Paper Citation Record · LEDGER

Advancing high-fidelity 3D and Texture Generation with 2.5D latents

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.

pith.paper-citation-record.v1
2505.21050 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:44:55.718353Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T18:21:15.831853Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-21T18:24:18.230169Z

Reference resolution

47 of 47 outbound references displayed

verified exact1
verified fuzzy30
unresolved16
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9d0967d4-10d6-49bb-9848-68352730a11d · outbound

This paper cites Albergo and Eric Vanden-Eijnden.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Albergo and Eric Vanden-Eijnden

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:02.884606Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 45df56ea-7ce0-43e1-8f8d-79d3c141135e · outbound

This paper cites Flux.1 model family.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Flux.1 model family

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:02.562694Z

Source-reported events for the cited work

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Observation dae2afd7-09f8-4dc9-90a7-63ee88430f72 · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 3

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Observation 1dbd9c65-d7c8-4912-b36f-bf9507ebddc9 · outbound

This paper cites Align your latents: High-resolution video synthe- sis with latent diffusion models.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:02.217888Z

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Observation e5105872-45be-4d53-b5e0-be52da2b4bb5 · outbound

This paper cites 3D-Adapter: Geometry-Consistent Multi-View Diffusion for High-Quality 3D Generation.

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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec90664c-5485-415f-aaae-d599fe10e9e0 · outbound

This paper cites Google scanned ob- jects: A high-quality dataset of 3d scanned household items.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:01.936912Z

Source-reported events for the cited work

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Observation 3a4ca331-daca-4910-ba79-86f2c3b8ca37 · outbound

This paper cites Scaling recti- fied flow transformers for high-resolution image synthe- sis.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Scaling recti- fied flow transformers for high-resolution image synthe- sis

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:01.676845Z

Source-reported events for the cited work

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Observation 3038ff2b-b83b-474e-9c7e-dd4924ff2ae4 · outbound

This paper cites DisEnvisioner: Disentangled and Enriched Visual Prompt for Customized Image Generation.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents DisEnvisioner: Disentangled and Enriched Visual Prompt for Customized Image Generation

Reference 8

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Source-reported events for the cited work

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Observation 663a2a6a-235d-4991-940a-4d980609598d · outbound

This paper cites Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T13:44:51.575434Z

Source-reported events for the cited work

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Observation d5b36f40-b1bd-4df3-ab41-d9ac8ba90b9c · outbound

This paper cites Clipscore: A reference-free eval- uation metric for image captioning.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Clipscore: A reference-free eval- uation metric for image captioning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:01.361729Z

Source-reported events for the cited work

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Observation dbcd3d9f-2f0b-4090-ace6-2df3c02d9058 · outbound

This paper cites Denoising diffusion probabilistic models.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Denoising diffusion probabilistic models

Reference 11

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Source-reported events for the cited work

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Observation 3102e8a4-30cd-4b1b-b08e-ea7de53394e7 · outbound

This paper cites Kingma, Ben Poole, Mohammad Norouzi, David J.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Kingma, Ben Poole, Mohammad Norouzi, David J

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:00.714998Z

Source-reported events for the cited work

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Observation 8b3db147-6bc6-45e0-87a9-57b597bf4b62 · outbound

This paper cites Video diffusion models.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Video diffusion models

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:00.439968Z

Source-reported events for the cited work

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Observation e85c2a46-1ce1-4720-9acd-8c8339b4c048 · outbound

This paper cites 3DTopia: Large Text-to-3D Generation Model with Hybrid Diffusion Priors.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents 3DTopia: Large Text-to-3D Generation Model with Hybrid Diffusion Priors

Reference 14

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Source-reported events for the cited work

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Observation a5fbb2b7-ef31-4094-a858-10774c442ff2 · outbound

This paper cites LoRA: Low-rank adaptation of large language models.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents LoRA: Low-rank adaptation of large language models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:00.154729Z

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 761774e2-4dbf-490c-83b9-0e381b748d2c · outbound

