From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning | Paper Citation Record

Observation 15fb7307-b67c-45a7-a1d2-53679810ab05 · outbound

This paper cites Deep learning.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Deep learning

Reference 1

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Observation b09b9182-b6bc-4a2d-bb4d-4c52cbef2beb · outbound

This paper cites Deep learning for audio signal processing,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Deep learning for audio signal processing,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.356882Z

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This paper cites Audio signal processing in the 21st century: The important outcomes of the past 25 years,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Audio signal processing in the 21st century: The important outcomes of the past 25 years,

Reference 3

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This paper cites Audio set: An ontology and human-labeled dataset for audio events.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Audio set: An ontology and human-labeled dataset for audio events

Reference 4

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This paper cites MAT-SED: A Masked Audio Transformer with Masked-Reconstruction Based Pre-training for Sound Event Detection.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning MAT-SED: A Masked Audio Transformer with Masked-Reconstruction Based Pre-training for Sound Event Detection

Reference 5

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This paper cites Taming data and transformers for audio generation,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Taming data and transformers for audio generation,

Reference 6

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Observation d9698c30-4990-4f27-ad34-fff468b6eebb · outbound

This paper cites Deep convolutional neural networks and data augmentation for environmental sound classification,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Deep convolutional neural networks and data augmentation for environmental sound classification,

Reference 7

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Observation 1f28c6f7-96b4-4c15-93cf-7e9832a83473 · outbound

This paper cites Synthio: Augmenting Small-Scale Audio Classification Datasets with Synthetic Data.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Synthio: Augmenting Small-Scale Audio Classification Datasets with Synthetic Data

Reference 8

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Observation c0593eb1-4fd6-4ead-8a07-8034fbfc99eb · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Explaining and Harnessing Adversarial Examples

Reference 9

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Observation f3e5354a-08f0-4a63-ba49-0c7f789b9133 · outbound

This paper cites Intriguing properties of neural networks.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Intriguing properties of neural networks

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-02T05:56:39.876297Z

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Observation 2ea35bd5-ebd5-4fd9-adea-31c56068fcaa · outbound

This paper cites Understanding deep learning requires rethinking generalization.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Understanding deep learning requires rethinking generalization

Reference 11

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Observation d26ce9db-c44b-433a-8ffc-a124754bf397 · outbound

This paper cites wav2vec: Unsupervised Pre-training for Speech Recognition.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning wav2vec: Unsupervised Pre-training for Speech Recognition

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.839281Z

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Observation 7c5a3410-c7d9-4c56-ae47-80359d2b001c · outbound

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

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

Reference 13

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This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representations,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.370879Z

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Observation 7e034ff8-c32f-4c80-a6c5-71d03422ef6f · outbound

This paper cites Musical genre classification of audio signals,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Musical genre classification of audio signals,

Reference 15

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Observation c71a135f-dc0e-43d6-803c-67325fd54f4e · outbound

This paper cites Dynamic attention-asymmetric perceptron network for overlapping sound event detection,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Dynamic attention-asymmetric perceptron network for overlapping sound event detection,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.241172Z

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This paper cites SPEAR: A Unified SSL Framework for Learning Speech and Audio Representations.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning SPEAR: A Unified SSL Framework for Learning Speech and Audio Representations

Reference 17

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Observation fe046f72-72e3-4569-a496-4df20a5c0450 · outbound

This paper cites Scaling up masked audio encoder learning for general audio classification.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Scaling up masked audio encoder learning for general audio classification

Reference 18

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Observation 481eff0a-cddb-4d9e-84a4-70be59d97455 · outbound

This paper cites A survey on contrastive self-supervised learning,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning A survey on contrastive self-supervised learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.172411Z

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Observation f1b9320e-9f57-4860-9cb3-00449f42f143 · outbound

This paper cites Audio self-supervised learning: A survey.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Audio self-supervised learning: A survey

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.223855Z

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Observation 4a149a3f-1bf0-4a07-ad24-a4cf9d6518a0 · outbound

This paper cites Scaling bioacoustic signal pre-training with million samples via mask- modeling,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Scaling bioacoustic signal pre-training with million samples via mask- modeling,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.234892Z

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Observation 72e0138e-a7e1-4d02-b026-8ba09aaee080 · outbound

This paper cites Hearsay benchmark: Do audio llms leak what they hear?.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Hearsay benchmark: Do audio llms leak what they hear?

