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Paper Citation Record · LEDGER

An Exploration of Mamba for Speech Self-Supervised Models

As of 14 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2506.12606.

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

pith.paper-citation-record.v1
2506.12606 v2

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-19T09:14:23.986764Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T16:22:07.001549Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-01T21:46:15.489876Z

Reference resolution

44 of 44 outbound references displayed

  • verified exact8
  • verified fuzzy36
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f424a9ab-e333-4a89-89b0-5eb53ffff89d · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

An Exploration of Mamba for Speech Self-Supervised Models Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 5b03949f-76e9-44a3-a0c5-5100cc5a7742 · outbound

This paper cites MambaMOT: State-Space Model as Motion Predictor for Multi-Object Tracking.

An Exploration of Mamba for Speech Self-Supervised Models MambaMOT: State-Space Model as Motion Predictor for Multi-Object Tracking

Reference 2

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raw_fallback, observed 2026-05-19T09:17:15.631965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:ef9d0416001f76d04092b04bf268bbc8015a31955f76ee25c815145f0469c440

Observation 5eeb0285-9a97-42d0-809a-edd8e7dc1429 · outbound

This paper cites Jamba: Hybrid Transformer-Mamba Language Models.

An Exploration of Mamba for Speech Self-Supervised Models Jamba: Hybrid Transformer-Mamba Language Models

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:53fbd5e28c2da066199f5ac6bcd960b0bd275d2af56658cbcf8bca8b3cffdb31

Observation 5c29b323-2c6b-489e-9fb0-941c4e660d2e · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

An Exploration of Mamba for Speech Self-Supervised Models Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 4

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local_arxiv, observed 2026-05-19T09:17:14.254488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:d96f486e5757c3c03af4bb52d3538f868e36b3a1bd84fb460c0247fe50a3eea9

Observation 5480c8ad-cd3f-45dd-aeae-2255ef53ab99 · outbound

This paper cites Speech slytherin: Examining the performance and efficiency of mamba for speech separation, recognition, and synthesis.

An Exploration of Mamba for Speech Self-Supervised Models Speech slytherin: Examining the performance and efficiency of mamba for speech separation, recognition, and synthesis

Reference 5

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raw_fallback, observed 2026-05-19T09:17:15.628212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:abb346c662ad6c19e5302484a2da1616a8e64c6c589edfeef02975ba85012593

Observation 9b97412f-20b2-4203-a461-b1ee7d65fa37 · outbound

This paper cites Dual-path Mamba: Short and Long-term Bidirectional Selective Structured State Space Models for Speech Separation.

An Exploration of Mamba for Speech Self-Supervised Models Dual-path Mamba: Short and Long-term Bidirectional Selective Structured State Space Models for Speech Separation

Reference 6

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raw_fallback, observed 2026-05-19T09:17:15.670482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:984eeb0fa768ff0e414df4a34508eda4547c7dc11789c04282ba1c2fae732b4a

Observation 0371e0f9-0957-4749-9661-2267dbeace1e · outbound

This paper cites Speech-Mamba: Long-Context Speech Recog- nition with Selective State Spaces Models.

An Exploration of Mamba for Speech Self-Supervised Models Speech-Mamba: Long-Context Speech Recog- nition with Selective State Spaces Models

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:ab80fc78fd3b4156b54530edbfec56745bae87a204e4c394428bae42f28a82cd

Observation 8cc3e1fc-3fc3-4f61-8252-f5fb66fd66c2 · outbound

This paper cites SPMamba: State-space model is all you need in speech separation.

An Exploration of Mamba for Speech Self-Supervised Models SPMamba: State-space model is all you need in speech separation

Reference 8

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arxiv_id, observed 2026-05-19T09:17:14.294989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:ed0e18f5fbd3d872bca8cf49558f2c9fae10e57b8e8faa6ad66ce060fcd95701

Observation f1f37833-93df-4059-b0cc-913899fdac33 · outbound

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

An Exploration of Mamba for Speech Self-Supervised Models HuBERT: Self-supervised speech representation learning by masked prediction of hidden units

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:c82acc5d0624e6bec59e641757d0404578ceaa6d0bf77497f412b1c3336b73d5

Observation e99a844c-562b-4fc8-8c4f-7d0d87706270 · outbound

This paper cites Mamba in Speech: Towards an Alternative to Self-Attention.

