Paper Citation Record · LEDGER

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework

As of 16 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2505.24245.

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

pith.paper-citation-record.v1
2505.24245 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:33:38.368887Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

verified exact1
verified fuzzy16
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ac94f1d8-26b4-4e5b-bd0e-27378c5e0056 · outbound

This paper cites GPT-4 Technical Report.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:34.854572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc9c0cdf-baa6-4b43-bfe7-bbb6c0b7abd8 · outbound

This paper cites Flamingo: a visual language model for few-shot learning.Advances in neural information processing systems, 35:23716–23736,.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Flamingo: a visual language model for few-shot learning.Advances in neural information processing systems, 35:23716–23736,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:34.991095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c445e6c-2b1a-4abc-a2a4-1333cf76f69c · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework ShapeNet: An Information-Rich 3D Model Repository

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:35.147821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17e07eeb-047b-4a72-be1a-3b9a93e0a164 · outbound

This paper cites MeshXL: Neural Coordinate Field for Generative 3D Foundation Models.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework MeshXL: Neural Coordinate Field for Generative 3D Foundation Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:35.284816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57d24baa-757d-4ad8-8621-23b055defbc0 · outbound

This paper cites Text-to-3d using gaussian splatting.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Text-to-3d using gaussian splatting

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:41.406199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2237ab6c-7e09-45de-bd10-25c8fa0cd992 · outbound

This paper cites Sdfusion: Multimodal 3d shape completion, reconstruction, and generation.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Sdfusion: Multimodal 3d shape completion, reconstruction, and generation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:41.248123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation acfb5287-8caa-4076-a3e6-0645244eeb67 · outbound

This paper cites Objaverse: A universe of annotated 3d objects.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Objaverse: A universe of annotated 3d objects

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:35.693755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bb6ce1c-8734-409c-8ecf-c6632d8ccc7a · outbound

This paper cites Masked autoencoders are scalable vision learners.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Masked autoencoders are scalable vision learners

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:41.118050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e04075b3-eaa6-4af1-8705-ce0c097dd671 · outbound

This paper cites DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:35.822212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bbe6e99-3960-4208-9d45-eb4b158e0da3 · outbound

This paper cites Shap-E: Generating Conditional 3D Implicit Functions.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Shap-E: Generating Conditional 3D Implicit Functions

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:35.918512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00f3cf73-ba51-4161-a09e-941db918af30 · outbound

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

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework 3d gaussian splatting for real-time radiance field rendering.ACM Trans

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:36.005351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 208ce92a-4569-4530-b08b-bd7a29cb40a2 · outbound

This paper cites Segment any- thing.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Segment any- thing

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:36.053994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9d2e18f-7b04-48a7-bd52-de60e38c468e · outbound

This paper cites Diffusion- sdf: Text-to-shape via voxelized diffusion.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Diffusion- sdf: Text-to-shape via voxelized diffusion

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:40.983218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dedbf24c-5b3a-47e3-9845-6dfd5df62e22 · outbound

This paper cites Autoregressive Image Generation without Vector Quantization.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Autoregressive Image Generation without Vector Quantization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:36.235172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa8df983-4bf5-4b52-a281-ffdf2d6e18b1 · outbound

This paper cites Magic3d: High-resolution text-to-3d content creation.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Magic3d: High-resolution text-to-3d content creation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:40.763173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 327095cf-11d8-467d-ac96-8cc0118edb4e · outbound

This paper cites FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:33:38.610708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 57568344-f8a1-4cee-9aa8-c9327e5b38bb · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view syn- thesis.Communications of the ACM, 65(1):99–106, 2021.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Nerf: Representing scenes as neural radiance fields for view syn- thesis.Communications of the ACM, 65(1):99–106, 2021

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:36.480926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da0c2d04-8ac2-43d8-bc44-4443fb563095 · outbound

This paper cites Autosdf: Shape priors for 3d comple- tion, reconstruction and generation.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Autosdf: Shape priors for 3d comple- tion, reconstruction and generation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:40.605354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c5168fa8-201e-43a0-944d-880c5587a814 · outbound

This paper cites Polygen: An autoregressive generative model of 3d meshes.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Polygen: An autoregressive generative model of 3d meshes

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:40.424862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 73d07521-8dda-4498-903a-0acc8c80afdd · outbound

This paper cites Point-E: A System for Generating 3D Point Clouds from Complex Prompts.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Point-E: A System for Generating 3D Point Clouds from Complex Prompts

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:36.695604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 226b3bd2-9914-4aa1-9846-a04f79dd6aba · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework DINOv2: Learning Robust Visual Features without Supervision

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:36.756072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72b2db93-28b6-46cd-b06a-f444cc5ef701 · outbound

This paper cites DreamFusion: Text-to-3D using 2D Diffusion.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework DreamFusion: Text-to-3D using 2D Diffusion

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:36.841766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bad6702b-8dc9-4f54-b718-8a6db91abeb2 · outbound