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.913510Z

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Observation 81fd931b-6c9f-4d44-942a-f7d388e79ac4 · outbound

This paper cites A survey on self-supervised learning: Algorithms, applications, and future trends.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning A survey on self-supervised learning: Algorithms, applications, and future trends

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.180032Z

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Observation 347f6342-5f94-4917-9acb-daf95f526d97 · outbound

This paper cites Self-supervised speech representation learning: A review.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Self-supervised speech representation learning: A review

Reference 24

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This paper cites Ssast: Self- supervised audio spectrogram transformer,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Ssast: Self- supervised audio spectrogram transformer,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.170725Z

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Observation 84be8aab-8c1e-49b8-8a5a-32cf5c7c9888 · outbound

This paper cites Unsupervised feature learning via non-parametric instance discrimination,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Unsupervised feature learning via non-parametric instance discrimination,

Reference 26

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Observation 0bd43875-1f31-4841-88c4-bd1ee41e19b3 · outbound

This paper cites Unsupervised representation learning by predicting image rotations,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Unsupervised representation learning by predicting image rotations,

Reference 27

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Observation e9dad6be-bad1-42f4-9e46-3f2e68bad82b · outbound

This paper cites Unsupervised learning of visual representa- tions by solving jigsaw puzzles,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Unsupervised learning of visual representa- tions by solving jigsaw puzzles,

Reference 28

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This paper cites A simple frame- work for contrastive learning of visual representations,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning A simple frame- work for contrastive learning of visual representations,

Reference 29

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This paper cites Contrastive learning of general-purpose audio representations.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Contrastive learning of general-purpose audio representations

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.425492Z

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This paper cites Masked autoencoders are scalable vision learners.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Masked autoencoders are scalable vision learners

Reference 31

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Observation be3db07c-2e93-427c-b69e-798f0e3653a7 · outbound

This paper cites Masked autoencoders that listen,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Masked autoencoders that listen,

Reference 32

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This paper cites Masked spectrogram prediction for self-supervised audio pre-training,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Masked spectrogram prediction for self-supervised audio pre-training,

Reference 33

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This paper cites Recent advances in discrete speech tokens: A review.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Recent advances in discrete speech tokens: A review

Reference 34

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Observation f7a930f7-f2ed-43c5-8098-c40fa06e921e · outbound

This paper cites BEATs: Audio Pre-Training with Acoustic Tokenizers.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning BEATs: Audio Pre-Training with Acoustic Tokenizers

Reference 35

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

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Hubert: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.415039Z

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Observation 4de403c4-307c-4cdc-9964-1f5a62be1a00 · outbound

This paper cites Vatt: Transformers for multimodal self-supervised learning from raw video, audio and text,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Vatt: Transformers for multimodal self-supervised learning from raw video, audio and text,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.452408Z

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Observation e32121c7-b816-4b15-a5be-086d5824a4ef · outbound

This paper cites Large-scale contrastive language-audio pretraining with feature fusion and keyword-to-caption augmentation.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Large-scale contrastive language-audio pretraining with feature fusion and keyword-to-caption augmentation

Reference 38

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Observation e99942a6-4d46-4b9d-9083-5efb883c2094 · outbound

This paper cites Clap learning audio concepts from natural language supervision.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Clap learning audio concepts from natural language supervision

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.407150Z

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Observation f5d8c9f3-b88a-4343-96dc-dc6752ba8468 · outbound

This paper cites Pre-training audio representations with self-supervision,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Pre-training audio representations with self-supervision,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.437006Z

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Observation 94c3c24e-d8b9-4854-abb9-db81a73bc0cb · outbound

This paper cites Shuffle and learn: unsupervised learning using temporal order verification,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Shuffle and learn: unsupervised learning using temporal order verification,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.439193Z

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Observation 950485b2-41d6-4fe1-83b8-9a37ce1cdcdf · outbound

This paper cites Self-supervised learning of audio representations from permutations with differentiable ranking,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Self-supervised learning of audio representations from permutations with differentiable ranking,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.400585Z

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Observation 2e338edc-21fc-4abc-9e48-9aeed74f2cd7 · outbound

This paper cites Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks

Reference 43

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Observation 539ae367-2a03-44ff-b666-3652f12aa5f4 · outbound

This paper cites Multi-task self-supervised learning for robust speech recognition,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Multi-task self-supervised learning for robust speech recognition,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.404619Z

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This paper cites Clar: Contrastive learning of auditory representations,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Clar: Contrastive learning of auditory representations,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.386271Z