An Exploration of Mamba for Speech Self-Supervised Models Mamba in Speech: Towards an Alternative to Self-Attention

Reference 10

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arxiv_id, observed 2026-05-19T09:17:14.288905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:3e257b5e5c284ca8d8e076ea3a987452577c9cae77c1f9d32c9f338c370d01db

Observation eecddfcf-583d-4b3d-9909-49a9ace310fb · outbound

This paper cites Relations between two sets of variates.

An Exploration of Mamba for Speech Self-Supervised Models Relations between two sets of variates

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:d379386c3f07f371c5bb2365b0d73ff714e7f4d94f6a38a22896a3dc7aaa8a79

Observation 816519ec-c69c-4629-a9b4-d4ec77d54772 · outbound

This paper cites SUPERB: Speech Processing Universal PERformance Benchmark.

An Exploration of Mamba for Speech Self-Supervised Models SUPERB: Speech Processing Universal PERformance Benchmark

Reference 12

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raw_fallback, observed 2026-05-19T09:17:15.659459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:0dc64d74b7a7c18ec66ed996ef8713ba83a6a08678346ffca96970e5b8121476

Observation cee98c5b-a1e0-4453-be6e-cac36b8d7820 · outbound

This paper cites wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations.

An Exploration of Mamba for Speech Self-Supervised Models wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations

Reference 13

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raw_fallback, observed 2026-05-19T09:17:15.643466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:d6c40726d126f0115286fbe7fc087552a4659a5abace9afa842da86f4c5431a5

Observation 1bb5e881-b469-4d0e-b0f0-fb4d8215449b · outbound

This paper cites An Investigation of Incorporating Mamba For Speech Enhancement.

An Exploration of Mamba for Speech Self-Supervised Models An Investigation of Incorporating Mamba For Speech Enhancement

Reference 14

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raw_fallback, observed 2026-05-19T09:17:15.639374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:8254b7ccb3ea5a567e5dbdb84ea75ebe8d41629e972212d7f9177955a3081d0b

Observation 82f852cf-ac10-4044-89f3-faca2b8f740c · outbound

This paper cites Mamba for Streaming ASR Combined with Unimodal Aggregation.

An Exploration of Mamba for Speech Self-Supervised Models Mamba for Streaming ASR Combined with Unimodal Aggregation

Reference 15

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raw_fallback, observed 2026-05-19T09:17:15.647383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:4e27d677a919b655f2e44f01a8f5ed09facee2715d2a3e31e46bf9c7be294672

Observation ea121dea-62bc-44cb-a12f-c30af5731637 · outbound

This paper cites Rethinking Mamba in Speech Processing by Self-Supervised Models.

An Exploration of Mamba for Speech Self-Supervised Models Rethinking Mamba in Speech Processing by Self-Supervised Models

Reference 16

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raw_fallback, observed 2026-05-19T09:17:15.651118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:5433f52d9f5de1db5cb6aaf306078e03da959c3e0495ae6cf2b3d1fd612c0fcc

Observation 8b2f420b-3a42-4fbf-81cc-c300b460109b · outbound

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

An Exploration of Mamba for Speech Self-Supervised Models Audio Mamba: Selective State Spaces for Self- Supervised Audio Representations

Reference 17

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:933781ea46638420ef3deed55de25a712c0579877141ded44be7fbad58f7e14e

Observation 36b8ad1c-690c-4b23-963e-45aa9583c529 · outbound

This paper cites Superb@ slt 2022: Challenge on generalization and efficiency of self-supervised speech representation learning.

An Exploration of Mamba for Speech Self-Supervised Models Superb@ slt 2022: Challenge on generalization and efficiency of self-supervised speech representation learning

Reference 18

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raw_fallback, observed 2026-05-19T09:17:15.769582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:155778e9508ba0e3f34a6be3525f993826cb0e2517660a38ae9ff06b60fa1d58

Observation 9500473b-58fc-42d1-8b99-523b99de3b82 · outbound

This paper cites Is Smaller Always Faster? Tradeoffs in Compressing Self-Supervised Speech Transformers.

