Paper Citation Record · LEDGER

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation

As of 14 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2412.18217.

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

pith.paper-citation-record.v1
2412.18217 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:58:49.171989Z

measured 31 of 31 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

verified exact0
verified fuzzy26
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 29b55b04-c6d1-4133-ada5-98dafe391cfc · outbound

This paper cites Whamr!: Noisy and reverberant single-channel speech separation,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Whamr!: Noisy and reverberant single-channel speech separation,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.603309Z

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.

Observation 4ddfb354-f889-4b91-a158-abfca9b0f809 · outbound

This paper cites Emotion awareness in multi-utterance turn for improving emotion prediction in multi-speaker conversation,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Emotion awareness in multi-utterance turn for improving emotion prediction in multi-speaker conversation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.591399Z

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.

Observation d7397c3e-6b2b-454c-80df-aa487ae586ef · outbound

This paper cites A separation priority pipeline for single-channel speech separation in noisy environments,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation A separation priority pipeline for single-channel speech separation in noisy environments,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.581553Z

Source-reported events for the cited work

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Observation 0580a019-1d59-4541-8b65-c1f0c55dde8d · outbound

This paper cites Uformer: A unet based dilated complex & real dual-path conformer network for simultaneous speech enhancement and dereverberation,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Uformer: A unet based dilated complex & real dual-path conformer network for simultaneous speech enhancement and dereverberation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.572295Z

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Observation 27edc90b-6111-43c0-a7ab-4ca591ee2738 · outbound

This paper cites Spec- trograms fusion with minimum difference masks esti- mation for monaural speech dereverberation,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Spec- trograms fusion with minimum difference masks esti- mation for monaural speech dereverberation,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.562692Z

Source-reported events for the cited work

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Observation 039a4e52-b506-4b2c-92d9-62348b343ed0 · outbound

This paper cites Multi-level knowledge distillation for speech emotion recognition in noisy con- ditions,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Multi-level knowledge distillation for speech emotion recognition in noisy con- ditions,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.552849Z

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.

Observation 695b1f98-4e85-49e9-aa7c-e7a1f60b0c0c · outbound

This paper cites Mul- titalker speech separation with utterance-level permu- tation invariant training of deep recurrent neural net- works,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Mul- titalker speech separation with utterance-level permu- tation invariant training of deep recurrent neural net- works,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.542556Z

Source-reported events for the cited work

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Observation df986683-fb63-41fd-9857-55243ada5c52 · outbound

This paper cites Dccrn: Deep complex convolution recurrent network for phase-aware speech enhancement,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Dccrn: Deep complex convolution recurrent network for phase-aware speech enhancement,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.531789Z

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.

Observation f8f863a2-4914-487c-8d27-fb8134de2f76 · outbound

This paper cites Diffusion- based speech enhancement with joint generative and predictive decoders,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Diffusion- based speech enhancement with joint generative and predictive decoders,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T04:58:49.084096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6a5dd98-01e1-4d52-ba37-c4b7e6836a54 · outbound

This paper cites Waveform- domain speech enhancement using spectrogram encod- ing for robust speech recognition,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Waveform- domain speech enhancement using spectrogram encod- ing for robust speech recognition,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.520098Z

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.

Observation 2b7e9cd5-5295-4db4-9118-cccc7e2fa7c1 · outbound

This paper cites Dual-path rnn: Ef- ficient long sequence modeling for time-domain single- channel speech separation,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Dual-path rnn: Ef- ficient long sequence modeling for time-domain single- channel speech separation,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.509049Z

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.

Observation 40beaf00-6bd3-491d-b45d-0a3c5ba99b15 · outbound

This paper cites Target speaker extraction with curriculum learning,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Target speaker extraction with curriculum learning,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.495872Z

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.

Observation 696a5545-bac1-4d37-ac0f-09c02aa60237 · outbound

This paper cites A restriction training recipe for speech separation on sparsely mixed speech,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation A restriction training recipe for speech separation on sparsely mixed speech,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.482364Z

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.

Observation 1be4374c-963d-4b97-aae0-e3f67c08de4f · outbound

This paper cites Attention is all you need in speech separation,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Attention is all you need in speech separation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.470968Z

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.