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Observation f331f772-8796-44e9-9838-cb4b07a675d5 · outbound

This paper cites Byol for audio: Exploring pre-trained general-purpose audio repre- 22 sentations,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Byol for audio: Exploring pre-trained general-purpose audio repre- 22 sentations,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.393585Z

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Observation e4679cb1-8c95-49ee-a2be-dcbcd1130fe5 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Representation Learning with Contrastive Predictive Coding

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-07-02T05:56:39.898991Z

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Observation 39855e98-1e4a-4296-814b-5edd9143696e · outbound

This paper cites Byol for audio: Self-supervised learning for general-purpose audio representation,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Byol for audio: Self-supervised learning for general-purpose audio representation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.447668Z

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Observation c28c2cd5-21e4-4a01-bcb2-a7bed13bdfa9 · outbound

This paper cites An Unsupervised Autoregressive Model for Speech Representation Learning.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning An Unsupervised Autoregressive Model for Speech Representation Learning

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-07-02T05:56:39.910790Z

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Observation 4526c40a-3467-4301-b3a9-b326e4f8b846 · outbound

This paper cites Mockingjay: Unsupervised speech representation learning with deep bidirectional transformer encoders,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Mockingjay: Unsupervised speech representation learning with deep bidirectional transformer encoders,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.383858Z

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 8ab2afd9-9ca3-4e50-acd4-93ffb9e8f98d · outbound

This paper cites Audio albert: A lite bert for self-supervised learning of audio representation,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Audio albert: A lite bert for self-supervised learning of audio representation,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.409863Z

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 5e014b4c-f80e-49d0-b73c-8c65e9531226 · outbound

This paper cites Audioldm 2: Learning holistic audio generation with self-supervised pretraining.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Audioldm 2: Learning holistic audio generation with self-supervised pretraining

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.417838Z

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 418d0736-613b-4ee4-98d4-f3e77d558404 · outbound

This paper cites MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformer.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformer

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.856520Z

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 184b1b0b-25c5-4db5-84e2-06b255d85cd3 · outbound

This paper cites w2v-bert: Combining contrastive learning and masked language modeling for self-supervised speech pre-training,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning w2v-bert: Combining contrastive learning and masked language modeling for self-supervised speech pre-training,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.457041Z

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 8671d9b6-11af-48d1-9654-13eb951fece5 · outbound

This paper cites Wavlm: Large-scale self-supervised pre- training for full stack speech processing.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Wavlm: Large-scale self-supervised pre- training for full stack speech processing

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.366138Z

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 7a747007-214b-4571-a80e-cf14747836e4 · outbound

This paper cites Discrete audio tokens: More than a survey!.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Discrete audio tokens: More than a survey!

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.932308Z

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 c58dfbec-4b83-49b6-89fb-1b284891cad0 · outbound

This paper cites Data2vec: A general framework for self-supervised learning in speech, vision and language.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Data2vec: A general framework for self-supervised learning in speech, vision and language

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.373133Z

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 afd95574-7c8f-41cb-a244-7bbfc574dbc3 · outbound

This paper cites EAT: Self-Supervised Pre-Training with Efficient Audio Transformer.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning EAT: Self-Supervised Pre-Training with Efficient Audio Transformer

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.916640Z

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 9d8dd83f-1272-4b98-b238-0291ef7e9ef2 · outbound

This paper cites Look, listen and learn.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Look, listen and learn

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.363660Z

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 b0f5883d-5eb2-45b7-9102-60fa7b250c75 · outbound

This paper cites Soundnet: Learning sound representations from unlabeled video,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Soundnet: Learning sound representations from unlabeled video,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.376544Z

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 e4c916b3-53db-4971-a3ad-ddf3decbcb74 · outbound

This paper cites Robust audio-visual in- stance discrimination,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Robust audio-visual in- stance discrimination,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.350626Z

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 4b9c210a-1092-4f56-b8dc-72802efc662c · outbound

This paper cites Audioclip: Extending clip to image, text and audio.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Audioclip: Extending clip to image, text and audio

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.217968Z

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 ab04c334-86a2-4bfd-ba50-c9208a35e265 · outbound

This paper cites Self-supervised audio teacher-student transformer for both clip-level and frame-level tasks,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Self-supervised audio teacher-student transformer for both clip-level and frame-level tasks,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.348438Z

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 7d8c8085-3369-4f67-a2a9-ff65d861caf5 · outbound

