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Paper Citation Record · LEDGER

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

As of 10 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 2026-08-09T06:31:02.800959+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=sha256:6665d0543bf092691abfeeea11e549f3a9b9ac1f028639e622a1592add7c1980

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:e3f73c9bc7042ea1583d6f42357d5aea765c26ccf8c0da2d08651021ed3382c2

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:cb90b878fd2306b8b832dbb48a9dc573ba4b0eb98d949a4799d9edab30ce38bf

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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source=pdf_text observed=2026-08-09T06:04:10.743795Z digest=sha256:f123d42dfb983fc4dba462c21a7d7abf3527f3abf4375e080ff7372839603af0

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.746744Z digest=sha256:1746dc852caab330297fbf4a491421d8bd0da91195eba17a7a95d0c1388b4a23

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:bbf0992290a063ee4541797e85a1148f6a4a821a303cb11a6c9553dcbf9d38f0

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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no resolver link, observed 2026-08-09T06:04:10.752176Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.752176Z digest=sha256:9b66d4924f078957c0a76b7bd253d95a708373fee18f2e3b39dbc474e751de9a

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:db44ad1db695cac51bf0239ff2b58814a0a9e4359052e6d943a99691f3ca7f9c

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.757189Z digest=sha256:ae6588ad34278a1ffca5a5feb16d633c62abd034953e8288c555394be5bca7a3

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=sha256:1126e4818039ed8b4dde4b39b7bf387c66e6cac063dac406ad1c2fb0559bff9a

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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source=pdf_text observed=2026-08-09T06:04:10.761207Z digest=sha256:9f97621eb82732d65ebeca9533b68b8874e5c8aeb7b35397d8da7d85395e017e

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=sha256:74e99293fdc6645eb7ca61a4676432ff78af1039b1c2965c20625e0cd03751bf

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.765272Z digest=sha256:8d8070ca902ad5e2094ba91cd92114e1b903ba923d1f89aaa4db79969f515ece

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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source=pdf_text observed=2026-08-09T06:04:10.769503Z digest=sha256:f8176f76c62f8ed1e408fe5e6e0e31e6b3cd139bebf28eba1d8270b1ae3f5c05

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=sha256:92b11338ab1fa321d662db92215868ae0641145f2ec8a27a92a7af7dc36f3a07

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:bbcad79bb25f9899027ba5da726af89771cdc30ece9436847d459f6cfc8dbb10

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=sha256:9cb7c72d55f893816a09e2bc465fc269f4be7aa51ae2958ab6c4ef2d9ef1088d

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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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.781798Z digest=sha256:55a9223674ec11fdd623091ba787197ed81e70b67c75c2177be19d7e43961968

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=sha256:9dc4323178d6975aa3bdb260f254ef1ebe3a6455bee9a55a83d95c36227a7ff9

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
verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.786347Z digest=sha256:f9c3795b1014dfa658d9a07d74a58752c2141a321997910d1732de81b32b93fc

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=sha256:616c6608cb106ced6146f65349d82dc99ddd706488371a16d2f1c07f1816584f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.791273Z digest=sha256:d3960db59d1df3664f81d958e6305914d53a922a09be06b1820ac034c4d6268b

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:f315b13010f7e6cc8c438454b59ac185b4d1e015baacf937dd37d04fcd6866bf

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=sha256:8efa8e98ec104b7ecce4ed2fef2a074ffb84f05cdfc823ee26f9eef7843dc69f

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:ecdd4981cb50c3d8a2062d03eb461de902e3caedfd90a8f7ea5aaef828c4b202

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

Resolution
verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.801594Z digest=sha256:167d71a9f7536bffc77c4e78f52a9d8157cceb5c5b2dbdf65eafd6f0f79df353

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=sha256:513d0aba79e77615ace40f75718a30a000687fe9c120c4eb239c8804084023f3

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.806418Z digest=sha256:fbc67ecf5b0cca93d62d5423d880b509415cb24b768ca1080a3bf334b6e64ecd

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.808816Z digest=sha256:b128213f304c28677eb97dfe55e83bc6af6fa3af8cf8e9d648eb4d1666ea2f4f

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.811142Z digest=sha256:728b1cd347016c390105c082c3c8b50a3cd4377b6d24239bdf6d0f38725f9135

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=pdf_text observed=2026-08-09T06:04:10.813929Z digest=sha256:27098a6b27aa367624b1b2daa2dd6bdc145cc3fb32555b81aa7a2ab7f22b54b7

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.816347Z digest=sha256:53a5b2528c2e39bde3d47e60a5d939ea44501ebd9f0732aebc016980f97653cc

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.819032Z digest=sha256:806e1989241ea80e22e7679b2e877f4c4cdb03a1ad43ee25e42a96f4fd864c41

