Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:44:55.718353Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 2 inbound Pith citation observations for arXiv:2505.21050.
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 2026-08-07T13:44:55.718353Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-21T18:21:15.831853Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T18:24:18.230169Z
47 of 47 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 9d0967d4-10d6-49bb-9848-68352730a11d · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Albergo and Eric Vanden-Eijnden
Reference 1
Source-reported events for the cited work
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Observation 45df56ea-7ce0-43e1-8f8d-79d3c141135e · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Flux.1 model family
Reference 2
Source-reported events for the cited work
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Observation dae2afd7-09f8-4dc9-90a7-63ee88430f72 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
Reference 3
Source-reported events for the cited work
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Observation 1dbd9c65-d7c8-4912-b36f-bf9507ebddc9 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Align your latents: High-resolution video synthe- sis with latent diffusion models
Reference 4
Source-reported events for the cited work
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Observation e5105872-45be-4d53-b5e0-be52da2b4bb5 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents 3D-Adapter: Geometry-Consistent Multi-View Diffusion for High-Quality 3D Generation
Reference 5
Source-reported events for the cited work
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Observation ec90664c-5485-415f-aaae-d599fe10e9e0 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Google scanned ob- jects: A high-quality dataset of 3d scanned household items
Reference 6
Source-reported events for the cited work
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Observation 3a4ca331-daca-4910-ba79-86f2c3b8ca37 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Scaling recti- fied flow transformers for high-resolution image synthe- sis
Reference 7
Source-reported events for the cited work
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Observation 3038ff2b-b83b-474e-9c7e-dd4924ff2ae4 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents DisEnvisioner: Disentangled and Enriched Visual Prompt for Customized Image Generation
Reference 8
Source-reported events for the cited work
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Observation 663a2a6a-235d-4991-940a-4d980609598d · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction
Reference 9
Source-reported events for the cited work
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Observation d5b36f40-b1bd-4df3-ab41-d9ac8ba90b9c · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Clipscore: A reference-free eval- uation metric for image captioning
Reference 10
Source-reported events for the cited work
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Observation dbcd3d9f-2f0b-4090-ace6-2df3c02d9058 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Denoising diffusion probabilistic models
Reference 11
Source-reported events for the cited work
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Observation 3102e8a4-30cd-4b1b-b08e-ea7de53394e7 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Kingma, Ben Poole, Mohammad Norouzi, David J
Reference 12
Source-reported events for the cited work
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Observation 8b3db147-6bc6-45e0-87a9-57b597bf4b62 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Video diffusion models
Reference 13
Source-reported events for the cited work
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Observation e85c2a46-1ce1-4720-9acd-8c8339b4c048 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents 3DTopia: Large Text-to-3D Generation Model with Hybrid Diffusion Priors
Reference 14
Source-reported events for the cited work
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Observation a5fbb2b7-ef31-4094-a858-10774c442ff2 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents LoRA: Low-rank adaptation of large language models
Reference 15
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Observation 761774e2-4dbf-490c-83b9-0e381b748d2c · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Mv- adapter: Multi-view consistent image generation made easy
Reference 16
Source-reported events for the cited work
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Observation b60267b7-d5cb-4d53-a81e-dce182b89044 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Elucidating the Design Space of Diffusion-Based Generative Models
Reference 17
Source-reported events for the cited work
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Observation 9800d0fd-556d-4033-b4a9-725b6cf0738d · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents 3d gaussian splatting for real-time radiance field rendering
Reference 18
Source-reported events for the cited work
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Observation b43a65d5-f38f-4ca4-bd93-4b43c3cd3fa1 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refiner
Reference 19
Source-reported events for the cited work
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Observation 66278dd6-f1c1-4fa6-ba7f-cfe9560fa176 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Triposg: High- fidelity 3d shape synthesis using large-scale rectified flow models
Reference 20
Source-reported events for the cited work
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Observation ba990e37-c957-49ab-91fc-adcb9ff51f73 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Kiss3dgen: Repurposing image dif- fusion models for 3d asset generation
Reference 21
Source-reported events for the cited work
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Observation 6279aff0-72a0-4524-b584-318c24dbcd49 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Unresolved cited work
Reference 22
Source-reported events for the cited work
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Observation 22e913ea-04b2-4fd7-912e-058026cfa0ec · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Flow straight and fast: Learning to generate and transfer data with rectified flow, 2022
Reference 23
Source-reported events for the cited work
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Observation e5fa586a-16d0-4fe4-bae0-40390d860601 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Text-guided texturing by synchronized multi- view diffusion
Reference 24
Source-reported events for the cited work