This paper cites Mv- adapter: Multi-view consistent image generation made easy.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Mv- adapter: Multi-view consistent image generation made easy

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:59.899641Z

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 b60267b7-d5cb-4d53-a81e-dce182b89044 · outbound

This paper cites Elucidating the Design Space of Diffusion-Based Generative Models.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Elucidating the Design Space of Diffusion-Based Generative Models

Reference 17

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Source-reported events for the cited work

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Observation 9800d0fd-556d-4033-b4a9-725b6cf0738d · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents 3d gaussian splatting for real-time radiance field rendering

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T13:44:52.466216Z

Source-reported events for the cited work

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Observation b43a65d5-f38f-4ca4-bd93-4b43c3cd3fa1 · outbound

This paper cites CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refiner.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T13:44:52.573441Z

Source-reported events for the cited work

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Observation 66278dd6-f1c1-4fa6-ba7f-cfe9560fa176 · outbound

This paper cites Triposg: High- fidelity 3d shape synthesis using large-scale rectified flow models.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:59.521881Z

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 ba990e37-c957-49ab-91fc-adcb9ff51f73 · outbound

This paper cites Kiss3dgen: Repurposing image dif- fusion models for 3d asset generation.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Kiss3dgen: Repurposing image dif- fusion models for 3d asset generation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:59.171200Z

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 6279aff0-72a0-4524-b584-318c24dbcd49 · outbound

This paper cites an unresolved cited work.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Unresolved cited work

Reference 22

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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 22e913ea-04b2-4fd7-912e-058026cfa0ec · outbound

This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow, 2022.

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

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Source-reported events for the cited work

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Observation e5fa586a-16d0-4fe4-bae0-40390d860601 · outbound

This paper cites Text-guided texturing by synchronized multi- view diffusion.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Text-guided texturing by synchronized multi- view diffusion

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:58.569175Z

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 cfddbd3b-4b80-47fa-b1c0-4017d68aa283 · outbound

This paper cites MeshDiffusion: Score-based Generative 3D Mesh Modeling.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents MeshDiffusion: Score-based Generative 3D Mesh Modeling

Reference 25

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Source-reported events for the cited work

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Observation 622a369a-d9b5-472e-bcb8-a24d6b676eee · outbound

This paper cites Wonder3d: Single image to 3d using cross-domain diffusion.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Wonder3d: Single image to 3d using cross-domain diffusion

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:58.341688Z

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 eee18347-02da-4770-9d87-0814bb2376dc · outbound

This paper cites an unresolved cited work.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:44:58.166874Z

Source-reported events for the cited work

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Observation 979c9861-5200-4709-a890-a90375b6f2b2 · outbound

This paper cites DSplats: 3D Generation by Denoising Splats-Based Multiview Diffusion Models.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents DSplats: 3D Generation by Denoising Splats-Based Multiview Diffusion Models

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:44:56.011352Z

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 21001367-0ddc-40ed-88ef-a933fe54bea1 · outbound

This paper cites Distilling Multi-view Diffusion Models into 3D Generators.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Distilling Multi-view Diffusion Models into 3D Generators

Reference 29

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Source-reported events for the cited work

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Observation 43754cc3-8751-4f0c-ad5b-91e5b6cb2524 · outbound

This paper cites Zero-shot text-to-image generation.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Zero-shot text-to-image generation

Reference 30

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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 44ac6f5d-e6fb-4439-af59-140f64cb09bc · outbound

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

Advancing high-fidelity 3D and Texture Generation with 2.5D latents High-resolution image synthesis with latent diffusion models

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:57.929442Z

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 123c774a-3a96-4eaf-8d3a-a19c66a322d4 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Photorealistic text-to-image diffusion models with deep language understanding

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:57.872216Z

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 cdfa3742-efd4-4d7b-9a6b-ef76ad4ef4bc · outbound