An Exploration of Mamba for Speech Self-Supervised Models Is Smaller Always Faster? Tradeoffs in Compressing Self-Supervised Speech Transformers

Reference 19

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arxiv_id, observed 2026-07-23T01:24:11.529612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:c4287d0abc4d765e28664706abfcb650d4248e8973986b94527049504186cbad

Observation f538a518-ec3f-41c2-a89e-d6b0f9552a1c · outbound

This paper cites TED-LIUM 3: Twice as much data and corpus repartition for experi- ments on speaker adaptation.

An Exploration of Mamba for Speech Self-Supervised Models TED-LIUM 3: Twice as much data and corpus repartition for experi- ments on speaker adaptation

Reference 20

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raw_fallback, observed 2026-05-19T09:17:15.747621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:94ee402423dd8cb7d51d4ab2f27c4b62e51643a16363f25bee8588ecfe65c469

Observation c0b7c5db-88f8-4541-a282-db6da309a436 · outbound

This paper cites On gener- ative spoken language modeling from raw audio.

An Exploration of Mamba for Speech Self-Supervised Models On gener- ative spoken language modeling from raw audio

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:a922279e55bfefc87acd95baca769fab66f811521546f9925cc9ae1efd9f23dd

Observation daeaf476-bac1-4e13-af04-e655732b1892 · outbound

This paper cites Textually Pretrained Speech Language Models.

An Exploration of Mamba for Speech Self-Supervised Models Textually Pretrained Speech Language Models

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:8485da51a616d3ed1cdd48df4b2a8d1401be5215133c65a327508a8c02612246

Observation 0ddffa19-1352-46ff-b2f6-adf4f1bfdc26 · outbound

This paper cites On The Landscape of Spoken Language Models: A Comprehensive Survey.

An Exploration of Mamba for Speech Self-Supervised Models On The Landscape of Spoken Language Models: A Comprehensive Survey

Reference 23

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local_arxiv, observed 2026-05-19T09:17:14.267181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:e84c2a15462746943e5f87b6495f2d82bb47aeadbc1b1b0f4230414a4ed049cc

Observation ff4670ec-3110-42d1-a873-856cc67b65f2 · outbound

This paper cites Building a Taiwanese Mandarin Spoken Language Model: A First Attempt.

An Exploration of Mamba for Speech Self-Supervised Models Building a Taiwanese Mandarin Spoken Language Model: A First Attempt

Reference 24

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arxiv_id, observed 2026-05-19T09:17:14.276089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:ca7e2dcd5b75f2e7144ae2aacc7c100e66e483c79ae11ea5b453c9069c9811c7

Observation 29dfd8ae-25fb-4689-998e-f25803d939bd · outbound

This paper cites Dynamic-SUPERB Phase-2: A Collaboratively Ex- panding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks.

An Exploration of Mamba for Speech Self-Supervised Models Dynamic-SUPERB Phase-2: A Collaboratively Ex- panding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks

Reference 25

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raw_fallback, observed 2026-05-19T09:17:15.712593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:2807b815a2d80c212b9c948e568d45b7133970b3380800accd9357f101ad3ac8

Observation 49a0c977-947f-4312-a495-5dca35bc74e4 · outbound

This paper cites Layer-wise analysis of a self-supervised speech representation model.

An Exploration of Mamba for Speech Self-Supervised Models Layer-wise analysis of a self-supervised speech representation model

Reference 26

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raw_fallback, observed 2026-05-19T09:17:15.666631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:ddefe5bdc8049af378b306dc436005d6b47ba39247654f7728a8a1e7e890c4f5

Observation 9161b507-8222-4825-b721-ea305aea33cd · outbound

This paper cites DAISY: Data Adaptive Self- Supervised Early Exit for Speech Representation Models.

An Exploration of Mamba for Speech Self-Supervised Models DAISY: Data Adaptive Self- Supervised Early Exit for Speech Representation Models

Reference 27

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raw_fallback, observed 2026-05-19T09:17:15.751975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:b4af0a81b6713bbc2b86fd26a898fc2297236a7f199f706fcf8624a8d75b2aed

Observation 5c474dcc-405c-4622-a1b1-0e6464bd3d3f · outbound

This paper cites What do self- supervised speech models know about words?.

