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Paper Citation Record · LEDGER

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization

As of 22 August 2026, this Paper Citation Record lists 92 of 92 outbound references and 7 inbound Pith citation observations for arXiv:2502.04370.

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

pith.paper-citation-record.v1
2502.04370 v1

Coverage vector

measured 92 of 92 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T06:04:11.056029Z

measured 99 of 99 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:57:34.760038Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:09:29.452062Z

Reference resolution

92 of 92 outbound references displayed

  • verified exact0
  • verified fuzzy36
  • unresolved56
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7aa07519-4a33-4403-84d3-c16bdfa4e10c · outbound

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

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization DreamFusion: Text-to-3D using 2D Diffusion

Reference 2

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.735543Z digest=sha256:31ee365214b1a66273ff5ba8f29527a3a7127e6dc03050ec562c6e3564021e0c

Observation 2a6b366e-d0fe-415b-bfdd-7f1a3161455c · outbound

This paper cites ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation

Reference 3

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source=pdf_text observed=2026-08-09T06:04:10.738011Z digest=sha256:cc44f31f207413abebba3969ab4e5347034643970c6c51146f95d481c70e902a

Observation cef68c5b-6926-4812-b631-75c43f37a344 · outbound

This paper cites Yeh, and Greg Shakhnarovich.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Yeh, and Greg Shakhnarovich

Reference 4

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source=pdf_text observed=2026-08-09T06:04:10.741067Z digest=sha256:03a8d5f3da268eb4737a7a12077fd9d2ae3bb9e1cf13add581d46fb65ab2f79b

Observation e2ea4a6f-e858-4903-ac3f-63a9a39b0188 · outbound

This paper cites Text-to-3D with Classifier Score Distillation.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Text-to-3D with Classifier Score Distillation

Reference 5

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.743795Z digest=sha256:3c7dfd94efc2a26f40a5f84149267237e2e97b726e4b98fae842e347b8c64204

Observation ac35b794-6aea-4735-aee1-096c65810563 · outbound

This paper cites Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation

Reference 6

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no resolver link, observed 2026-08-09T06:04:10.746744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.746744Z digest=sha256:f8c0e872dcf4f990e5e062c892e3d0ef387357c77c8aa3398a6c11fafced5de7

Observation 0c0d1ea2-7c96-40d9-b401-fc23e70a376f · outbound

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

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization MVDream: Multi-view Diffusion for 3D Generation

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.749371Z digest=sha256:e424fe5eeb67705f555cda39de462176b5efa6ca05d8134ef5e21bf3333e81d5

Observation cdefcc24-1fe9-4420-adb2-304881f0ca9e · outbound

This paper cites Noise-Free Score Distillation.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Noise-Free Score Distillation

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.752176Z digest=sha256:b61a485ea3738afb91fb73317a848b3a2caa8c6e26258b27778374e3e189c8dc

Observation 90ef463f-016a-4429-8e58-e11c058c3244 · outbound

This paper cites Luciddreamer: Domain-free generation of 3d gaussian splatting scenes.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Luciddreamer: Domain-free generation of 3d gaussian splatting scenes

Reference 9

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no resolver link, observed 2026-08-09T06:04:10.755077Z

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source=pdf_text observed=2026-08-09T06:04:10.755077Z digest=sha256:0287ef2a2d43a916800a6ce505f241dd44a57186c460302933cff6b9ca0cca07

Observation 75fa5eaa-b4d8-4779-853a-08c3a78c912b · outbound

This paper cites Consistent3d: Towards consistent high-fidelity text-to-3d generation with deterministic sampling prior.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Consistent3d: Towards consistent high-fidelity text-to-3d generation with deterministic sampling prior

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.757189Z digest=sha256:d592092c922918ef57e062031cfe8502d9dbbe0b827819f661bad7ccb4d4281e

Observation bd9094f0-c609-4a52-9c60-ab204da3e199 · outbound

This paper cites Carve3d: Improving multi-view reconstruction consistency for diffusion models with rl finetuning.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Carve3d: Improving multi-view reconstruction consistency for diffusion models with rl finetuning

Reference 11

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.759207Z digest=sha256:c6dda6da301171ebd2a8b977be6f285480263dd2e96ba43ae0286982ac2e1f0a

Observation f2459d05-8410-4d40-83fd-49b8af37a0f6 · outbound

This paper cites Dreamreward: Text-to-3d generation with human preference.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Dreamreward: Text-to-3d generation with human preference

Reference 12

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.761207Z digest=sha256:472cbd4522d1ffc3d037900044b7cb53d6385a2ad90817d2a5ace4a45ba51155

Observation bb3d0d5a-0787-4383-af68-3adb57d0caa8 · outbound

This paper cites Srinivasan, Matthew Tancik, Jonathan T.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Srinivasan, Matthew Tancik, Jonathan T