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.821193Z digest=sha256:ddd1db4515b7ef1cde6db6cb53eec5449d18bff044ab9f1044122db46d50ae38

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.823225Z digest=sha256:848e6cea9890a13dbacb90ecd126a8ccb0dfcc4c8a67ede16136d98863da3cad

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

Resolution
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no resolver link, observed 2026-08-09T06:04:10.825453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.825453Z digest=sha256:052c0d6b12e380ded1256ebc652ca8c8bd5163a9a7a7b61a5744d07db9a2167c

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
unresolved
no resolver link, observed 2026-08-09T06:04:10.827673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.827673Z digest=sha256:c1b7715f8f2793c3a782b2db0a35f1ac4f8ebbd758cb37317345120c9752d826

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

Resolution
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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=sha256:615d1e6f6bcddfa3f377f1616d5c23a16ac473db55b2003cba5ddcc63f2a0bb4

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
unresolved
no resolver link, observed 2026-08-09T06:04:10.833263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.833263Z digest=sha256:41af3a72455109cd955f7ff6b4ccf37754c459503ffd6d713123a8cdb1504fba

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.835287Z digest=sha256:ed5c3240c9c7f2a3eb9d952f7d9d36aa0665380126c5dce827b45bb4376a3469

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
unresolved
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=sha256:9d73ed712e4971fc0cd17f37b0bf5e07fb7157c18e9d1cf9bb5806008fcbfb23

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
unresolved
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=sha256:0dde3f835c0d7b3e2773826078b9ffd5b4b0c3d34a6a9d52ada9f0ba8bd4429a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.841657Z digest=sha256:c2d444b6290fbcb0cafee383cea941b68072b2d8ca285f04dd484434d3a4a708

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.844116Z digest=sha256:6310eff974fe531b907f16ccbb26e333785fa7c5db8a2d925342cf82dd2bac37

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.846472Z digest=sha256:686b19c591cf7edfed4ea5d2e821b3fce2e7e949da6284cdf6aab87728711edf

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.849140Z digest=sha256:7414c4534381844dae843f2d393994f3eef730957978cc19a572a202b9ad241e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.852336Z digest=sha256:9a745fc8986c9c91d320070e8580bf5378baf1e7510217192813c29bd54389c8

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.855611Z digest=sha256:c818507be51453fd9eea2ef655c3b2ada463a660e1fdee6188fdbe8123c9ca18

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.858334Z digest=sha256:e46a4f105d56135aa9a30790a29ae538265702f4445650b2443a9962b4d49033

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.861878Z digest=sha256:23e1691e2d3ec9f3fae8e8bf98a567d409ffa52649538ccfd5e50afe3591573b

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
unresolved
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=sha256:2aa5bb0ab18891948017c5aa46496ed0c0b0a24f3f57a4a24223a006d8023b71

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.867406Z digest=sha256:405855a2f0dd1e7720501bf628aec4022ce956119c1865bfae8c8a3e086ed9fc

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
unresolved
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=sha256:5477a7131227b942adfc5b3cb82f8f1b75140b4d0623f085a318494ef94f8172

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=sha256:23381dd42ff3b375568286b0d506caa676176382b4d90f00bb25861ce70ab328

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:ee3fd9ef2f34953ac5774963744ed1636c9a95002c7be7e8ca3d7d271b3debd3

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
unresolved
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:eb7b73cbda7f3584711cf79b5b8ef8145a70377d5e6c8a33432e26f64a3ebc5e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.881137Z digest=sha256:74a791a499444a4ab6330e94bb28e54dd9b2f0dd0f214ebb5126c205a3f455ff

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
unresolved
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=sha256:444ad0370ba14e0e016e1d1f521d7704eb876e266a4316446941602afcb33f1e

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:a318fd04f72c9555788bc81d0f7b383eb3d3a32555d879d343007f2c7ee58b27

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
unresolved
no resolver link, observed 2026-08-09T06:04:10.888953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.888953Z digest=sha256:a62352af223f5eba21eec76e9f2c1002163dc61777292e97e34f2a93045ca85c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.891707Z digest=sha256:6209775aca1dcab5c572fd43437f02eb05d267736986b1b01a15690f64659631

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.893939Z digest=sha256:a1702fa78b6037572760e7a74bac6df67c313d363aab2abd566f0001fc4a0a89

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.896256Z digest=sha256:17b5819883fc102d3add0425f18a4a4c834ec927608b146c9bc49fc44a76232d

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=sha256:4935025ead08ff788cbbafb595700b5b1a178331074476e1a5dc25d464493898

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=sha256:9e5b2a877103fbce843fd9fe13b094f5d9e47fc8273e34f480db42b024015589

