Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T13:49:09.756824Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 2 inbound Pith citation observations for arXiv:2509.00318.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T13:49:09.756824Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
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A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-15T07:39:50.334622Z
75 of 75 outbound references displayed
External citation measurements
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Observation afe1ebf0-504e-4381-b9ab-cbdaad4d3308 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning M., Lostanlen, V., Cramer, A., Salamon, J., Dokter, A., Kelling, S., Bello, J
Reference 1
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning V., Advancing bird classification: Harnessing PSA-DenseNet for call-based recognition, In: Ta, T.V., Nguyen, L.T.H
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
Reference 3
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
Reference 4
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Autoregressive Diffusion Models
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Observation e7a8e61c-bdf2-42cf-b930-41fe2a39b3d4 · outbound
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Reference 8
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning S., Ma, J., Thomas, M
Reference 10
Source-reported events for the cited work
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Observation 7244515b-20ed-4602-971f-2c94da8b616e · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning 13136–13140
Reference 11
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Observation 082983f5-54c3-465f-ba66-dd5c966e67a9 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
Reference 12
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Vision Transformer Segmentation for Visual Bird Sound Denoising
Reference 13
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Observation e2e08210-fd2f-42c6-b013-b65817a90bc1 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning and Li, J., BirdSoundsDenoising: Deep Visual Audio Denoising for Bird Sounds, Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) , (2023), pp
Reference 14
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
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Reference 16
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
Reference 17
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Deep Learning for Automated Identification of Vietnamese Timber Species: A Tool for Ecological Monitoring and Conservation
Reference 18
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Qi and T
Reference 19
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Quantifying Fish School Fragmentation under Predation Using Stochastic Differential Equations
Reference 20
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning T., Casse, T., Ta, T
Reference 22
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning D., Nguyen, L
Reference 24
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning V., Nguyen, L
Reference 27
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Observation 0fbf840f-60f8-4a4f-804d-b802c2adafcc · outbound
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning V., Yamamoto, Y., Yagi, A
Reference 29
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning V., Yagi, A., Yamamoto, Y
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Reference 31
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Reference 38
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning V., Yamamoto, Y., Nguyen, D
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Reference 47
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Reference 50
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning D., Ta, T
Reference 51
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
Reference 52
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Mathematical Models for Fish Schooling
Reference 53
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Existence and stability of periodic solutions of a Lotka-Volterra system
Reference 54
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning V., Nguyen, L
Reference 55
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning DiffWave: A Versatile Diffusion Model for Audio Synthesis
Reference 56
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Observation 9198d8d3-a8ec-4cb0-ba95-03d53b9f0c4c · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning WaveNet: A Generative Model for Raw Audio
Reference 57
Source-reported events for the cited work
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Observation edbd0e94-41d2-4576-99c8-606a1293a808 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning F., Suppression of acoustic noise in speech using spectral subtraction, IEEE Transactions on Acoustics, Speech, and Signal Processing , 27(2):113–120, 1979
Reference 58
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Reference 59
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Reference 60
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
Reference 61
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Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
Reference 62
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Observation 428f9a48-806a-467f-95e1-1cbec30e38d1 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Fr\'echet Audio Distance: A Metric for Evaluating Music Enhancement Algorithms
Reference 63
Source-reported events for the cited work
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Observation 1eb96883-51d1-41c5-b02a-c6d44140636f · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Jr, and Matsuyama, Y., Distortion Measures for Speech Processing, IEEE Transactions on Acoustics, Speech, and Signal Processing, 28:367–376, (1980)
Reference 64
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Observation 66a1d689-9b36-4382-806f-b971ae206114 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
Reference 65
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Observation 45c7ae68-0026-4508-865d-b9d2d4fe39cc · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning L., Pardo, J
Reference 66
Source-reported events for the cited work
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Observation 3eb4d0e4-ac4c-4580-b941-32403fbed552 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning and Weiss, Y., On GANs and GMMs, Advances in Neural Information Processing Systems (NeurIPS) , vol
Reference 67
Source-reported events for the cited work
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Observation 75e57f4f-84b8-404e-a8d3-bca310a9d20d · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning NatureLM-audio: an Audio-Language Foundation Model for Bioacoustics
Reference 68
Source-reported events for the cited work
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Observation 8a47e175-854b-429c-bc4b-4cfac21e5621 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
Reference 69
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Observation 15eabd26-030f-4bb7-a997-d0e2e06e4762 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning and Marro, C
Reference 70
Source-reported events for the cited work
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Observation 3554eb02-5379-4cc7-b154-76cbe995914f · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning D., Acoustic Scene Generation with Conditional SampleRNN, Proceedings of the IEEE Inter- national Conference on Acoustics, Speech and Signal Processing (ICASSP) , pp
Reference 71
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Observation 8d81f0ca-0953-48a9-b4f5-6cef9b698417 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
Reference 72
Source-reported events for the cited work
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Observation c45c2547-0f41-4874-bfc9-2a8062790480 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
Reference 73
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.
Observation 3cd1982f-beb1-4052-b919-6ebc5a447016 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
Reference 74
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.
Observation da05e744-94bc-47d5-8866-4a1957a33bf1 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Unresolved cited work
Reference 75
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.
Observation a076fa3e-fa0e-4382-a341-30ffbf960c35 · outbound
Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning Springer, Singapore
Reference 2023
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.
Observation ee2444ff-4eca-42b4-8d04-9fd7c41764da · inbound
BioSEN: A Bio-acoustic Signal Enhancement Network for Animal Vocalizations Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning
Reference 11
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.
Observation 2b9d53ee-e684-4c1b-bacd-5ad0e0967d5d · inbound
BioSEN: A Bio-acoustic Signal Enhancement Network for Animal Vocalizations Towards High-Fidelity and Controllable Bioacoustic Generation via Enhanced Diffusion Learning
Reference 11
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.