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Observation cfddbd3b-4b80-47fa-b1c0-4017d68aa283 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents MeshDiffusion: Score-based Generative 3D Mesh Modeling
Reference 25
Source-reported events for the cited work
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Observation 622a369a-d9b5-472e-bcb8-a24d6b676eee · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Wonder3d: Single image to 3d using cross-domain diffusion
Reference 26
Source-reported events for the cited work
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Observation eee18347-02da-4770-9d87-0814bb2376dc · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Unresolved cited work
Reference 27
Source-reported events for the cited work
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Observation 979c9861-5200-4709-a890-a90375b6f2b2 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents DSplats: 3D Generation by Denoising Splats-Based Multiview Diffusion Models
Reference 28
Source-reported events for the cited work
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Observation 21001367-0ddc-40ed-88ef-a933fe54bea1 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Distilling Multi-view Diffusion Models into 3D Generators
Reference 29
Source-reported events for the cited work
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Observation 43754cc3-8751-4f0c-ad5b-91e5b6cb2524 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Zero-shot text-to-image generation
Reference 30
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Observation 44ac6f5d-e6fb-4439-af59-140f64cb09bc · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents High-resolution image synthesis with latent diffusion models
Reference 31
Source-reported events for the cited work
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Observation 123c774a-3a96-4eaf-8d3a-a19c66a322d4 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Photorealistic text-to-image diffusion models with deep language understanding
Reference 32
Source-reported events for the cited work
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Observation cdfa3742-efd4-4d7b-9a6b-ef76ad4ef4bc · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Flexible isosurface extraction for gradient-based mesh optimiza- tion
Reference 33
Source-reported events for the cited work
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Observation 02e52bac-7f2f-4e2d-9500-70726d7964ea · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents MVDream: Multi-view Diffusion for 3D Generation
Reference 34
Source-reported events for the cited work
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Observation f5686262-42ce-4e80-8c61-eab5c8cc9aca · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Reference 35
Source-reported events for the cited work
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Observation a818d21b-c800-4efd-b5bb-59256c94944c · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Hunyuan3d 1.0: A uni- fied framework for text-to-3d and image-to-3d genera- tion, 2024
Reference 36
Source-reported events for the cited work
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Observation 18da872c-cdd0-4110-8f04-e29cbd4acedf · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Hunyuan3d 2.0: Scaling dif- fusion models for high resolution textured 3d assets gen- eration, 2025
Reference 37
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Observation 981a1305-39c1-49ff-9eff-f766c03b7a84 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Crm: Single image to 3d textured mesh with convolutional reconstruction model
Reference 38
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Observation 7a5a39ec-727c-4ca5-87d6-d721bb4414f9 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Q-align: Teaching lmms for visual scor- ing via discrete text-defined levels
Reference 39
Source-reported events for the cited work
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Advancing high-fidelity 3D and Texture Generation with 2.5D latents Unique3d: High-quality and efficient 3d mesh genera- tion from a single image, 2024
Reference 40
Source-reported events for the cited work
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Observation 43f98017-d19e-4d30-afe0-d6dbca8d6999 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Structured 3d latents for scalable and versatile 3d generation
Reference 41
Source-reported events for the cited work
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Observation 65372ffa-055d-4ed4-b5f2-b271bbca4fe1 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Florence-2: Advancing a unified representation for a variety of vision tasks
Reference 42
Source-reported events for the cited work
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Observation 0c064bdd-e866-4062-8eaf-96115c041d1e · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Texgaussian: Generating high-quality pbr material via octree-based 3d gaussian splatting
Reference 43
Source-reported events for the cited work
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Observation 0be927bf-ecf7-46fa-88d3-f269174a670a · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents FlexGen: Flexible Multi-View Generation from Text and Image Inputs
Reference 44
Source-reported events for the cited work
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Observation 018dbdba-e883-4bb8-95d6-06065e9a50b7 · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Sigmoid loss for language image pre- training, 2023
Reference 45
Source-reported events for the cited work
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Advancing high-fidelity 3D and Texture Generation with 2.5D latents Clay: A controllable large-scale generative model for creating high-quality 3d assets
Reference 46
Source-reported events for the cited work
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Observation d451ad1a-670b-4609-bc35-3759cac015bb · outbound
Advancing high-fidelity 3D and Texture Generation with 2.5D latents Mvdˆ 2: Efficient multiview 3d reconstruc- tion for multiview diffusion
Reference 47
Source-reported events for the cited work
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Observation 1df738bf-cf2e-401b-a0c4-3eb7469b5dbb · inbound
Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Model Advancing high-fidelity 3D and Texture Generation with 2.5D latents
Reference 46
Source-reported events for the cited work
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Observation 6ea79d41-0b8c-4b91-8c66-c236b62fa772 · inbound
DataEvolver: Let Your Data Build and Improve Itself via Goal-Driven Loop Agents Advancing high-fidelity 3D and Texture Generation with 2.5D latents
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.