An Exploration of Mamba for Speech Self-Supervised Models What do self- supervised speech models know about words?

Reference 28

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raw_fallback, observed 2026-05-19T09:17:15.716567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:60977194659dc595420099a2817c416eed9709b8248a2cb14ce618327ee0dbea

Observation 683849fe-c91e-4ccc-a4df-7274498c7a8e · outbound

This paper cites Property Neurons in Self-Supervised Speech Transformers.

An Exploration of Mamba for Speech Self-Supervised Models Property Neurons in Self-Supervised Speech Transformers

Reference 29

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raw_fallback, observed 2026-05-19T09:17:15.720658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:93f94219c38c59bf3b228911d76cf93cee7208ca2b633477a7fb042c5d49276b

Observation d0313ef1-5db8-4fd3-bd3d-61cd900ead47 · outbound

This paper cites MelHuBERT: A Simplified Hubert on Mel Spectrograms.

An Exploration of Mamba for Speech Self-Supervised Models MelHuBERT: A Simplified Hubert on Mel Spectrograms

Reference 30

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raw_fallback, observed 2026-05-19T09:17:15.708177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:ca01b601b41762f40937af1294f45d9257e003550e6c175cb8176b0b034daef7

Observation a2a114d9-cada-4cd9-9561-6301a9b14ac6 · outbound

This paper cites Generalized end-to-end loss for speaker verification.

An Exploration of Mamba for Speech Self-Supervised Models Generalized end-to-end loss for speaker verification

Reference 31

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raw_fallback, observed 2026-05-19T09:17:15.724826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:9ffc49c3aa844090e97ff89e9dad33c8c925a36e9063b2f49e4108b0d6742d9b

Observation 2e2daf8c-8c93-4ec9-b5b1-ea598e6c7cd6 · outbound

This paper cites Titanet: Neural model for speaker representation with 1d depth-wise separable convolutions and global context.

An Exploration of Mamba for Speech Self-Supervised Models Titanet: Neural model for speaker representation with 1d depth-wise separable convolutions and global context

Reference 32

Resolution
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raw_fallback, observed 2026-05-19T09:17:15.738595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:b1d23c8c781cfd4a83b7bac95cb0e05d6e7299c4f14d94c45f31c0d0d1cfdd66

Observation 2174fa52-9df8-49a8-8460-34183b0b55b5 · outbound

This paper cites ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verification.

An Exploration of Mamba for Speech Self-Supervised Models ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verification

Reference 33

Resolution
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arxiv_id, observed 2026-05-19T09:17:14.261196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:bf5c1acd9ef03e2a5f323c1bb660c57fb8bc6c6a1107b8c71d2bcd7aac0081b6

Observation b2b38881-561e-42c4-a509-13d6da057884 · outbound

This paper cites emotion2vec: Self-Supervised Pre-Training for Speech Emotion Repre- sentation.

An Exploration of Mamba for Speech Self-Supervised Models emotion2vec: Self-Supervised Pre-Training for Speech Emotion Repre- sentation

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T09:17:15.763593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:15eec89ccd9f4c70af80f22b4827b66a07f55f5d7555117c2e19e79cc5265df3

Observation 7cfc88f7-5f54-4835-81f2-9992cdc4040a · outbound

This paper cites MiniSu- PEBR: Lightweight benchmark for self-supervised speech models.

An Exploration of Mamba for Speech Self-Supervised Models MiniSu- PEBR: Lightweight benchmark for self-supervised speech models

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T09:17:15.704289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:3dae77314aa84a5050121e20d4f6e8462ad349a65a510ecb149cfd7f4f2dc871

Observation 68af80ba-0743-49d7-91ca-d1307323ee72 · outbound

This paper cites ML- SUPERB: Multilingual Speech Universal PERformance Benchmark.

An Exploration of Mamba for Speech Self-Supervised Models ML- SUPERB: Multilingual Speech Universal PERformance Benchmark

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T09:17:15.689476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:cad026f8b2a9329f0ec729fc4b3cd72ae7d68c3ec7f9424adb6b63072d4bd415

Observation eb230e87-06e0-4acb-abf7-375c622bac07 · outbound

This paper cites Findings of the 2023 ML-SUPERB challenge: Pre-training and evaluation over more languages and beyond.