Reference 13

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source=pdf_text observed=2026-08-09T06:04:10.763238Z digest=sha256:dcc9c5b6b53bb1f9bbbc79079bbcb764b0cc32ae090791f6bbed1ae31281f065

Observation dfc3b374-a1ed-4c77-a4ad-9605278aca2f · outbound

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

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization 3d gaussian splatting for real-time radiance field rendering

Reference 14

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no resolver link, observed 2026-08-09T06:04:10.765272Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.765272Z digest=sha256:3f41ac72c3269a5b902d2f7aaa2ae7d4976c68441edf282332f379d56215f86a

Observation 5db1a806-cd30-4e1d-99c0-863d38d2d05d · outbound

This paper cites Generating chain-of-thoughts with a direct pairwise-comparison approach to searching for the most promising intermediate thought.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Generating chain-of-thoughts with a direct pairwise-comparison approach to searching for the most promising intermediate thought

Reference 16

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.769503Z digest=sha256:4929f0c8b97574a16f0207ce477a2261ecf0e2a1933850522ee05bfc148ee1ad

Observation 53ce393f-38a0-4a1a-ae14-b8d2322304f7 · outbound

This paper cites Deep marching tetrahedra: a hybrid representation for high-resolution 3d shape synthesis.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Deep marching tetrahedra: a hybrid representation for high-resolution 3d shape synthesis

Reference 18

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source=pdf_text observed=2026-08-09T06:04:10.774493Z digest=sha256:ad70d100774b8498245df2657d8f3bb6087cfb66278b81b2ca76249ee4603b78

Observation 5a86ae59-a55e-469b-af16-5b96a5dc5e44 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Deep unsupervised learning using nonequilibrium thermodynamics

Reference 19

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source=pdf_text observed=2026-08-09T06:04:10.776867Z digest=sha256:8be3cccb7569c989897dc474bd44d90c1d93f50bdc114193bacdf77cfaf5ed48

Observation 439a5c62-f673-45dd-9c62-8e321cea860d · outbound

This paper cites Diffusion Guided Domain Adaptation of Image Generators.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Diffusion Guided Domain Adaptation of Image Generators

Reference 20

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source=pdf_text observed=2026-08-09T06:04:10.779292Z digest=sha256:0e76ab2caec64477336f78c8453d9ebf8f6f9176c762637427e14226f5e596f1

Observation bc5ef44f-56a9-4efa-9f40-9cb84c78bb39 · outbound

This paper cites Analytic-dpm: an analytic estimate of the optimal reverse variance in diffusion probabilistic models.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Analytic-dpm: an analytic estimate of the optimal reverse variance in diffusion probabilistic models

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-09T06:04:12.046297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.781798Z digest=sha256:17492bc20401f307ce484075e10777e61637af113f5aa052717f8d606dec4f4a

Observation c3cf7960-f3e5-49d1-bcf7-792b61b7f955 · outbound

This paper cites Scalable diffusion models with transformers.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Scalable diffusion models with transformers

Reference 22

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source=pdf_text observed=2026-08-09T06:04:10.784015Z digest=sha256:9f7db9a9be895adb8cdf7416c37eadf4487e9c7b0ed0fcd952d9481c455ea7cb

Observation f73ceafe-61e6-4e21-9afe-34377263f3e0 · outbound

This paper cites Vividdreamer: invariant score distillation for hyper-realistic text-to-3d generation.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Vividdreamer: invariant score distillation for hyper-realistic text-to-3d generation

Reference 23

Resolution
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raw_fallback, observed 2026-08-09T06:04:12.024236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.786347Z digest=sha256:bcc150d92aae724a649239ed4933ece8792284b2ad60ff298bb746a9bb47a4b5

Observation 810a6e6a-86a1-493b-859b-9efe6b1d31b1 · outbound

This paper cites Classifier-Free Diffusion Guidance.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Classifier-Free Diffusion Guidance

Reference 24

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source=pdf_text observed=2026-08-09T06:04:10.788751Z digest=sha256:154682a5ed5dd988484b0644a694d04ea9252cd43ea6b5a22c407a894695246a

Observation 4d129655-2ba3-4264-9d95-be3c08d3e7b6 · outbound

This paper cites Gpt-4v (ision) is a human-aligned evaluator for text-to-3d generation.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Gpt-4v (ision) is a human-aligned evaluator for text-to-3d generation

Reference 25

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raw_fallback, observed 2026-08-09T06:04:11.999372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.791273Z digest=sha256:91927c5a1e808f502bb30a90fda5e00b1bd7e3d687100ae72d779b378478f4a3

Observation 1170ecc6-9da3-4e37-ae23-4308b447ece1 · outbound

This paper cites Imagereward: Learning and evaluating human preferences for text-to-image generation.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Imagereward: Learning and evaluating human preferences for text-to-image generation