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.903814Z digest=sha256:e219560726a9dc70e1e6634751eb520aaf09e641ae7d7d040a7c021be5ff4723

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.906081Z digest=sha256:7a248fc1ce2e012bbbbedba30d055787e5f8e6f1da45c0258168a80c6c82cf02

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.908126Z digest=sha256:04b1191e0db45d790668153b859f3d906862fe642972e9c31687c867ba59d02b

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.910444Z digest=sha256:41804f98f4d3a06b0a9e98bf28a8da894ce3231d6d2fc9669f18b8a2bc479513

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

Resolution
unresolved
no resolver link, observed 2026-08-09T06:04:10.913043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.913043Z digest=sha256:95465373c5087b458d7650071a0a60db4eac10351378eaf58dc2ea5379914ea4

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
unresolved
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=sha256:2baf714e29d3971a63d58672545d990f89109fc0ab063a931a9c88570de72280

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:10.926055Z digest=sha256:45a3b810cf7bb441c7843a002021c76b355c7b042d7b83b6f6735b55a9ee849d

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=sha256:07c0de5e58304f883c3715ded21f5b30b96e2d3b4ede48e299cb32a8559e4c15

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
unresolved
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:f5a2b1cd8e0ba091af8a1df206871aeb655fe0566265187969f5dd73f405956f

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
unresolved
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:bea13159a9c1b87708104875e974e48a1973ebfaca1f356261813ea3698b4153

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
unresolved
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=sha256:48bdfb81dfa4998f8680ce4990b10839bd5751de94c7cd9cfe290bf223c7a83d

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=sha256:388d10f42d05c139210133ad0db972ea8546a855df63975288760a55c8f70113

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=sha256:4e6ad15b053af0274c42fef52c5e7dce2e79ebf457c4d91565a3868cec1a234b

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:11.022379Z digest=sha256:a1af652b3d3474455971bd850bd7bfe6e99ba7c571b4767a9c1635ea7e57d02b

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=sha256:791ebb65edb2da24050aec38978d58ac4c3564e965601148315f115dc70d64c0

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:11.027164Z digest=sha256:13e9fc945e305e1e7538f409797aa4b97da52a57b039c8dbce9c36467c35671e

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
unresolved
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=sha256:1a959533a2baaf37584c236607a1b3b33a975d05a2e288bf38c534e7fe020dc7

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=sha256:03a10ef3460d3f7501419d9b76c9992468b7dfaa960cb684cb0e418048c8ac2c

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=sha256:241b7e3be9cec97a8bde3f3406ab029d9108e1ea9e5c7ebb92100c5593924010

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:e35095f8ff14f817052ec076e8a737ddda8fa00ad1fcce43d7cbeb76e21ccd62

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:11.039893Z digest=sha256:a85746d62d041f97d54860d8fd13e3829c42e69b2f1aa13ab43d7147e92ab12a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:11.042995Z digest=sha256:ad98ac0a36b1939d2d5a44321109f18ae03a28504c3a2520530b4cbbe3ff40ca

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:11.045398Z digest=sha256:672c164de371a1009dab4d146db075fa56d1de25ec424937cbe61c4ff43f80fe

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:11.048196Z digest=sha256:726acc94be83bf8b1b477a4ce62145559ef590b36c9f25a6bcd1f1920e148250

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:11.051188Z digest=sha256:fd7ebb3e0467bb730575d11751e8e1cab0bfe323dd22563efde366c4e2f656ec

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:11.053585Z digest=sha256:437a46278679e3eeca08d48b6fc3afca6238c5143f18430ae6fdb73c9ee791a4

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T06:04:11.056029Z digest=sha256:3549576c73c3a485f07a3cb5231fba0074e25e7b13c7ba2b7484a70642adadb9

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=sha256:43ae16734b908a8a64b04246e152a32e4ba097c3adadb60c280d7772ef49dfa8

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:d91ea392c5f4dc6ca8e414a408456be04351a7ae2e5fe9afe955855c75fdebd3

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=sha256:67b24758cc4ec675c8999684b4809a24051d2e3e01ddb7761b53d811d47fe016

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=sha256:80886883bf1122952dd9251fbd0b0408b92cb8af1e6e927d7bdb2d08e952a457

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T22:08:51.292545Z digest=sha256:f641a4d5962d25ddc40b3f1b142245558d301b951bf38998eeeb0cf11511a6fe

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T00:54:57.489186Z digest=sha256:9277fd46afbdf9af4245947acf4c741c5a8b2cca915f944bb90dc9e960814bf3

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T18:25:45.000030Z digest=sha256:d7b345288471f966aca1a6fac9d8bf61707fac9b12ab0eb88a78cb777c571c2f