TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation | Paper Citation Record

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TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Unresolved cited work

Reference 1

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TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Unresolved cited work

Reference 2

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This paper cites Generative novel view synthesis with 3d-aware diffusion models.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Generative novel view synthesis with 3d-aware diffusion models

Reference 3

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This paper cites Hierarchical integration diffusion model for realistic image deblurring.Advances in neural information processing systems, 36, 2024.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Hierarchical integration diffusion model for realistic image deblurring.Advances in neural information processing systems, 36, 2024

Reference 4

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This paper cites Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images

Reference 5

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This paper cites Diffusion models beat gans on image synthesis.Advances in neural informa- tion processing systems, 34:8780–8794, 2021.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Diffusion models beat gans on image synthesis.Advances in neural informa- tion processing systems, 34:8780–8794, 2021

Reference 6

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This paper cites Phylogeny, taxonomy and nomenclature: The problem of taxonomic categories and of nomenclatural ranks.Zootaxa, 1519:27–68, 2007.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Phylogeny, taxonomy and nomenclature: The problem of taxonomic categories and of nomenclatural ranks.Zootaxa, 1519:27–68, 2007

Reference 7

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This paper cites Make-a-scene: Scene- based text-to-image generation with human priors.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Make-a-scene: Scene- based text-to-image generation with human priors

Reference 8

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This paper cites A step towards worldwide biodiversity assessment: The bioscan-1m insect dataset.Advances in Neural Information Processing Systems, 36, 2024.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation A step towards worldwide biodiversity assessment: The bioscan-1m insect dataset.Advances in Neural Information Processing Systems, 36, 2024

Reference 9

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This paper cites Generative adversarial nets.Advances in neural information processing systems, 27, 2014.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Generative adversarial nets.Advances in neural information processing systems, 27, 2014

Reference 10

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This paper cites Highly Personalized Text Embedding for Image Manipulation by Stable Diffusion.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Highly Personalized Text Embedding for Image Manipulation by Stable Diffusion

Reference 11

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This paper cites Classifier-free diffusion guidance.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Classifier-free diffusion guidance

Reference 12

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This paper cites Classifier-Free Diffusion Guidance.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Classifier-Free Diffusion Guidance

Reference 13

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This paper cites Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 14

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This paper cites Barik, Les Christidis, Stephen T.Garnett, Paul Kirk, Thomas M.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Barik, Les Christidis, Stephen T.Garnett, Paul Kirk, Thomas M

Reference 15

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This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation LoRA: Low-Rank Adaptation of Large Language Models

Reference 16

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This paper cites Diffusion Model-Based Image Editing: A Survey.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Diffusion Model-Based Image Editing: A Survey

Reference 17

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This paper cites Guiding a Diffusion Model with a Bad Version of Itself.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Guiding a Diffusion Model with a Bad Version of Itself

Reference 18

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Observation 73374414-dd5b-4946-9d80-2fafae93d686 · outbound

This paper cites Fishnet: A large-scale dataset and bench- mark for fish recognition, detection, and functional trait pre- diction.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Fishnet: A large-scale dataset and bench- mark for fish recognition, detection, and functional trait pre- diction

Reference 19

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Observation f3fa5b90-90b9-409f-943c-d809c0931bea · outbound

This paper cites Hierarchical conditioning of diffusion models using tree-of-life for study- ing species evolution.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Hierarchical conditioning of diffusion models using tree-of-life for study- ing species evolution

Reference 20

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This paper cites Diffu- sionclip: Text-guided diffusion models for robust image ma- nipulation.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Diffu- sionclip: Text-guided diffusion models for robust image ma- nipulation

Reference 21

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This paper cites Auto-Encoding Variational Bayes.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Auto-Encoding Variational Bayes

Reference 22

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This paper cites Controlnet++: Improving conditional controls with efficient consistency feedback.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Controlnet++: Improving conditional controls with efficient consistency feedback

Reference 23

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This paper cites Progressive generation of 3d point clouds with hierarchical consistency.Pattern Recognition, 136:109200, 2023.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Progressive generation of 3d point clouds with hierarchical consistency.Pattern Recognition, 136:109200, 2023