Reference 26

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source=pdf_text observed=2026-08-09T06:04:10.794177Z digest=sha256:1b74d88978df0178ab0d2acd8f8b5e9d755b5a486481637957583ab3982bcf50

Observation 985b8618-15a2-46ce-847e-57f67825404e · outbound

This paper cites Learning transferable visual models from natural language supervision.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Learning transferable visual models from natural language supervision

Reference 27

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source=pdf_text observed=2026-08-09T06:04:10.796513Z digest=sha256:81384df8efed0d51c61136422ff9eea0d727ee952bd780d5044739f2a0f0640f

Observation 84028fa5-0f9c-4a08-afaf-f821f17930d0 · outbound

This paper cites DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation

Reference 28

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source=pdf_text observed=2026-08-09T06:04:10.799027Z digest=sha256:fd47f375365249644f61b3697c89a1f63969253554aa205a0db905fb38479755

Observation 2ee0e7de-c807-4b96-a681-30dd7745fcf4 · outbound

This paper cites Fantasia3d: Disentangling geometry and appearance for high-quality text-to-3d content creation.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Fantasia3d: Disentangling geometry and appearance for high-quality text-to-3d content creation

Reference 29

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raw_fallback, observed 2026-08-09T06:04:11.957068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.801594Z digest=sha256:11dd1b37a9539810068186debc07b9973fcdd6072ecd2af3141681d4473dea5f

Observation b38a722e-f5b8-48e9-b1e4-0597bbe23f8b · outbound

This paper cites Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model

Reference 30

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source=pdf_text observed=2026-08-09T06:04:10.804039Z digest=sha256:4a37142feb303228836a905f97d5dd4043e11a38ca00c82952a219eb04746cb8

Observation 2e01d642-2267-4228-a8d5-86c7904194fb · outbound

This paper cites Latent-nerf for shape-guided generation of 3d shapes and textures.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Latent-nerf for shape-guided generation of 3d shapes and textures

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.915690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.806418Z digest=sha256:9cde91192d0955bf999e30f0a8038fc24151353e0f1bee52cca7815d2bf9865f

Observation e75f5dc4-f8b7-401c-8407-6ea4a05a1867 · outbound

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

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Magic3d: High-resolution text-to-3d content creation

Reference 32

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raw_fallback, observed 2026-08-09T06:04:11.888325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.808816Z digest=sha256:b5c3815e97fa2aa7493ff97fc4e393adc2d4a994c3e207921f6ca2808e794ad4

Observation c954b939-4873-4520-9a34-adfe1a077e50 · outbound

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

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Point-E: A System for Generating 3D Point Clouds from Complex Prompts

Reference 33

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source=pdf_text observed=2026-08-09T06:04:10.811142Z digest=sha256:8fc7165f1d16435b98630eaef6dba6fc6a0e9da3795ff1fe909aa037d8d79f84

Observation f344ffb3-cac2-4a6f-b68b-1b40fb8bd95d · outbound

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

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Shap-E: Generating Conditional 3D Implicit Functions

Reference 34

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-09T06:04:10.813929Z digest=sha256:8096189c224000a3c4f0c4044957609beb85a825bc06cb31b188c1ab8f93fa79

Observation 682128d6-192d-4aaf-bcf2-6533841d352a · outbound

This paper cites Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.880289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.816347Z digest=sha256:f9d021c7b92d171bc5b72c87a2f539852952dfbd025877e9323517f0f619ae1b

Observation 7ba5e17c-2a35-4bfa-bf4c-e1f97401c139 · outbound

This paper cites SyncDreamer: Generating Multiview-consistent Images from a Single-view Image.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization SyncDreamer: Generating Multiview-consistent Images from a Single-view Image

Reference 36

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source=pdf_text observed=2026-08-09T06:04:10.819032Z digest=sha256:7e0664c1e98a3f9fe947c41b48dd486732e658508d9fb2cc0ace429dc034051f

Observation 73170d86-9a29-4282-9876-dee6385ff29a · outbound

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

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Wonder3d: Single image to 3d using cross-domain diffusion

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.871769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.821193Z digest=sha256:62a94c22fb162d55b7f81102115dee91f4b5c49bdfd11b0b43a1a651ed4681ba

Observation c166ac88-2cbe-4d97-93b4-89f986eee4b0 · outbound

This paper cites Denoising diffusion probabilistic models.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Denoising diffusion probabilistic models

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.862858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.823225Z digest=sha256:e50759d432900976229e9b335ce053796c56f5b2fe51ff24215bbf37e5e2d568

Observation 1420adfb-7256-4cf2-ac57-bc0c180f0707 · outbound

This paper cites Denoising diffusion implicit models.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Denoising diffusion implicit models

Reference 39

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.825453Z digest=sha256:426cfd886c5bc3f4de3f3a8ed2dae667e63d5d5b4fe3dd660da0bdd177bcd9b5

Observation c8b4a58e-c83f-4cfa-a4f7-c52c65f49458 · outbound

This paper cites Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Reference 40

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.827673Z digest=sha256:ba1fb333c026df97d77e2cd501ce97c5a44b736989d46c1c3d443d4ab77d47d6

Observation 36cc0a81-1110-4588-8551-c389e1f210e6 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 41

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no resolver link, observed 2026-08-09T06:04:10.830307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.830307Z digest=sha256:b23a9c803371db9e9cd43125009f7eb85c9758be834bffa1811cb73441793372

Observation a77091ed-26da-45bb-8dfd-bdf6f4cc5f7f · outbound

This paper cites The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision).

