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Paper Citation Record · LEDGER

Efficient Text-to-Audio Generation via Pruning

As of 10 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2607.13330.

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

pith.paper-citation-record.v1
2607.13330 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T05:32:41.533152Z

measured 26 of 26 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

26 of 26 outbound references displayed

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Outbound references

Observation 9c68a6f8-c8be-4846-a8d3-3b109e712250 · outbound

This paper cites Make-an-audio: Text-to-audio generation with prompt- enhanced diffusion models,.

Efficient Text-to-Audio Generation via Pruning Make-an-audio: Text-to-audio generation with prompt- enhanced diffusion models,

Reference 1

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Observation 6b131067-16fe-43bd-bf57-a5c1f074cde1 · outbound

This paper cites AudioLDM: Text-to-audio generation with latent diffusion models,.

Efficient Text-to-Audio Generation via Pruning AudioLDM: Text-to-audio generation with latent diffusion models,

Reference 2

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Observation a812b58f-21fb-4e41-9679-ca5a9d1e6e3e · outbound

This paper cites DreamAudio: Customized text-to-audio generation with diffusion models,.

Efficient Text-to-Audio Generation via Pruning DreamAudio: Customized text-to-audio generation with diffusion models,

Reference 3

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Observation d2a51c39-e09a-436c-afca-081942a9df1b · outbound

This paper cites Efficient diffusion models: A comprehensive survey from principles to practices,.

Efficient Text-to-Audio Generation via Pruning Efficient diffusion models: A comprehensive survey from principles to practices,

Reference 4

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Observation e9426c50-c5fe-476a-ad49-9623f29106bb · outbound

This paper cites Diffsound: Discrete diffusion model for text-to-sound generation,.

Efficient Text-to-Audio Generation via Pruning Diffsound: Discrete diffusion model for text-to-sound generation,

Reference 5

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Observation c373037a-3b8d-4182-a507-af97aa91867a · outbound

This paper cites Come-closer-diffuse-faster: Accelerating conditional diffusion models for inverse problems through stochastic contraction,.

Efficient Text-to-Audio Generation via Pruning Come-closer-diffuse-faster: Accelerating conditional diffusion models for inverse problems through stochastic contraction,

Reference 6

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Observation 00d4664a-bdbb-42cf-99b7-eb8ff9663e69 · outbound

This paper cites Diffwave: A versatile diffusion model for audio synthesis,.

Efficient Text-to-Audio Generation via Pruning Diffwave: A versatile diffusion model for audio synthesis,

Reference 7

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source=pdf_text observed=2026-08-02T05:32:40.155730Z digest=sha256:fa8d1e7e7a3d62d09cd6ee8341ff2b039a47cb3e3b44eda8df3221eac9f00c3e

Observation f0d7262a-b665-4119-87f2-b525aaa79faf · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Efficient Text-to-Audio Generation via Pruning Distilling the Knowledge in a Neural Network

Reference 8

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source=pdf_text observed=2026-08-02T05:32:40.265579Z digest=sha256:cbc6e94d1d17786f6959b4f32586bb45a7c7238ab5e94721e02ce53b52332787

Observation 21d5cf5a-a7b6-4037-be04-b1e3cb4f158d · outbound

This paper cites Progressive distillation for fast sampling of diffu- sion models,.

Efficient Text-to-Audio Generation via Pruning Progressive distillation for fast sampling of diffu- sion models,

Reference 9

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Observation 3aa8b987-678e-4953-80f9-ea59ac84eb85 · outbound

This paper cites SoundLoCD: An efficient conditional discrete contrastive latent diffusion model for text-to-sound generation,.

Efficient Text-to-Audio Generation via Pruning SoundLoCD: An efficient conditional discrete contrastive latent diffusion model for text-to-sound generation,

Reference 10

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source=pdf_text observed=2026-08-02T05:32:40.411074Z digest=sha256:9d9e7346528fd5b3b66158f017001c9043af01f04a329d7168b34252689d4323

Observation 92ba6a72-3a45-4dad-9eb8-2105fe62ca7c · outbound

This paper cites Structured pruning for deep convolutional neural networks: A survey,.

Efficient Text-to-Audio Generation via Pruning Structured pruning for deep convolutional neural networks: A survey,

Reference 11

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source=pdf_text observed=2026-08-02T05:32:40.476534Z digest=sha256:f8a7dd313d6bba5cd2809147f35a3c773d51866f2659cf2aac383681bedbdca1

Observation a215ec4c-d234-4243-a49d-4fec537f07f6 · outbound

This paper cites Efficient CNNs via passive filter pruning,.

Efficient Text-to-Audio Generation via Pruning Efficient CNNs via passive filter pruning,

Reference 12

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source=pdf_text observed=2026-08-02T05:32:40.554824Z digest=sha256:506b418be7782d920b3a9d67e4eb26912c61af027592daab6a47cc3709124565

Observation 7040d16a-9e5f-40c1-9b67-1c91fc6c66ae · outbound

This paper cites Ld-pruner: Efficient pruning of latent diffusion models using task-agnostic insights,.