Observation e5bfd4f2-4cdc-4844-b765-903da2429015 · outbound

This paper cites Conv-TasNet: Surpassing ideal time–frequency magnitude masking for speech separation,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Conv-TasNet: Surpassing ideal time–frequency magnitude masking for speech separation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.460396Z

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.

Observation 5693ca49-d70e-4c45-888d-616ca2afbcf5 · outbound

This paper cites Attention is all you need,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Attention is all you need,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.449341Z

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.

Observation 3aad59f5-f154-4a9d-ae5e-3646b0c7cfc3 · outbound

This paper cites U-net: Convo- lutional networks for biomedical image segmentation,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation U-net: Convo- lutional networks for biomedical image segmentation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.439421Z

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.

Observation 374c5864-3d0a-40d4-b082-bfcd749e2213 · outbound

This paper cites Demucs: Deep Extractor for Music Sources with extra unlabeled data remixed.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Demucs: Deep Extractor for Music Sources with extra unlabeled data remixed

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T04:58:49.122903Z

Source-reported events for the cited work

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Observation 94c66dc6-2136-440a-844c-a9134927d97a · outbound

This paper cites Sudo rm -rf: Efficient networks for universal audio source separa- tion,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Sudo rm -rf: Efficient networks for universal audio source separa- tion,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.429495Z

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.

Observation db9bcbb5-99db-4d94-87c2-1e5c03d96c5d · outbound

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

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T04:58:49.131402Z

Source-reported events for the cited work

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Observation 32c7b4c1-b7de-406a-a8d0-fd57eff928b7 · outbound

This paper cites How to Train Your HiPPO: State Space Models with Generalized Orthogonal Basis Projections.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation How to Train Your HiPPO: State Space Models with Generalized Orthogonal Basis Projections

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T04:58:49.135961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71130e78-78ce-4224-8ce7-d6abf9fa1eb9 · outbound

This paper cites Cosentino, M.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Cosentino, M

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.419488Z

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.

Observation fa74c730-e6a9-4e0a-840d-7f9cc4012c6e · outbound

This paper cites Us- ing semi-supervised learning for monaural time-domain speech separation with a self-supervised learning-based si-snr estimator,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Us- ing semi-supervised learning for monaural time-domain speech separation with a self-supervised learning-based si-snr estimator,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.409502Z

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.

Observation 11c6caf7-d88e-4617-884c-9cb45fd03935 · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Efficiently Modeling Long Sequences with Structured State Spaces

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T04:58:49.149015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5edfb777-f3ea-4c49-9f5b-3c9bce40273e · outbound

This paper cites WHAM!: Extending speech separation to noisy environments,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation WHAM!: Extending speech separation to noisy environments,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.397955Z

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.

Observation 0d587faa-9dc0-4f04-a346-14a068b4ab69 · outbound

This paper cites Pyrooma- coustics: A python package for audio room simulation and array processing algorithms,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Pyrooma- coustics: A python package for audio room simulation and array processing algorithms,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.385932Z

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.

Observation b917c0c1-1e0a-4807-9dba-052cd985ea29 · outbound

This paper cites SDR–half-baked or well done?.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation SDR–half-baked or well done?

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.374015Z

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.

Observation 215aca2f-9bff-4802-81de-2941aac406a0 · outbound

This paper cites Performance measurement in blind audio source separation,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Performance measurement in blind audio source separation,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.363399Z

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.

Observation 752d6c02-285e-4045-8e1e-55ac5d0e1cf7 · outbound

This paper cites Perceptual evaluation of speech quality (pesq)-a new method for speech quality assessment of telephone networks and codecs,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Perceptual evaluation of speech quality (pesq)-a new method for speech quality assessment of telephone networks and codecs,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.352060Z

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.

Observation 55b04ccb-65a5-40d4-b6e6-6142f54ca0ab · outbound

This paper cites Evaluation of objective quality measures for speech enhancement,.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Evaluation of objective quality measures for speech enhancement,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.340151Z

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.

Observation ef5068bc-9f07-44d4-a468-92fbd733ead4 · outbound

This paper cites Ptflops: A flops counting tool for neu- ral networks in pytorch framework.

U-Mamba-Net: A highly efficient Mamba-based U-net style network for noisy and reverberant speech separation Ptflops: A flops counting tool for neu- ral networks in pytorch framework

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:58:49.328234Z

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.

Pith citing papers

No inbound Pith citation observations are available.