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)

Reference 42

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.833263Z digest=sha256:6c6d85256a9a99a0b9f4325b08ebd233f43b5f665966c90876c5501b4df832c8

Observation 3df79d11-e585-4915-b29b-ff443a62b535 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Direct preference optimization: Your language model is secretly a reward model

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.850190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.835287Z digest=sha256:e2a5a673d8a1c53ffe33e8393c050af927aa7ef53dd0e645a767ee4128650906

Observation b3f3a684-9bf5-43ce-957c-1282e2e0a2ad · outbound

This paper cites SimPO: Simple Preference Optimization with a Reference-Free Reward.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization SimPO: Simple Preference Optimization with a Reference-Free Reward

Reference 44

Resolution
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no resolver link, observed 2026-08-09T06:04:10.837435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.837435Z digest=sha256:e26ab590eeba2a7aff307ac6eb0b46f9c04870d38651e4c4744b6fd53df06c15

Observation 6c99b37c-d852-4588-8ccd-80161328b2d6 · outbound

This paper cites Diffusion model alignment using direct preference optimization.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Diffusion model alignment using direct preference optimization

Reference 45

Resolution
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no resolver link, observed 2026-08-09T06:04:10.839473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.839473Z digest=sha256:892a9058c14cec43d3df611cb0fdef7120defb9bab22e576249f46fb900941a7

Observation 0253297d-9adc-4b5d-bacd-065075ecfa85 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Pytorch: An imperative style, high-performance deep learning library

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.838456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.841657Z digest=sha256:b1a21f1bbc85905a3d2f6a64bbc3e4693685bb916ca1240da0131fecbe4d163e

Observation 0098d81b-684a-4da3-9ce5-aeccb9b3a915 · outbound

This paper cites threestudio: A unified framework for 3d content generation.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization threestudio: A unified framework for 3d content generation

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.831179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.844116Z digest=sha256:34f7f21202e5adebd458794467998d68545becf1c7328d46221e6e1730b0feea

Observation 58f281bb-08f3-4eca-a772-3ee6af0e121f · outbound

This paper cites Headstudio: Text to animatable head avatars with 3d gaussian splatting.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Headstudio: Text to animatable head avatars with 3d gaussian splatting

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.823218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.846472Z digest=sha256:ac24e68b9ee4e1b48567e990d8d2492ab799cb7dce29385e0160efb81e8b03b1

Observation e578f5af-60c3-4cdb-90f1-f463a89e2880 · outbound

This paper cites Visionreward: Fine-grained multi-dimensional human preference learning for image and video generation, 2024.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Visionreward: Fine-grained multi-dimensional human preference learning for image and video generation, 2024

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.815700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.849140Z digest=sha256:7a34a6af9e6d94531232d3e20f49358ed41fd5a4aaf8a37d14a3ed7d06c329fc

Observation f87bf0fd-0455-4918-8799-c337b66a372c · outbound

This paper cites 4d-fy: Text-to-4d generation using hybrid score distillation sampling.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization 4d-fy: Text-to-4d generation using hybrid score distillation sampling

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.808062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.852336Z digest=sha256:6da928cc43723d751374597cadf52c6a4481f6b1beabaa39db88e0692f32d201

Observation 65f630ec-f289-4077-b530-e1bd1d8697f3 · outbound

This paper cites Text2nerf: Text-driven 3d scene generation with neural radiance fields.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Text2nerf: Text-driven 3d scene generation with neural radiance fields

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.800008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.855611Z digest=sha256:c69e24aeeaab178cbfddd6ae6b77761c6263321534943a41c5714074757a4f49

Observation ad39f2df-ce30-4b6e-9845-be196d64b886 · outbound

This paper cites Vp3d: Unleashing 2d visual prompt for text-to-3d generation.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Vp3d: Unleashing 2d visual prompt for text-to-3d generation

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.763551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.858334Z digest=sha256:d2fa8135bfb9f7898176faf27c51b0443eb245308b9e52aab83cd4643d477223

Observation e434a227-9ade-4a9c-8292-985771b0623f · outbound

This paper cites Detecting everything in the open world: Towards universal object detection.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Detecting everything in the open world: Towards universal object detection