This paper cites Flexible isosurface extraction for gradient-based mesh optimiza- tion.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Flexible isosurface extraction for gradient-based mesh optimiza- tion

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:57.832209Z

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 02e52bac-7f2f-4e2d-9500-70726d7964ea · outbound

This paper cites MVDream: Multi-view Diffusion for 3D Generation.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents MVDream: Multi-view Diffusion for 3D Generation

Reference 34

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Source-reported events for the cited work

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Observation f5686262-42ce-4e80-8c61-eab5c8cc9aca · outbound

This paper cites Deep Unsupervised Learning using Nonequilibrium Thermodynamics.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T13:44:54.473473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a818d21b-c800-4efd-b5bb-59256c94944c · outbound

This paper cites Hunyuan3d 1.0: A uni- fied framework for text-to-3d and image-to-3d genera- tion, 2024.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:57.753053Z

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 18da872c-cdd0-4110-8f04-e29cbd4acedf · outbound

This paper cites Hunyuan3d 2.0: Scaling dif- fusion models for high resolution textured 3d assets gen- eration, 2025.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:57.617281Z

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 981a1305-39c1-49ff-9eff-f766c03b7a84 · outbound

This paper cites Crm: Single image to 3d textured mesh with convolutional reconstruction model.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Crm: Single image to 3d textured mesh with convolutional reconstruction model

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:57.450368Z

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 7a5a39ec-727c-4ca5-87d6-d721bb4414f9 · outbound

This paper cites Q-align: Teaching lmms for visual scor- ing via discrete text-defined levels.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:57.323228Z

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 bea7fce3-bf05-41e0-8e93-d048647a8857 · outbound

This paper cites Unique3d: High-quality and efficient 3d mesh genera- tion from a single image, 2024.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:57.195467Z

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 43f98017-d19e-4d30-afe0-d6dbca8d6999 · outbound

This paper cites Structured 3d latents for scalable and versatile 3d generation.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Structured 3d latents for scalable and versatile 3d generation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:57.064937Z

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 65372ffa-055d-4ed4-b5f2-b271bbca4fe1 · outbound

This paper cites Florence-2: Advancing a unified representation for a variety of vision tasks.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:56.913224Z

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 0c064bdd-e866-4062-8eaf-96115c041d1e · outbound

This paper cites Texgaussian: Generating high-quality pbr material via octree-based 3d gaussian splatting.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:56.794228Z

Source-reported events for the cited work

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Observation 0be927bf-ecf7-46fa-88d3-f269174a670a · outbound

This paper cites FlexGen: Flexible Multi-View Generation from Text and Image Inputs.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents FlexGen: Flexible Multi-View Generation from Text and Image Inputs

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T13:44:55.377242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 018dbdba-e883-4bb8-95d6-06065e9a50b7 · outbound

This paper cites Sigmoid loss for language image pre- training, 2023.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Sigmoid loss for language image pre- training, 2023

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:56.673708Z

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 40291dd7-c446-4869-9950-26d40b694265 · outbound

This paper cites Clay: A controllable large-scale generative model for creating high-quality 3d assets.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:56.542360Z

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 d451ad1a-670b-4609-bc35-3759cac015bb · outbound

This paper cites Mvdˆ 2: Efficient multiview 3d reconstruc- tion for multiview diffusion.

Advancing high-fidelity 3D and Texture Generation with 2.5D latents Mvdˆ 2: Efficient multiview 3d reconstruc- tion for multiview diffusion

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:44:56.337077Z

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.

Pith citing papers

Observation 1df738bf-cf2e-401b-a0c4-3eb7469b5dbb · inbound

Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Model cites this paper.

Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Model Advancing high-fidelity 3D and Texture Generation with 2.5D latents

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-21T18:24:18.232257Z

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 6ea79d41-0b8c-4b91-8c66-c236b62fa772 · inbound

DataEvolver: Let Your Data Build and Improve Itself via Goal-Driven Loop Agents cites this paper.

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

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:46:05.452930Z

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.