Reference 24

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Observation 81ad2d9b-73f7-4411-9573-8ef62b7028dc · outbound

This paper cites When stylegan meets stable diffusion: a w+ adapter for person- alized image generation.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation When stylegan meets stable diffusion: a w+ adapter for person- alized image generation

Reference 25

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Observation a09f6001-6e57-4d68-9b4b-b2d949bb23f4 · outbound

This paper cites Fine-grained Image Editing by Pixel-wise Guidance Using Diffusion Models.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Fine-grained Image Editing by Pixel-wise Guidance Using Diffusion Models

Reference 26

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This paper cites DetailCLIP: Detail-Oriented CLIP for Fine-Grained Tasks.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation DetailCLIP: Detail-Oriented CLIP for Fine-Grained Tasks

Reference 27

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This paper cites KnobGen: Controlling the Sophistication of Artwork in Sketch-Based Diffusion Models.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation KnobGen: Controlling the Sophistication of Artwork in Sketch-Based Diffusion Models

Reference 28

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Observation 68bce454-33ba-4552-9094-c1162d1992d1 · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 29

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Observation 60da0ce9-3d3f-4269-b799-9aeec43875e9 · outbound

This paper cites The integrative future of taxonomy.Fron- tiers in zoology, 7:1–14, 2010.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation The integrative future of taxonomy.Fron- tiers in zoology, 7:1–14, 2010

Reference 30

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This paper cites FineDiffusion: Scaling up Diffusion Models for Fine-grained Image Generation with 10,000 Classes.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation FineDiffusion: Scaling up Diffusion Models for Fine-grained Image Generation with 10,000 Classes

Reference 31

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This paper cites Precisecontrol: En- hancing text-to-image diffusion models with fine-grained at- tribute control.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Precisecontrol: En- hancing text-to-image diffusion models with fine-grained at- tribute control

Reference 32

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Observation 48ddff79-dc32-4ad3-961c-f592376ea8c2 · outbound

This paper cites Scalable diffusion models with transformers.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Scalable diffusion models with transformers

Reference 33

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This paper cites Hierarchical generation of human-object inter- actions with diffusion probabilistic models.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Hierarchical generation of human-object inter- actions with diffusion probabilistic models

Reference 34

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This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 35

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This paper cites Learning transferable visual models from natural language supervi- sion.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Learning transferable visual models from natural language supervi- sion

Reference 36

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This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 37

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This paper cites Gener- ating diverse high-fidelity images with vq-vae-2.Advances in neural information processing systems, 32, 2019.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Gener- ating diverse high-fidelity images with vq-vae-2.Advances in neural information processing systems, 32, 2019

Reference 38

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This paper cites High-resolution image synthesis with latent diffusion models.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation High-resolution image synthesis with latent diffusion models

Reference 39

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This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 40

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This paper cites Hyperdreambooth: Hypernetworks for fast personalization of text-to-image models.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Hyperdreambooth: Hypernetworks for fast personalization of text-to-image models

Reference 41

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Observation 4c0dde84-7755-455b-9e8c-7c4b31172d34 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494, 2022.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494, 2022

Reference 42

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This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.Advances in Neural In- formation Processing Systems, 35:25278–25294, 2022.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Laion-5b: An open large-scale dataset for training next generation image-text models.Advances in Neural In- formation Processing Systems, 35:25278–25294, 2022

Reference 43

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This paper cites pytorch-fid: FID Score for PyTorch.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation pytorch-fid: FID Score for PyTorch

Reference 44

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Observation 4a3e847d-8c52-4afe-a7c2-9e08330891b5 · outbound

This paper cites Bioclip: A vision foundation model for the tree of life.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Bioclip: A vision foundation model for the tree of life

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:00.598107Z

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Observation 2b7fc99f-dc9f-4095-8a6a-e9aee33a1fdf · outbound