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.704473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.861878Z digest=sha256:b2ee53ab533b5dbbd36975a6c8f8e913895fbfe5d4e629f9278dd7f24880a5e8

Observation b5405a7f-5531-4ad2-818c-1f0b1235f35e · outbound

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

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization DINOv2: Learning Robust Visual Features without Supervision

Reference 54

Resolution
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no resolver link, observed 2026-08-09T06:04:10.864412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.864412Z digest=sha256:d49f90b5ab5895c1dcc1bd7c6112c74259fdf7dd9f7c75c47925772b19df6011

Observation 45b79256-154f-4b0b-b8a0-f4d63c6b06c2 · outbound

This paper cites Diffuse attend and segment: Unsupervised zero-shot segmentation using stable diffusion.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Diffuse attend and segment: Unsupervised zero-shot segmentation using stable diffusion

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.658836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.867406Z digest=sha256:d484c690baec8d88cc40144506b199df19147fdc1721cb26b063cd3cbee856c1

Observation d0c733da-b616-4fdc-aba5-85d74ffd3645 · outbound

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

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 56

Resolution
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no resolver link, observed 2026-08-09T06:04:10.869794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.869794Z digest=sha256:1ca9a4bb812d879e64fd0e5c9bf7a89bf7019db331efb09b11af0da672acdab1

Observation a09f9db6-cdac-4e9c-9def-0286e7d18ecd · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Imagen Video: High Definition Video Generation with Diffusion Models

Reference 57

Resolution
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no resolver link, observed 2026-08-09T06:04:10.872438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.872438Z digest=sha256:6d41ba83bcd1500b73f88d2475b448f4e890cb1278f2d6ed5893e32d2096d74f

Observation fd3e5285-34e8-4d27-9c8a-5fd915bc6c68 · outbound

This paper cites Text-to-image Diffusion Models in Generative AI: A Survey.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Text-to-image Diffusion Models in Generative AI: A Survey

Reference 58

Resolution
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no resolver link, observed 2026-08-09T06:04:10.875380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.875380Z digest=sha256:791fa7e60cc6955246b2a2a88433ef4d645615bb2c9726fe8b9aa7340bbc298d

Observation c8588b71-d933-4d8b-9fb1-cf744d9b32bb · outbound

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

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization High-resolution image synthesis with latent diffusion models

Reference 59

Resolution
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no resolver link, observed 2026-08-09T06:04:10.878058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.878058Z digest=sha256:9d90ce95adaa788e745042b5c2c6cf078facbac06b5c238078e69146e56f81e7

Observation 4c3426be-fe0e-4e8b-903a-6d7284a511e8 · outbound

This paper cites Sketch-guided text-to-image diffusion models.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Sketch-guided text-to-image diffusion models

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.651159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.881137Z digest=sha256:899bd0feca072aec81f1deeb9a0cc1c264ba3465f19eb3440dc823c90a55fc25

Observation 10120a37-db61-4862-a1ff-fdc6eb519fbb · outbound

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

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Adding conditional control to text-to-image diffusion models

Reference 61

Resolution
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no resolver link, observed 2026-08-09T06:04:10.883817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.883817Z digest=sha256:62349faef1b295803f80e8e3ac477d55be74032846a7990572382031ffd7d6c9

Observation 204592fa-9369-410b-86ed-473f64b57ea6 · outbound

This paper cites An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Reference 62

Resolution
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no resolver link, observed 2026-08-09T06:04:10.886154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.886154Z digest=sha256:88d574d2555e6b50ea48a79e84792c9515b2c47a17026270ddd1d781d570046c

Observation f73c546e-713f-4bfc-9b0d-11444c745061 · outbound

This paper cites DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation

Reference 63

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.888953Z digest=sha256:f3ebddf5d222fc40d58365e455251996c5f1260ea7abecea147aff20516e9b48

Observation b09995c4-39b4-4e73-b693-7e4d748b006e · outbound

This paper cites Instructpix2pix: Learning to follow image editing instructions.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Instructpix2pix: Learning to follow image editing instructions

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.640125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.891707Z digest=sha256:baef3e31fd4b5b5b7d1fe8da0966615bd112f8ea02f23c86195a590e51b357dd

Observation 54befc3d-8204-4b26-aea0-80cdb762640c · outbound

This paper cites Mip-nerf 360: Unbounded anti-aliased neural radiance fields.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Mip-nerf 360: Unbounded anti-aliased neural radiance fields

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.632920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.893939Z digest=sha256:cb06e8476d912ecf693dad1026302fac18e3afe9667236f148268730a64560cb

Observation 77179cc0-d886-45b9-9019-7590d9caca1b · outbound

This paper cites Barron, Pieter Abbeel, and Ben Poole.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Barron, Pieter Abbeel, and Ben Poole

