Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-15T14:35:11.756852Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-15T14:35:11.756852Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
49 of 49 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation f17c9905-9f61-46fb-8a21-400a0fbf5e1b · outbound
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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Observation be26720b-2f1a-4ee6-8e05-f5dd5a9efaf6 · outbound
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
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
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
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
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
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
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
Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Modern koopman theory for dynamical systems,
Reference 28
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Unavailable: canonical work link unavailable.
Observation 3490f646-3ae2-441f-b465-6dbf8ecac51c · outbound
Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Learning Koopman invariant subspaces for dynamic mode decomposition,
Reference 29
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Unavailable: canonical work link unavailable.
Observation 0d154e1d-0367-4289-8ec5-218567a3752e · outbound
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
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
Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Transformers for Modeling Physical Sys- tems,
Reference 32
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Observation 1d95c038-8f33-4e3a-9f57-d21164184e5f · outbound
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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Observation 652aa5a3-a932-40f7-92f1-4132881a0309 · outbound
Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Multifactor Sequential Disen- tanglement via Structured Koopman Autoencoders,
Reference 34
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Unavailable: canonical work link unavailable.
Observation 99aa1075-d47c-4753-902e-9d6f35847311 · outbound
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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Observation 1ba7fff0-501e-4c99-a9d3-806a1447677d · outbound
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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Observation d521d101-8e58-48eb-8249-236e40733d21 · outbound
Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Linearly recurrent autoencoder networks for learning dynamics,
Reference 37
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Observation f1b6f2ac-f9d1-42a3-894f-27f404b13d6e · outbound
Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Compressed dynamic mode decomposition for background modeling,
Reference 38
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Observation cfae428b-7b0e-4054-8c05-bc570058d1e4 · outbound
Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Long Short-Term Memory,
Reference 39
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Observation 14d7c903-e290-4fe6-9a97-f91ec6dc1476 · outbound
Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Deep Residual Learning for Image Recognition,
Reference 40
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Observation 8840aeb3-9015-4d16-b448-11505e7e4622 · outbound
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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Observation f5f6caf4-d0fa-426e-9389-717888fe2560 · outbound
Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations Instance-based temporal normalization for speaker Verification,
Reference 42
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Observation fef5723d-b356-4373-b057-7197c4836731 · outbound
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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Observation 073545da-2087-45a8-96c5-b63d62eb0099 · outbound
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
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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Observation b0f7bf02-0220-49d6-8bae-032a71e54986 · outbound
Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations TIMIT Acoustic-Phonetic Continuous Speech Corpus,
Reference 46
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Observation aee7ec53-e770-4c7b-b872-0b4fa1044c8f · outbound
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
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
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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No inbound Pith citation observations are available.