This paper cites Audio Mamba: Selective State Spaces for Self-Supervised Audio Representations.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Audio Mamba: Selective State Spaces for Self-Supervised Audio Representations

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.798062Z

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 f73f66d7-732d-4d73-a7eb-0f6c06f869d7 · outbound

This paper cites SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.815085Z

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 f5ab6965-481c-4113-8987-115d97b9ebb1 · outbound

This paper cites Mamba in speech: Towards an alternative to self-attention,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Mamba in speech: Towards an alternative to self-attention,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.352668Z

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 5c283c3e-87ff-46fc-9488-c38df3c319e1 · outbound

This paper cites xlstm: Extended long short-term memory,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning xlstm: Extended long short-term memory,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.198951Z

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 8ba750ba-0085-46ab-a873-33fd755affa7 · outbound

This paper cites AxLSTMs: learning self-supervised audio representations with xLSTMs.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning AxLSTMs: learning self-supervised audio representations with xLSTMs

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.837872Z

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 03da306f-1914-42f7-991a-538d5156499a · outbound

This paper cites Tera: Self-supervised learning of transformer encoder representation for speech.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Tera: Self-supervised learning of transformer encoder representation for speech

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.412584Z

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 8376e35f-5aeb-4bfc-aea8-66cf16962f44 · outbound

This paper cites AST: Audio Spectrogram Transformer.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning AST: Audio Spectrogram Transformer

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.820388Z

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 8d77ddb9-f659-4438-ba77-924dbc38be1f · outbound

This paper cites AaSP: Aliasing-aware Self-Supervised Pre-Training for Audio Spectrogram Transformers.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning AaSP: Aliasing-aware Self-Supervised Pre-Training for Audio Spectrogram Transformers

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-07-02T05:56:39.906436Z

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 4ca4d881-c727-4479-a123-a09b332b838b · outbound

This paper cites Bigssl: Exploring the frontier of large-scale semi-supervised learning for automatic speech recognition,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Bigssl: Exploring the frontier of large-scale semi-supervised learning for automatic speech recognition,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.434677Z

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 880f7438-026d-4164-9e5e-bd9f6409e7a1 · outbound

This paper cites HyperConformer: Multi-head HyperMixer for Efficient Speech Recognition.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning HyperConformer: Multi-head HyperMixer for Efficient Speech Recognition

Reference 73

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.812037Z

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 33e22351-0061-4fd2-9fa8-035764780e79 · outbound

This paper cites Branchformer: Parallel mlp-attention architectures to capture local and global context for speech recognition and understanding,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Branchformer: Parallel mlp-attention architectures to capture local and global context for speech recognition and understanding,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.343513Z

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 55f5ba7c-e139-448d-aa7a-3c92c36ddc1b · outbound

This paper cites E-branchformer: Branchformer with enhanced merging for speech recognition,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning E-branchformer: Branchformer with enhanced merging for speech recognition,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.336962Z

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 b2610e2d-264d-4edb-aa02-8b362b035575 · outbound

This paper cites Zipformer: A faster and better encoder for automatic speech recognition.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Zipformer: A faster and better encoder for automatic speech recognition

Reference 76

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.902887Z

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 370cd1fc-f671-4e2f-a54f-28e9d9802468 · outbound

This paper cites Hts-at: A hierarchical token-semantic audio transformer for sound classification and detection.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Hts-at: A hierarchical token-semantic audio transformer for sound classification and detection

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.267939Z

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 1231c773-ab75-4841-b562-f728bf34f504 · outbound

This paper cites Joint semantic knowl- edge distillation and masked acoustic modeling for full-band speech restoration with improved intelligibility,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Joint semantic knowl- edge distillation and masked acoustic modeling for full-band speech restoration with improved intelligibility,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.331578Z

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 50d28ddc-3d53-4abd-90f2-5ecee7f34da7 · outbound

This paper cites Distilhubert: Speech represen- tation learning by layer-wise distillation of hidden-unit bert,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Distilhubert: Speech represen- tation learning by layer-wise distillation of hidden-unit bert,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.333547Z

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 d88e755e-0abe-4657-ab26-18f59f406fc8 · outbound

This paper cites Skill: Similarity-aware knowledge distillation for speech self-supervised learning,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Skill: Similarity-aware knowledge distillation for speech self-supervised learning,

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.323664Z

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 de188346-7ff0-4192-880b-24806483e9be · outbound

This paper cites Semanticodec: An ultra low bitrate semantic audio codec for general sound,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Semanticodec: An ultra low bitrate semantic audio codec for general sound,