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.625644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.896256Z digest=sha256:47bf1bf87a4dd02c6d25229db1bab4d7a7ccb674cbad40431618690eb0700cbf

Observation c8fa2f50-48bd-49e1-a95a-50b7bfc1e185 · outbound

This paper cites Generative AI meets 3D: A Survey on Text-to-3D in AIGC Era.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Generative AI meets 3D: A Survey on Text-to-3D in AIGC Era

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-09T06:04:10.898773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.898773Z digest=sha256:b65c3f07d72d3c77a8966c3d574804e5a94a0c6fa0adaae87053e0aedcbe21d8

Observation 82af5d14-c072-445c-a481-2c23d7c33212 · outbound

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

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization HiFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-09T06:04:10.901397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.901397Z digest=sha256:ff12b0d3e96ad5d874dbd6eaf1331d407a95f6caaacbac0f7100662e226fb01e

Observation 7e351a74-3a4e-44e3-a8f8-b01ae4ce95fa · outbound

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

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Objaverse: A universe of annotated 3d objects

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.618928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.903814Z digest=sha256:0e06bf38f945cddb25ff20173a91b9b7d393923d4db56b05be6933789aee166f

Observation 39144d47-6c3d-4822-af47-fca9fbf75675 · outbound

This paper cites Objaverse-xl: A universe of 10m+ 3d objects.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Objaverse-xl: A universe of 10m+ 3d objects

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.612093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.906081Z digest=sha256:e7924f942c52be6550706f460725edeb04320df13d467ce363ce03d652b45038

Observation 7355206e-38df-4346-b853-3c112c675681 · outbound

This paper cites Zero-1-to-3: Zero-shot one image to 3d object.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Zero-1-to-3: Zero-shot one image to 3d object

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.604811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.908126Z digest=sha256:64461167171fbb3df3a80619a69113ef493341762e13ab70392347ac249314a3

Observation a7c33b82-47d5-436b-98f6-f55eff8948d7 · outbound

This paper cites One-2-3-45: Any single image to 3d mesh in 45 seconds without per-shape optimization.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization One-2-3-45: Any single image to 3d mesh in 45 seconds without per-shape optimization

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.597547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.910444Z digest=sha256:181714bb8cb9b4ca534bc4e25e224e807cad5d371649067d4b445bf21bf8cef5

Observation 1ef16e62-7052-4ce4-9220-e401925f8880 · outbound

This paper cites Set-the-Scene: Global-Local Training for Generating Controllable NeRF Scenes.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Set-the-Scene: Global-Local Training for Generating Controllable NeRF Scenes

Reference 73

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.913043Z digest=sha256:f70f151837e3dda0cb9555eeaa6a2f4002a811f845f26b35c597095ae5490d65

Observation 54dfc6b9-9cf5-490b-a620-dfe9568844f3 · outbound

This paper cites Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Models.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Models

Reference 74

Resolution
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no resolver link, observed 2026-08-09T06:04:10.915527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.915527Z digest=sha256:1e5eeaa1b33070475c80f297c260132b69c8bcef509723ebb7881e0ece77151e

Observation 007ddc8a-f9ef-4da2-b3b4-08455b6efef5 · outbound

This paper cites Instruct-nerf2nerf: Editing 3d scenes with instructions.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Instruct-nerf2nerf: Editing 3d scenes with instructions

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.589949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:10.926055Z digest=sha256:238827b36905cf8376d3d72c1788395c365e3b989989713ca2e9b75192e234b2

Observation f105d0c7-e274-4c3a-8c2a-c75708db5f94 · outbound

This paper cites Instruct 3D-to-3D: Text Instruction Guided 3D-to-3D conversion.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Instruct 3D-to-3D: Text Instruction Guided 3D-to-3D conversion

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-09T06:04:10.938030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.938030Z digest=sha256:585fb80697d31dd2622237fab6418f1e56d6eab16f0339188e6d7cbcd1fb694b

Observation 96f46db9-fd18-4d08-b43e-f294657c9573 · outbound

This paper cites DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Models.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Models

Reference 77

Resolution
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no resolver link, observed 2026-08-09T06:04:10.951357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.951357Z digest=sha256:c29e19399cb5e42241da14bfd34d34cbc28c986fabc3b8edc018508696230c4e

Observation 01a8b929-8d4b-43a0-aa39-90c798b7c68c · outbound

This paper cites AvatarCraft: Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Control.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization AvatarCraft: Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Control

Reference 78

Resolution
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no resolver link, observed 2026-08-09T06:04:10.965794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.965794Z digest=sha256:b9e98bbb920d843a20d18f1ec49db5095f14be67aee7656fbb0a23db8d95d15a

Observation 0c2ac4f4-817d-404b-b177-35b837bc8bca · outbound

This paper cites HeadSculpt: Crafting 3D Head Avatars with Text.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization HeadSculpt: Crafting 3D Head Avatars with Text