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

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Learning transferable visual models from natural language supervi- sion

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:36.932320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 687f1646-a635-4c6c-86ff-ec7cf0861352 · outbound

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

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Zero-shot text-to-image generation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:40.289153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9f5cc8b7-3b0e-4c0e-8f98-321995e2d3c9 · outbound

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

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework High-resolution image synthesis with latent diffusion models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:37.110644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63366473-daa8-4f29-b3cd-bffc1a179e68 · outbound

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

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494, 2022

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:37.190675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d29d2450-72a9-4999-b891-6bc0eff2eee2 · outbound

This paper cites Meshgpt: Generating triangle meshes with decoder-only transformers.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Meshgpt: Generating triangle meshes with decoder-only transformers

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:40.115863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 41822879-05f7-4508-a8d7-6c198db6fc75 · outbound

This paper cites Make-it-3d: High-fidelity 3d creation from a single image with diffusion prior.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Make-it-3d: High-fidelity 3d creation from a single image with diffusion prior

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:37.342613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d4d5483-f788-49f6-9f6d-be072f4c38d8 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework LLaMA: Open and Efficient Foundation Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:37.442699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98fdb654-897f-4ac9-9291-d08f21299333 · outbound

This paper cites Attention is all you need.Advances in Neural Information Processing Systems, 2017.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Attention is all you need.Advances in Neural Information Processing Systems, 2017

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:37.523208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85e0ad5c-177f-4b2e-ba1d-068861af7717 · outbound

This paper cites Hd- fusion: Detailed text-to-3d generation leveraging multiple noise estimation.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Hd- fusion: Detailed text-to-3d generation leveraging multiple noise estimation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:39.964739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e1c5edcd-23a3-49ae-8406-8b8553df24be · outbound

This paper cites Disn: Deep implicit surface network for high-quality single-view 3d reconstruction.Ad- vances in neural information processing systems, 32, 2019.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Disn: Deep implicit surface network for high-quality single-view 3d reconstruction.Ad- vances in neural information processing systems, 32, 2019

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:39.778378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation eee02389-cf48-41fb-8fe0-c7a476b4611e · outbound

This paper cites Ulip: Learning a unified representation of language, images, and point clouds for 3d understanding.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Ulip: Learning a unified representation of language, images, and point clouds for 3d understanding

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:37.768481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af029760-1e12-476b-8a70-9e9892f3da45 · outbound

This paper cites Points-to-3d: Bridging the gap be- tween sparse points and shape-controllable text-to-3d gener- ation.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Points-to-3d: Bridging the gap be- tween sparse points and shape-controllable text-to-3d gener- ation

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:39.579199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4be91d63-555f-43a0-afc8-64631d1e3a10 · outbound

This paper cites 3dilg: Ir- regular latent grids for 3d generative modeling.Advances in Neural Information Processing Systems, 35:21871–21885,.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework 3dilg: Ir- regular latent grids for 3d generative modeling.Advances in Neural Information Processing Systems, 35:21871–21885,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:39.406195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 765be0fa-94b9-4959-a1ab-aa2adb10b946 · outbound

This paper cites 3dshape2vecset: A 3d shape representation for neu- ral fields and generative diffusion models.ACM Transactions on Graphics (TOG), 42(4):1–16, 2023.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework 3dshape2vecset: A 3d shape representation for neu- ral fields and generative diffusion models.ACM Transactions on Graphics (TOG), 42(4):1–16, 2023

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:39.264135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1adbf657-3076-4a16-bed6-286a73275ddb · outbound

This paper cites GaussianCube: A Structured and Explicit Radiance Representation for 3D Generative Modeling.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework GaussianCube: A Structured and Explicit Radiance Representation for 3D Generative Modeling

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:38.104585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d26a4439-31d4-496f-bb74-dd5e7854e083 · outbound

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

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Adding conditional control to text-to-image diffusion models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:38.157033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09731d65-093a-4de5-b92f-484bbfbb6a53 · outbound

This paper cites Clay: A controllable large-scale generative model for creat- ing high-quality 3d assets.ACM Transactions on Graphics (TOG), 43(4):1–20, 2024.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Clay: A controllable large-scale generative model for creat- ing high-quality 3d assets.ACM Transactions on Graphics (TOG), 43(4):1–20, 2024

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:39.091365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f8ab4ab2-90ac-4046-96ae-78b2e6bd8874 · outbound

This paper cites Michelangelo: Conditional 3d shape generation based on shape-image-text aligned latent representation.Advances in Neural Information Processing Systems, 36, 2024.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework Michelangelo: Conditional 3d shape generation based on shape-image-text aligned latent representation.Advances in Neural Information Processing Systems, 36, 2024

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:33:38.937115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 861e2db1-8939-48a8-9724-d2f3b863eea2 · outbound

This paper cites HiFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance.

LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework HiFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T12:33:38.368887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.