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.461040Z

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 738c50fb-c616-4bae-9ec5-c8addfe11d27 · outbound

This paper cites WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modeling.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modeling

Reference 82

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.919713Z

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 5fbd5ea8-fb63-4e40-b732-416492efbf74 · outbound

This paper cites MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training

Reference 83

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.890564Z

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 729e9ef5-03f7-422c-862e-e34ec139aba4 · outbound

This paper cites Codecfake-omni: A large-scale codec- based deepfake speech dataset,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Codecfake-omni: A large-scale codec- based deepfake speech dataset,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.422988Z

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 9bf6d11c-0b5f-4a07-9949-777d777b2bfd · outbound

This paper cites TS3-Codec: Transformer-Based Simple Streaming Single Codec.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning TS3-Codec: Transformer-Based Simple Streaming Single Codec

Reference 85

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T05:56:39.854827Z

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 707f8a58-c63c-46b7-b60e-1c704da53897 · outbound

This paper cites Fast- hubert: an efficient training framework for self-supervised speech representation learning,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Fast- hubert: an efficient training framework for self-supervised speech representation learning,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.321801Z

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 81a34224-e9bc-45ea-9f3a-77d0da107583 · outbound

This paper cites Cnn architectures for large-scale audio classification,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Cnn architectures for large-scale audio classification,

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.261383Z

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 d8255aa3-9af7-4e4f-aaca-05ad8ab16334 · outbound

This paper cites Long short-term memory.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Long short-term memory

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.320048Z

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 9af83738-121c-4722-92c4-444b91b4a13a · outbound

This paper cites Mamba: Linear-time sequence modeling with selective state spaces.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Mamba: Linear-time sequence modeling with selective state spaces

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.327389Z

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 759a09c5-31ee-4f15-9663-88093c3b3e71 · outbound

This paper cites Attention is all you need,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Attention is all you need,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.340711Z

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 3c7bc2a3-01ec-425f-a7c0-b6088e83b0ec · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning An image is worth 16x16 words: Transformers for image recognition at scale

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.297771Z

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 9268124b-a2f4-4f8d-aea6-3087f0b1c290 · outbound

This paper cites Conformer: Convolution-augmented Transformer for Speech Recognition.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Conformer: Convolution-augmented Transformer for Speech Recognition

Reference 92

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T05:56:39.897175Z

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 abbf0d63-cf32-495b-a9cb-570350d25ac4 · outbound

This paper cites XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale

Reference 93

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.846458Z

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 379becd0-0e5e-4527-8962-460a79b8042a · outbound

This paper cites Investigating self-supervised learning-based front-end for multi-channel replay attack detection,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Investigating self-supervised learning-based front-end for multi-channel replay attack detection,

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.313603Z

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 2fc140d0-23bd-4548-9c8a-8b924dd0d98c · outbound

This paper cites SSLAM: Enhancing Self-Supervised Models with Audio Mixtures for Polyphonic Soundscapes.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning SSLAM: Enhancing Self-Supervised Models with Audio Mixtures for Polyphonic Soundscapes

Reference 95

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.911902Z

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 833c88ef-6e09-4824-93f5-67ef7b9c71eb · outbound

This paper cites AnoPatch: Towards Better Consistency in Machine Anomalous Sound Detection.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning AnoPatch: Towards Better Consistency in Machine Anomalous Sound Detection

Reference 96

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:39.830382Z

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 4fadf425-000d-4db8-af5b-f1363027a95c · outbound

This paper cites Dp- mae: A dual-path masked autoencoder based self-supervised learning method for anomalous sound detection,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Dp- mae: A dual-path masked autoencoder based self-supervised learning method for anomalous sound detection,

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.318215Z

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 60b87f4c-1ab5-45d9-afd8-2cf0790c4242 · outbound

This paper cites Muq: Self-supervised music representation learning with mel residual vector quantization,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Muq: Self-supervised music representation learning with mel residual vector quantization,

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.263379Z

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 d102e475-e100-4d7d-a099-c6fffd12f62b · outbound

This paper cites A foundation model for music informatics,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning A foundation model for music informatics,

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.265159Z

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

Observation 4beb6b9c-57a5-4b25-b726-5ce93408a548 · outbound

This paper cites Unsupervised sound separation using mixture invariant training,.

From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning Unsupervised sound separation using mixture invariant training,

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T06:52:04.259505Z

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.

Coverage vector

Reference resolution

Outbound references

Pith citing papers