Reference 79

Resolution
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no resolver link, observed 2026-08-09T06:04:10.988385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.988385Z digest=sha256:f1adec16869210219c0d49217ae91a390848dc5a160c19c3b88342f4499d02fe

Observation 61527d71-5339-455c-90fc-189f1b4aa964 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-09T06:04:11.001287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:11.001287Z digest=sha256:aa95f2cd75de95b6ace2221af4020e01dd6c4ef3cc5eb2b3bd503b21903af611

Observation 4475a227-981b-41db-b94f-941730a4c379 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Constitutional AI: Harmlessness from AI Feedback

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-09T06:04:11.019163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:11.019163Z digest=sha256:980294cc7947346a368d01f1347049a8bfe35b2ae5d6abf6034bae74f836ce46

Observation 1570477b-7ca3-4032-87d7-fdae1618a21d · outbound

This paper cites Rlaif vs.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Rlaif vs

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.582702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:11.022379Z digest=sha256:9a6b85bdf1b40ae75257311b5d8809e5c8d0c40ca15882d4cdeb7151be534f11

Observation c314b9c4-5740-4200-a21f-44fb595d84ad · outbound

This paper cites Aligning Large Multimodal Models with Factually Augmented RLHF.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Aligning Large Multimodal Models with Factually Augmented RLHF

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-09T06:04:11.024998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:11.024998Z digest=sha256:df30d3614c9e962a1b3870f5553451b193c3c0a4a8f5076968fe4fa3501023da

Observation 877df5ee-1a89-45df-8031-983c5f7e57b2 · outbound

This paper cites Rlhf-v: Towards trustworthy mllms via behavior alignment from fine-grained correctional human feedback.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Rlhf-v: Towards trustworthy mllms via behavior alignment from fine-grained correctional human feedback

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.574902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:11.027164Z digest=sha256:6be266b9530d628de0007b93eb4b0d9c5362127910714306d958e798cf1b3d9a

Observation b05e1e47-c13c-43f3-8d28-8ad17d391864 · outbound

This paper cites Rlaif-v: Aligning mllms through open-source ai feedback for super gpt-4v trustworthiness.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Rlaif-v: Aligning mllms through open-source ai feedback for super gpt-4v trustworthiness

Reference 85

Resolution
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no resolver link, observed 2026-08-09T06:04:11.029592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:11.029592Z digest=sha256:02b0759c49033af0382b8716ae390a12e2c9442a79c7260175e88f4a828517eb

Observation 64652286-8a36-4eb8-866c-da4a4a711518 · outbound

This paper cites Training Diffusion Models with Reinforcement Learning.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Training Diffusion Models with Reinforcement Learning

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-09T06:04:11.031891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:11.031891Z digest=sha256:a1bec132d70afdc350a6269266aabe776da61141ca9a40da0d6c92e20f7269be

Observation 5f1d21b8-bfe3-4b76-8532-3872521df782 · outbound

This paper cites Aligning Text-to-Image Models using Human Feedback.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Aligning Text-to-Image Models using Human Feedback

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-09T06:04:11.034619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:11.034619Z digest=sha256:83232c3a55a694b00dc7e416f0489a2c36de8db687e290aaa05bf4ee69e05472

Observation 2d73b3a4-2d20-4bdb-aeff-30b882c65199 · outbound

This paper cites Directly Fine-Tuning Diffusion Models on Differentiable Rewards.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Directly Fine-Tuning Diffusion Models on Differentiable Rewards

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-09T06:04:11.037395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:11.037395Z digest=sha256:fc01bb0cfff42df1f26f7f77465b66321d3f3093a83ef9a9554aa46c62bf3633

Observation a99b4757-76f5-4fc5-9348-51d28e3bff2c · outbound

This paper cites Reinforcement learning for fine-tuning text-to-image diffusion models.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Reinforcement learning for fine-tuning text-to-image diffusion models

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.547896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:11.039893Z digest=sha256:154369c575c3a4d994e38dccd3ea2b45872ce0cfedecb504226bd4c167f1a913

Observation 07f2a0ae-4353-4348-8944-d11ba1f14d5d · outbound

This paper cites Hive: Harnessing human feedback for instructional visual editing.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Hive: Harnessing human feedback for instructional visual editing

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.515329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:11.042995Z digest=sha256:f4bde2e1d5d0ec44967151db63aa5f37eee2c12223c7a537e278b6e074de7518

Observation aa82b1d3-e053-44a9-a849-97ea5c685929 · outbound

This paper cites Deep reinforcement learning from human preferences.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Deep reinforcement learning from human preferences

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.481709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:11.045398Z digest=sha256:6533c0002d9eab8fd2429ab9abf8187dcdf1b04ba9645006c9fe6cc86b957908

