Paper Citation Record · LEDGER

Dynamic Slimmable Networks for Efficient Speech Separation

As of 18 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2507.06179.

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

pith.paper-citation-record.v1
2507.06179 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:14:05.811097Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

38 of 38 outbound references displayed

verified exact0
verified fuzzy35
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 16c201a0-212a-48de-ae04-d33dbce20381 · outbound

This paper cites A regression approach to speech enhancement based on deep neural networks,.

Dynamic Slimmable Networks for Efficient Speech Separation A regression approach to speech enhancement based on deep neural networks,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:13.274383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5ec36cb0-0f06-48bd-ae30-ae5358a11a1b · outbound

This paper cites Sixty years of frequency-domain monaural speech enhancement: From traditional to deep learning methods,.

Dynamic Slimmable Networks for Efficient Speech Separation Sixty years of frequency-domain monaural speech enhancement: From traditional to deep learning methods,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:13.112250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c357305d-56c6-430e-a307-1816b0b98f68 · outbound

This paper cites Speech recognition using deep neural networks: A systematic review,.

Dynamic Slimmable Networks for Efficient Speech Separation Speech recognition using deep neural networks: A systematic review,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:12.846837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c0512a17-b772-4755-9932-a4ce8c239ec3 · outbound

This paper cites End-to-end speech recognition: A survey,.

Dynamic Slimmable Networks for Efficient Speech Separation End-to-end speech recognition: A survey,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:12.652945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3cb3cabf-1cd7-41c9-8a6b-f1a12974126f · outbound

This paper cites Deep spoken keyword spotting: An overview,.

Dynamic Slimmable Networks for Efficient Speech Separation Deep spoken keyword spotting: An overview,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:12.386351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 298a08d1-8611-49d2-a5f9-bf2af5f46598 · outbound

This paper cites Supervised speech separation based on deep learning: An overview,.

Dynamic Slimmable Networks for Efficient Speech Separation Supervised speech separation based on deep learning: An overview,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:12.177014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e6a55cc5-d695-4199-8d54-4773c093a42a · outbound

This paper cites Dual-path RNN: Efficient long sequence modeling for time-domain single-channel speech separation,.

Dynamic Slimmable Networks for Efficient Speech Separation Dual-path RNN: Efficient long sequence modeling for time-domain single-channel speech separation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:12.034628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f19758fd-ae83-4ea4-bfca-340d0d503d27 · outbound

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

Dynamic Slimmable Networks for Efficient Speech Separation Attention is all you need in speech separation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:11.810956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ae79ab4e-6d61-4a19-8dc2-80ed1fdc75d8 · outbound

This paper cites Exploring self-attention mechanisms for speech separation,.

Dynamic Slimmable Networks for Efficient Speech Separation Exploring self-attention mechanisms for speech separation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:11.595705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b727e693-4428-4af1-8f81-079e0a33b1ce · outbound

This paper cites TF-GridNet: Integrating full- and sub-band modeling for speech sep- aration,.

Dynamic Slimmable Networks for Efficient Speech Separation TF-GridNet: Integrating full- and sub-band modeling for speech sep- aration,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:11.389679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c96310a0-7d30-4c1f-99d1-89178410e053 · outbound

This paper cites Speaker counting and separation from single-channel noisy mixtures,.

Dynamic Slimmable Networks for Efficient Speech Separation Speaker counting and separation from single-channel noisy mixtures,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:11.167203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ce925b1e-8a81-4058-b6e6-39af15113346 · outbound

This paper cites Dynamic neural networks: A survey,.

Dynamic Slimmable Networks for Efficient Speech Separation Dynamic neural networks: A survey,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:10.937740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2e78f75c-e93a-4c07-a96a-e222fa99d15a · outbound

This paper cites Adaptive mixtures of local experts,.

Dynamic Slimmable Networks for Efficient Speech Separation Adaptive mixtures of local experts,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:10.743410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f91c3b76-d265-4e73-837d-74d0cc695464 · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,.

Dynamic Slimmable Networks for Efficient Speech Separation Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:10.550335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 363d39fc-6c25-498b-aabe-244e6b1a15f9 · outbound

This paper cites SpeechMoE: Scaling to large acoustic models with dynamic routing mixture of experts,.

Dynamic Slimmable Networks for Efficient Speech Separation SpeechMoE: Scaling to large acoustic models with dynamic routing mixture of experts,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:10.295984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e883d7f3-5457-44fe-91e2-87b259f5f653 · outbound

This paper cites Adaptive neural networks for efficient inference,.

Dynamic Slimmable Networks for Efficient Speech Separation Adaptive neural networks for efficient inference,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:10.106158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 97a17ab3-2cc4-4fc3-8ebb-a4aa86ebe134 · outbound

This paper cites SkipNet: Learning dynamic routing in convolutional networks,.

Dynamic Slimmable Networks for Efficient Speech Separation SkipNet: Learning dynamic routing in convolutional networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:09.917500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b18e352d-ac2c-4520-aa44-8d6488e6f887 · outbound

This paper cites Skip RNN: Learning to skip state updates in recurrent neural networks,.

Dynamic Slimmable Networks for Efficient Speech Separation Skip RNN: Learning to skip state updates in recurrent neural networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:09.712472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e740ba8e-15a2-4b3f-b337-f1a0c14d990a · outbound

This paper cites Dynamic slimmable network,.