This paper cites An em- pirical study and analysis of text-to-image generation us- ing large language model-powered textual representation.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation An em- pirical study and analysis of text-to-image generation us- ing large language model-powered textual representation

Reference 46

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Observation fa6e87ac-7456-428f-8aac-a89c9629e292 · outbound

This paper cites Nvae: A deep hierarchical vari- ational autoencoder.Advances in neural information pro- cessing systems, 33:19667–19679, 2020.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Nvae: A deep hierarchical vari- ational autoencoder.Advances in neural information pro- cessing systems, 33:19667–19679, 2020

Reference 47

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Observation bfe06961-4b6b-4a1f-a2b6-3453e890421a · outbound

This paper cites The inaturalist species classification and de- tection dataset.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation The inaturalist species classification and de- tection dataset

Reference 48

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This paper cites AnimateLCM: Computation-Efficient Personalized Style Video Generation without Personalized Video Data.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation AnimateLCM: Computation-Efficient Personalized Style Video Generation without Personalized Video Data

Reference 49

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Observation 6cdc67f5-a652-4e5f-83ff-e53bfbfaa7bb · outbound

This paper cites To- wards effective usage of human-centric priors in diffusion models for text-based human image generation.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation To- wards effective usage of human-centric priors in diffusion models for text-based human image generation

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:36:59.834491Z

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Observation 77d6a237-0034-4dac-9510-edfaa8ee5966 · outbound

This paper cites Fg-t2m: Fine-grained text-driven human motion generation via diffusion model.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Fg-t2m: Fine-grained text-driven human motion generation via diffusion model

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:36:59.627288Z

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Observation 0c7ee131-4a58-4baa-96f0-c0f50877b2f5 · outbound

This paper cites Generative hierarchical features from synthe- sizing images.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Generative hierarchical features from synthe- sizing images

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:36:59.490987Z

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Observation ee04e5e2-3976-49db-a93a-4b3105bf87d9 · outbound

This paper cites Fine-grained Appearance Transfer with Diffusion Models.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Fine-grained Appearance Transfer with Diffusion Models

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:36:58.258023Z

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Observation aa15b766-7e15-4850-b051-3ae81858739b · outbound

This paper cites ChatFace: Chat-Guided Real Face Editing via Diffusion Latent Space Manipulation.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation ChatFace: Chat-Guided Real Face Editing via Diffusion Latent Space Manipulation

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T11:36:57.289275Z

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Observation eebb3725-a2ef-4d85-83cd-e4fab5ac94a5 · outbound

This paper cites Dilightnet: Fine-grained light- ing control for diffusion-based image generation.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Dilightnet: Fine-grained light- ing control for diffusion-based image generation

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T11:36:57.385125Z

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Observation 382fbadf-221b-4fd3-b7af-036ddf5b948e · outbound

This paper cites Iti- gen: Inclusive text-to-image generation.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Iti- gen: Inclusive text-to-image generation

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:36:59.327896Z

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 5b28420e-63ae-443a-9ee9-84f73f7b758c · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Adding conditional control to text-to-image diffusion models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T11:36:57.559976Z

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Observation 257162d3-28a5-4930-91bb-02fe01cf2bc7 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation The unreasonable effectiveness of deep features as a perceptual metric

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T11:36:57.638014Z

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Observation f78c6f8c-4496-4d68-a2bd-410adc1cff37 · outbound

This paper cites A survey on personalized content synthesis with diffusion models.arXiv preprint arXiv:2405.05538, 2024.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation A survey on personalized content synthesis with diffusion models.arXiv preprint arXiv:2405.05538, 2024

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T11:36:57.712131Z

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Observation 03406c8c-a90d-48d4-b658-ef8a97c0e7bc · outbound

This paper cites Sine: Single image editing with text- to-image diffusion models.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Sine: Single image editing with text- to-image diffusion models

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:36:59.123577Z

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 f70c7982-f345-44d8-8953-93488afe168a · outbound

This paper cites Actinopteri.

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Actinopteri

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:36:58.978660Z

Source-reported events for the cited work

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