencoder networks for learning dynamics,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Linearly recurrent autoencoder networks for learning dynamics,

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Observation f1b6f2ac-f9d1-42a3-894f-27f404b13d6e · outbound

This paper cites Compressed dynamic mode decomposition for background modeling,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Compressed dynamic mode decomposition for background modeling,

Reference 38

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Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Long Short-Term Memory,

Reference 39

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This paper cites Deep Residual Learning for Image Recognition,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Deep Residual Learning for Image Recognition,

Reference 40

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This paper cites Deep Speaker: an End-to-End Neural Speaker Embedding System.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Deep Speaker: an End-to-End Neural Speaker Embedding System

Reference 41

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This paper cites Instance-based temporal normalization for speaker Verification,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Instance-based temporal normalization for speaker Verification,

Reference 42

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This paper cites SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition,

Reference 43

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This paper cites Decoupled Weight Decay Regularization,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Decoupled Weight Decay Regularization,

Reference 44

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Observation dccba8d7-687b-47b1-99ea-5b15541ed272 · outbound

This paper cites CSTR VCTK Corpus: English Multi-speaker Corpus for CSTR V oice Cloning Toolkit (version 0.92),.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations CSTR VCTK Corpus: English Multi-speaker Corpus for CSTR V oice Cloning Toolkit (version 0.92),

Reference 45

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This paper cites TIMIT Acoustic-Phonetic Continuous Speech Corpus,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations TIMIT Acoustic-Phonetic Continuous Speech Corpus,

Reference 46

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Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations WebRTC voice activity detection,

Reference 47

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Observation 7b9a4587-d357-4db0-84e1-6b749f2258bc · outbound

This paper cites Visualizing Data using t-SNE,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Visualizing Data using t-SNE,

Reference 48

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Observation 46b1a4e3-5260-4688-9ce7-16aa4ee514aa · outbound

This paper cites Transformers in speech processing: Over- coming challenges and paving the future,.

Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Transformers in speech processing: Over- coming challenges and paving the future,

Reference 49

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