Dynamic Slimmable Networks for Efficient Speech Separation Dynamic slimmable network,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:09.547749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ae5706b4-781e-4e46-ad04-45205ea563f0 · outbound

This paper cites You look twice: GaterNet for dynamic filter selection in CNNs,.

Dynamic Slimmable Networks for Efficient Speech Separation You look twice: GaterNet for dynamic filter selection in CNNs,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:09.285972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 758ac4c0-7c1e-47b7-b314-fd6d56b278a6 · outbound

This paper cites Channel gating neural networks,.

Dynamic Slimmable Networks for Efficient Speech Separation Channel gating neural networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:09.093154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9a7cdf01-0836-4326-88e3-808dd3edbc07 · outbound

This paper cites Deep clustering: Discriminative embeddings for segmentation and separation,.

Dynamic Slimmable Networks for Efficient Speech Separation Deep clustering: Discriminative embeddings for segmentation and separation,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:08.857434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bb92bfd9-214d-4cdc-aaea-8fc827acbf2a · outbound

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

Dynamic Slimmable Networks for Efficient Speech Separation WHAM!: Extending speech separation to noisy environments,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:08.673487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e92ba4b2-58ad-4d40-8103-9a42005f1af3 · outbound

This paper cites Don’t shoot butterfly with rifles: Multi-channel continuous speech separation with early exit transformer,.

Dynamic Slimmable Networks for Efficient Speech Separation Don’t shoot butterfly with rifles: Multi-channel continuous speech separation with early exit transformer,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:08.456315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4f2761b4-1ce7-4cce-b9ea-5bcab0c32505 · outbound

This paper cites Latent iterative refinement for modular source separation,.

Dynamic Slimmable Networks for Efficient Speech Separation Latent iterative refinement for modular source separation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:08.269151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cb823223-d4f6-4b1a-8058-d23fa732195f · outbound

This paper cites Inference skipping for more efficient real-time speech enhancement with parallel RNNs,.

Dynamic Slimmable Networks for Efficient Speech Separation Inference skipping for more efficient real-time speech enhancement with parallel RNNs,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:08.047661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ee830dbf-4d97-410e-8b31-98d7b577ade8 · outbound

This paper cites Scalable speech enhancement with dynamic channel pruning,.

Dynamic Slimmable Networks for Efficient Speech Separation Scalable speech enhancement with dynamic channel pruning,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:07.870522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation acf98eed-e56f-4354-a04f-ae57b6941fa8 · outbound

This paper cites Slim-TasNet: A slimmable neural network for speech separation,.

Dynamic Slimmable Networks for Efficient Speech Separation Slim-TasNet: A slimmable neural network for speech separation,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:07.603366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d3ab0b18-6cb6-4dcd-80b7-9250dc14dc92 · outbound

This paper cites Dynamic slimmable network for speech separation,.

Dynamic Slimmable Networks for Efficient Speech Separation Dynamic slimmable network for speech separation,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:07.422111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation adbc6cfe-7a7d-491a-be13-e45f5010585d · outbound

This paper cites Categorical reparameterization with gumbel-softmax,.

Dynamic Slimmable Networks for Efficient Speech Separation Categorical reparameterization with gumbel-softmax,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:07.247173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ee5b6338-e68d-4947-b8f7-6ecd621f9e25 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

Dynamic Slimmable Networks for Efficient Speech Separation Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T19:14:05.137608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb33add5-a4b8-4839-a8df-8fc741d45659 · outbound

This paper cites Attention is all you need,.

Dynamic Slimmable Networks for Efficient Speech Separation Attention is all you need,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:07.085692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e9d79cca-80b7-4b3b-8734-a4888af34419 · outbound

This paper cites MoH: Multi-head attention as mixture-of-head attention,.

Dynamic Slimmable Networks for Efficient Speech Separation MoH: Multi-head attention as mixture-of-head attention,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T19:14:05.342325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77dcbd52-0283-4c4f-ba01-7313d62576a1 · outbound

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

Dynamic Slimmable Networks for Efficient Speech Separation SDR–half- baked or well done?

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:06.880556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 459d1528-dda6-469b-9c1e-811fa4b0b42d · outbound

This paper cites Multitalker speech separation with utterance-level permutation invariant training of deep recurrent neural networks,.

Dynamic Slimmable Networks for Efficient Speech Separation Multitalker speech separation with utterance-level permutation invariant training of deep recurrent neural networks,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:06.625376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9b1b952f-3d30-49b1-a88f-382fb38b544e · outbound

This paper cites SpeechBrain: A General-Purpose Speech Toolkit.

Dynamic Slimmable Networks for Efficient Speech Separation SpeechBrain: A General-Purpose Speech Toolkit

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T19:14:05.621489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0317a6b-f148-4aea-97c7-a5ef6e92ab37 · outbound

This paper cites Adam: A method for stochastic optimization,.

Dynamic Slimmable Networks for Efficient Speech Separation Adam: A method for stochastic optimization,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:06.381506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 99d4f398-b4b2-47ee-a529-ccebe6aaf855 · outbound

This paper cites Analysis of overlaps in meetings by dialog factors, hot spots, speakers, and collection site: Insights for automatic speech recognition,.

Dynamic Slimmable Networks for Efficient Speech Separation Analysis of overlaps in meetings by dialog factors, hot spots, speakers, and collection site: Insights for automatic speech recognition,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:14:06.184462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.