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Paper Citation Record · LEDGER

SPMamba: State-space model is all you need in speech separation

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2404.02063.

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

pith.paper-citation-record.v1
2404.02063 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:59:22.650800Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:30:07.489304Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 8c5132fe-5fb9-4394-9f75-126bc15d70a1 · inbound

A Survey of Mamba cites this paper.

A Survey of Mamba SPMamba: State-space model is all you need in speech separation

Reference 104

Resolution
verified exact
arxiv_id, observed 2026-05-23T22:13:30.897180Z

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.

source=pdf_text observed=2026-05-23T22:09:19.917854Z digest=sha256:d7e99c8de6400449a016e2d0407075479990bcc87648cc074fc8c08e5356ace6

Observation 132855d6-1165-4f63-8963-1f9d292d60f5 · inbound

Active Speech Enhancement: Active Speech Denoising Decliping and Deveraberation cites this paper.

Active Speech Enhancement: Active Speech Denoising Decliping and Deveraberation SPMamba: State-space model is all you need in speech separation

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-07T14:59:22.650800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:59:22.650800Z digest=sha256:642e2c844d539598db5a2eb339a80aba1cf69a061e30b69133e4d372a898dc9f

Observation e6a27d0f-83b0-47a4-b831-3b0e46ed4003 · inbound

SoloSpeech: Enhancing Intelligibility and Quality in Target Speech Extraction through a Cascaded Generative Pipeline cites this paper.

SoloSpeech: Enhancing Intelligibility and Quality in Target Speech Extraction through a Cascaded Generative Pipeline SPMamba: State-space model is all you need in speech separation

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T14:22:07.370792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:22:07.370792Z digest=sha256:290d3e04f006647206967c8cbd5503d7afc5e8c06f8a6218dc0c6814290f5342

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

An Exploration of Mamba for Speech Self-Supervised Models cites this paper.

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

Reference 8

Resolution
verified exact
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T09:14:23.986764Z digest=sha256:8ea6498a5fc0f62e1ff117172f569d0b673c53353c57719ed320802bec4ac58c

Observation 100526fc-2a2d-40f2-a4e1-ed08c42b5971 · inbound

ClearerVoice-Studio: Bridging Advanced Speech Processing Research and Practical Deployment cites this paper.

ClearerVoice-Studio: Bridging Advanced Speech Processing Research and Practical Deployment SPMamba: State-space model is all you need in speech separation

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T23:11:24.519069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:11:24.519069Z digest=sha256:9214d07b1cd86ecf48366595dc93b22b5dfdaf43d2882a500fa22919b269271d

Observation b7775015-a327-4def-8d4b-21612c497fa1 · inbound

EAGLE: An Efficient Global Attention Lesion Segmentation Model for Hepatic Echinococcosis cites this paper.

EAGLE: An Efficient Global Attention Lesion Segmentation Model for Hepatic Echinococcosis SPMamba: State-space model is all you need in speech separation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T22:56:07.151729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:56:07.151729Z digest=sha256:0ddd888834ff825df7157850608b6d9a0c7871889ac77f3b08365d22a21fbf04

Observation 3a06e65c-62bc-4206-92a4-132a3b64c22b · inbound

Enhancing Stereo Sound Event Detection with BiMamba and Pretrained PSELDnet cites this paper.

Enhancing Stereo Sound Event Detection with BiMamba and Pretrained PSELDnet SPMamba: State-space model is all you need in speech separation

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T17:57:10.562636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:57:10.562636Z digest=sha256:c7ab5d2d20d9bc954586cbbb968368c2af9a07f4f81cc53e591cba5916f98b54

Observation 501289c8-deb1-4a23-a57b-4017816f344a · inbound

Cortical-SSM: A Deep State Space Model for Motor Imagery Decoding from EEG Signals cites this paper.

Cortical-SSM: A Deep State Space Model for Motor Imagery Decoding from EEG Signals SPMamba: State-space model is all you need in speech separation

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-04T09:27:09.216413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:27:09.216413Z digest=sha256:6349ba1d8c243ab0f9b48d1da47ff948f2664b2e6773aac5047943cce7b58969

Observation afe4c10b-d82c-45c7-8910-36ee9f43912c · inbound

Asymmetric Encoder-Decoder Based on Time-Frequency Correlation for Speech Separation cites this paper.

Asymmetric Encoder-Decoder Based on Time-Frequency Correlation for Speech Separation SPMamba: State-space model is all you need in speech separation

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-15T06:39:48.637256Z

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.

source=pdf_text observed=2026-05-15T06:37:31.047423Z digest=sha256:fba9c4eed2bf7a60cfbcc5c594edc4d5776534f3ca94d5770c4e1c15ba188b81

Observation d5f4684b-4c51-4ccb-bd79-ea7c8e2132ca · inbound

Query-based Cross-Modal Projector Bolstering Mamba Multimodal LLM cites this paper.

Query-based Cross-Modal Projector Bolstering Mamba Multimodal LLM SPMamba: State-space model is all you need in speech separation

Reference 34

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T08:06:47.865004Z

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.

source=arxiv_source observed=2026-06-28T06:25:26.790564Z digest=sha256:9145e960e7053702d852e80215fc65a015e39952f0ea26d09aa3e65553d53826

Observation 8bc432f0-664b-417a-921a-494b9dc31131 · inbound

State Space Models Meet Remote Sensing: A Survey cites this paper.

State Space Models Meet Remote Sensing: A Survey SPMamba: State-space model is all you need in speech separation

Reference 122

Resolution
verified exact
arxiv_id, observed 2026-07-04T19:30:07.490809Z

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.

source=arxiv_source observed=2026-06-25T21:18:05.054587Z digest=sha256:f9f5b12c6a86bb0e4f77b4a7f89c4d62a4f8b9948e21d91dca38898d8ab91cbe

Observation 6475748c-4a14-4d92-95fa-e1271f928b6c · inbound

TF-MossFormer: Integrating Convolution Gated Local-Global Attentions for Enhanced Time-Frequency Domain Monaural Speech Separation cites this paper.

TF-MossFormer: Integrating Convolution Gated Local-Global Attentions for Enhanced Time-Frequency Domain Monaural Speech Separation SPMamba: State-space model is all you need in speech separation

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-01T08:25:44.312937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T08:25:44.312937Z digest=sha256:cd2dfa98a030e064ec79b6ca447f1b03b195e3f60459c7103df9bc12ded7ac78