Observation 9f2f887a-dafd-4f66-b4a1-775658218e55 · outbound

This paper cites Training language models to follow instructions with human feedback.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Training language models to follow instructions with human feedback

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.449818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:11.048196Z digest=sha256:7d8bc8439f6e52d71f2c328828e4a04766855cf6fe8d7c837107ec7ada9a4788

Observation 1b47aadc-ccf4-4cc9-a9b6-d98c2f769afa · outbound

This paper cites qwen-vl-plus-latest.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization qwen-vl-plus-latest

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.441886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:11.051188Z digest=sha256:9e2ecfcc18c8a09b157511ae2c8ace2b5a7ef16e6201ea5c2a6123785363bcfd

Observation 99c29b5a-d31f-4472-b525-da944871f45c · outbound

This paper cites an unresolved cited work.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Unresolved cited work

Reference 94

Resolution
unresolved
raw_fallback, observed 2026-08-09T06:04:11.434373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:11.053585Z digest=sha256:2d33f7481b85487a2891144fadecce16c2168f93b268843f42423b1baaea1067

Observation c64fdcaf-7afe-43e3-bda2-6dfb7c918ea5 · outbound

This paper cites Yes” or “No.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Yes” or “No

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T06:04:11.426055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T06:04:11.056029Z digest=sha256:a013b140b2ad97b1db2068c55dfced264b47fc0acacb924dabbe3f89d61af615

Pith citing papers

Observation 71142e03-05df-428c-8bc1-c5e1e97b0b1f · inbound

MPO: Multilingual Safety Alignment via Reward Gap Optimization cites this paper.

MPO: Multilingual Safety Alignment via Reward Gap Optimization DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-07T14:57:34.760038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:57:34.760038Z digest=sha256:9e43c8757245dd6a081df98a2306d5ba2ca27c419f415476263f8f5eb3aa997d

Observation 1514486a-460e-40d4-8850-0f3272a64727 · inbound

Nabla-R2D3: Effective and Efficient 3D Diffusion Alignment with 2D Rewards cites this paper.

Nabla-R2D3: Effective and Efficient 3D Diffusion Alignment with 2D Rewards DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T23:57:17.326115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:57:17.326115Z digest=sha256:c11f1f8a8b97d44b2532fe4e123945ec7515ec866e1fb93279471387aae5dae6

Observation d7fb1b3d-f7db-4d26-b8ec-6c9ea6700b0e · inbound

Point Cloud Compression and Objective Quality Assessment: A Survey cites this paper.

Point Cloud Compression and Objective Quality Assessment: A Survey DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization

Reference 220

Resolution
unresolved
no resolver link, observed 2026-08-06T21:59:11.224541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:59:11.224541Z digest=sha256:8777310118840178a7f6330932292100a670000a4615e66385fc1cb4e7dc298e

Observation 2c0deb8e-0412-4b76-8e00-d3635f9230e3 · inbound

Let Language Constrain Geometry: Vision-Language Models as Semantic and Spatial Critics for 3D Generation cites this paper.

Let Language Constrain Geometry: Vision-Language Models as Semantic and Spatial Critics for 3D Generation DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-03T21:41:32.036892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:41:32.036892Z digest=sha256:1be7c1873f0159dccde9571b57fd8686e7dbaab0b8f656eb8a00196ec3739e9d

Observation 0d37ba46-624b-442c-b711-a7dc3b4ab0fa · inbound

BrickAnything: Geometry-Conditioned Buildable Brick Generation with Structure-Aware Tokenization cites this paper.

BrickAnything: Geometry-Conditioned Buildable Brick Generation with Structure-Aware Tokenization DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:14:00.105818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-29T22:08:51.292545Z digest=sha256:bbc3d9d13700da8edf549668cbdb6c038e3e69a92c563f756b93a974383f9770

Observation ced36b07-3fbb-415d-984c-12d9da5024f7 · inbound

A Cross-Model VLM-Judge Protocol for Single-Image 3D Mesh Quality (and Why Cheap Proxies Fall Short) cites this paper.

A Cross-Model VLM-Judge Protocol for Single-Image 3D Mesh Quality (and Why Cheap Proxies Fall Short) DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-07-03T21:08:58.189580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T00:54:57.489186Z digest=sha256:fd427edd671335bb3b5a8610ab79eb1ec19eb46c422bf2bade92c9e898222bc2

Observation 33897e9a-ca04-40ac-948c-ea8cefca8981 · inbound

Judging to Improve: A De-biased VLM-as-3D-Judge Protocol for Single-Image 3D Generation cites this paper.

Judging to Improve: A De-biased VLM-as-3D-Judge Protocol for Single-Image 3D Generation DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-07-04T03:09:29.454899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-26T18:25:45.000030Z digest=sha256:91a4f8ea4ca375ec2bbbd1e047ca6473a62a2fe74214e788e7f34ccff2893813