An Exploration of Mamba for Speech Self-Supervised Models Findings of the 2023 ML-SUPERB challenge: Pre-training and evaluation over more languages and beyond

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T09:17:15.685720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:bb53d608f3d19fc70b7ab94a68bff880c81ed3e99fceb40bfb90f4e41e57c6bb

Observation 006eab8f-774a-4fba-a1d9-f6091a340cf4 · outbound

This paper cites Multi-resolution Hu- BERT: Multi-resolution Speech Self-Supervised Learning with Masked Unit Prediction.

An Exploration of Mamba for Speech Self-Supervised Models Multi-resolution Hu- BERT: Multi-resolution Speech Self-Supervised Learning with Masked Unit Prediction

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T09:17:15.693018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:895225458a72be01c4046cee543c855110103225b67bc41f095aff20e1743e8b

Observation c1df901f-6a9b-42a3-a92c-a890968978d9 · outbound

This paper cites Task- Agnostic Structured Pruning of Speech Representation Models.

An Exploration of Mamba for Speech Self-Supervised Models Task- Agnostic Structured Pruning of Speech Representation Models

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T09:17:15.696930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:c1cc0a9e46dac883c5bf0dff914fd426f8063c23ba71a0876f806e0570fbc185

Observation fe281e32-c847-4520-9570-5250e386113f · outbound

This paper cites Speech-FT: Merging Pre-trained And Fine-Tuned Speech Representation Models For Cross-Task Generalization.

An Exploration of Mamba for Speech Self-Supervised Models Speech-FT: Merging Pre-trained And Fine-Tuned Speech Representation Models For Cross-Task Generalization

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-05-19T09:17:14.282401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:e5ba6c8fe0fa15a4b2073a4ea5f13521eda235d8c9bbb25b9402e80cb31557b2

Observation 3491453f-5c13-4721-a53c-02700e85aa60 · outbound

This paper cites Speech Self-Supervised Representation Benchmarking: Are We Doing it Right?.

An Exploration of Mamba for Speech Self-Supervised Models Speech Self-Supervised Representation Benchmarking: Are We Doing it Right?

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T09:17:15.674247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:dd59b99b90e6878f7e287bb6c7e252e0e095935dca4c8e9debafa8856a7ffdcd

Observation ba8b37de-8fd1-4b06-ab55-6765351b0fd4 · outbound

This paper cites Towards a Unified Representation Evaluation Framework Beyond Downstream Tasks.

An Exploration of Mamba for Speech Self-Supervised Models Towards a Unified Representation Evaluation Framework Beyond Downstream Tasks

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T09:17:15.677852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:d1c2505b9c1c1272df79363defa7f72976b9bd4d7539308afd2abece39f898f4

Observation a0706b73-fd7a-41b9-b3db-844d781c9e9c · outbound

This paper cites What Can an Accent Identifier Learn? Probing Phonetic and Prosodic Information in a Wav2vec2-based Accent Identification Model.

An Exploration of Mamba for Speech Self-Supervised Models What Can an Accent Identifier Learn? Probing Phonetic and Prosodic Information in a Wav2vec2-based Accent Identification Model

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T09:17:15.681904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:ed99927770eb9607154fcb19cb4854f0ee16b7043ac77afe30f95e5b497b9fec

Observation 52199b8a-a4bc-4203-b4ec-3525bfb97348 · outbound

This paper cites What Do Self-Supervised Vision Transformers Learn?.

An Exploration of Mamba for Speech Self-Supervised Models What Do Self-Supervised Vision Transformers Learn?

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T09:17:15.700569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:a9e127234a1b3c0beea78cbe7167f5afa768b72d8fbe79ba82e238abda8d2a4b

Pith citing papers

Observation 4ff077a9-6024-43fc-893d-1013741a479f · inbound

Spiking and Event-driven Neuromorphic Mamba Models for Efficient Speech Recognition cites this paper.

Spiking and Event-driven Neuromorphic Mamba Models for Efficient Speech Recognition An Exploration of Mamba for Speech Self-Supervised Models

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-07-01T21:46:15.491266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T16:22:07.001549Z digest=sha256:0785c5ace8db83d4f2f3a5113a77777119e7bc721143eab098944b7a7eae3722