Efficient Text-to-Audio Generation via Pruning Ld-pruner: Efficient pruning of latent diffusion models using task-agnostic insights,

Reference 13

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source=pdf_text observed=2026-08-02T05:32:40.635940Z digest=sha256:8757888ec938b16c81274d665ffa0aba0a7f3b8bf31f80d1135c3c976ddf5ca2

Observation 26b8a9fc-2bb6-4689-8ee3-ad6a6b30dc5d · outbound

This paper cites LAPTOP-Diff: Layer Pruning and Normalized Distillation for Compressing Diffusion Models.

Efficient Text-to-Audio Generation via Pruning LAPTOP-Diff: Layer Pruning and Normalized Distillation for Compressing Diffusion Models

Reference 14

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Observation 9b899b96-3d38-49a3-bcfc-eac333d11230 · outbound

This paper cites Layermerge: Neural network depth compression through layer pruning and merging,.

Efficient Text-to-Audio Generation via Pruning Layermerge: Neural network depth compression through layer pruning and merging,

Reference 15

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source=pdf_text observed=2026-08-02T05:32:40.817718Z digest=sha256:fef48bedab55f402735b0aabe1027cc9a8ccd99540a030d4edc5f6abeaf482bf

Observation ff7b44b9-6412-4f15-a3c9-3a67d9b7e655 · outbound

This paper cites Structural pruning for diffusion models,.

Efficient Text-to-Audio Generation via Pruning Structural pruning for diffusion models,

Reference 16

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Observation dbebb7f6-f257-4f61-b2e6-4ebd28cd30ad · outbound

This paper cites Using feature entropy to guide filter pruning for efficient convolutional networks,.

Efficient Text-to-Audio Generation via Pruning Using feature entropy to guide filter pruning for efficient convolutional networks,

Reference 17

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source=pdf_text observed=2026-08-02T05:32:40.928546Z digest=sha256:084e1cc8019540677f8bd6b13a586372feaf89a13d684bd1a33a3da463fc1837

Observation 1d57ec41-53ee-49c2-b26f-771310c57141 · outbound

This paper cites HRank: Filter pruning using high-rank feature map,.

Efficient Text-to-Audio Generation via Pruning HRank: Filter pruning using high-rank feature map,

Reference 18

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source=pdf_text observed=2026-08-02T05:32:41.015504Z digest=sha256:b28fa7e2c3a7c7c1422ebf0009be5f26ff5c1dfa8733335f8037bc2c78868163

Observation 998db8c8-2221-4255-bb77-7fd0857c2aad · outbound

This paper cites EZCrop: Energy- zoned channels for robust output pruning,.

Efficient Text-to-Audio Generation via Pruning EZCrop: Energy- zoned channels for robust output pruning,

Reference 19

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Observation b714e89c-e69a-470a-8a45-b2af39dbdc8b · outbound

This paper cites Pruning filters for efficient ConvNets,.

Efficient Text-to-Audio Generation via Pruning Pruning filters for efficient ConvNets,

Reference 20

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Observation 4599b153-5169-43b1-ae97-61f59afc398c · outbound

This paper cites Compressing audio cnns with graph centrality based filter pruning,.

Efficient Text-to-Audio Generation via Pruning Compressing audio cnns with graph centrality based filter pruning,

Reference 21

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Observation fd6766a3-a2b0-4e44-8377-353b0436b56d · outbound

This paper cites Audiocaps: Generating captions for audios in the wild,.

Efficient Text-to-Audio Generation via Pruning Audiocaps: Generating captions for audios in the wild,

Reference 22

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Observation 3a7e686b-f4e3-41cd-96e5-c2a3d89770ad · outbound

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

Efficient Text-to-Audio Generation via Pruning Audio set: An ontology and human- labeled dataset for audio events,

Reference 23

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Observation 6c63dd82-4e28-4882-8ed9-21601106bb7b · outbound

This paper cites AudioGen: Textually Guided Audio Generation.

Efficient Text-to-Audio Generation via Pruning AudioGen: Textually Guided Audio Generation

Reference 24

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source=pdf_text observed=2026-08-02T05:32:41.406290Z digest=sha256:ea6ba1e47f4fc13eb3bf8533c36866c3810bff67c88e541706dde7bf34e1ea2c

Observation 9431b0c7-8d3a-4319-a451-5cc31c9e30d8 · outbound

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

Efficient Text-to-Audio Generation via Pruning Audioldm 2: Learning holistic audio generation with self-supervised pretraining,

Reference 25

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Observation f8b9d57c-f772-4929-a2fc-955a96b2a16c · outbound

This paper cites PANNs: Large-scale pretrained audio neural networks for audio pattern recognition,.

Efficient Text-to-Audio Generation via Pruning PANNs: Large-scale pretrained audio neural networks for audio pattern recognition,

Reference 26

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