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Paper Citation Record · LEDGER

MObI: Multimodal Object Inpainting Using Diffusion Models

As of 20 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 0 inbound Pith citation observations for arXiv:2501.03173.

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

pith.paper-citation-record.v1
2501.03173 v2

Coverage vector

measured 75 of 75 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:56:17.729124Z

measured 75 of 75 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

75 of 75 outbound references displayed

  • verified exact1
  • verified fuzzy35
  • unresolved38
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1ceea53d-45f1-43e7-9547-1a34f25c7fa8 · outbound

This paper cites Flamingo: a visual language model for few-shot learning.

MObI: Multimodal Object Inpainting Using Diffusion Models Flamingo: a visual language model for few-shot learning

Reference 1

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Unavailable: canonical work link unavailable.

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Observation f4abcf9c-9d23-4c5b-b5c3-5d1c2a1a0c9f · outbound

This paper cites Dynamiccity: Large-scale lidar gener- ation from dynamic scenes, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Dynamiccity: Large-scale lidar gener- ation from dynamic scenes, 2024

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation fb35b2a9-aae3-4e8b-800a-a074fb36f1a1 · outbound

This paper cites nuscenes: A multi- modal dataset for autonomous driving.

MObI: Multimodal Object Inpainting Using Diffusion Models nuscenes: A multi- modal dataset for autonomous driving

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3ec9a4be-7981-4aed-aa8c-fd2c93cab1de · outbound

This paper cites Just Add $100 More: Augmenting NeRF-based Pseudo-LiDAR Point Cloud for Resolving Class-imbalance Problem.

MObI: Multimodal Object Inpainting Using Diffusion Models Just Add $100 More: Augmenting NeRF-based Pseudo-LiDAR Point Cloud for Resolving Class-imbalance Problem

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 31a25eec-0050-4a4e-9db4-e487a5f2f5de · outbound

This paper cites AnyDoor: Zero-shot Object-level Image Customization.

MObI: Multimodal Object Inpainting Using Diffusion Models AnyDoor: Zero-shot Object-level Image Customization

Reference 5

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Observation e201e549-1cf1-4e75-b3f0-fe1a1fdbd46c · outbound

This paper cites Geosim: Realistic video sim- ulation via geometry-aware composition for self-driving.

MObI: Multimodal Object Inpainting Using Diffusion Models Geosim: Realistic video sim- ulation via geometry-aware composition for self-driving

Reference 6

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raw_fallback, observed 2026-08-10T21:56:18.920739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8ad4d6d2-fcae-4603-a6b5-7852b415057d · outbound

This paper cites Placing Objects in Context via Inpainting for Out-of-distribution Segmentation.

MObI: Multimodal Object Inpainting Using Diffusion Models Placing Objects in Context via Inpainting for Out-of-distribution Segmentation

Reference 7

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source=pdf_text observed=2026-08-10T21:56:17.383508Z digest=sha256:7b8f7a77772799a91b1eeca522097b0a0242e409e12013cd66f9c6177ec42919

Observation 8f35d35b-3f7f-490e-ae88-b43183191bf1 · outbound

This paper cites Cut, paste and learn: Surprisingly easy synthesis for instance de- tection.

MObI: Multimodal Object Inpainting Using Diffusion Models Cut, paste and learn: Surprisingly easy synthesis for instance de- tection

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.389496Z digest=sha256:8177edfd0d59b1c6f94dad0761dc1a48fe5ea9d40e681dd025db0d8ecd28db6c

Observation ec0dc077-5d3e-4b17-9400-1b2ac12adfd2 · outbound

This paper cites Taming transformers for high-resolution image synthesis.

MObI: Multimodal Object Inpainting Using Diffusion Models Taming transformers for high-resolution image synthesis

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.394991Z digest=sha256:ed0a63bc107555d86b72c099a90b49437d7dc6e6ee821b5a7e4a8dfbd6238eba

Observation 4a2d0f31-e302-4ae8-9474-f05098c7a7d3 · outbound

This paper cites MagicDrive: Street View Generation with Diverse 3D Geometry Control.

MObI: Multimodal Object Inpainting Using Diffusion Models MagicDrive: Street View Generation with Diverse 3D Geometry Control

Reference 10

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source=pdf_text observed=2026-08-10T21:56:17.400022Z digest=sha256:79d6f214c24a4a38d2a33c638325c6c8d942825376f4abb00f637d3b9127344d

Observation 30eb62cf-3d8e-4c71-a58c-5b2e5a22511e · outbound

This paper cites Multitest: Physical-aware object insertion for testing multi-sensor fusion perception systems.

MObI: Multimodal Object Inpainting Using Diffusion Models Multitest: Physical-aware object insertion for testing multi-sensor fusion perception systems

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.405681Z digest=sha256:aee0a2c2d85d5be22eacfef7b5eaae55041bb45e9de0d7ef3e7421d8d76ea5c9

Observation 92d1b274-6a43-4751-ade1-031c7dccfe12 · outbound

This paper cites Synthesizing Training Data for Object Detection in Indoor Scenes.

MObI: Multimodal Object Inpainting Using Diffusion Models Synthesizing Training Data for Object Detection in Indoor Scenes

Reference 12

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source=pdf_text observed=2026-08-10T21:56:17.410637Z digest=sha256:81554da7abe9976343f22e7b993f63ee9db5457b6c34fa84b5840aee81780926

Observation 8c3a3708-31af-4e60-805a-ccac02f07346 · outbound

This paper cites Sim- ple copy-paste is a strong data augmentation method for in- stance segmentation.

MObI: Multimodal Object Inpainting Using Diffusion Models Sim- ple copy-paste is a strong data augmentation method for in- stance segmentation

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.415762Z digest=sha256:0a161c854518a447c3c3620592768d87fcc08517d1d632a2542fdd0a7fa1a688

Observation d65d071e-b193-48e9-ae1e-737705f845f8 · outbound

This paper cites Generative adversarial nets.

MObI: Multimodal Object Inpainting Using Diffusion Models Generative adversarial nets

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.420544Z digest=sha256:28ddb596825311fe86e91ef0b22ca04d1c24a67c2f29adbe6c16a0dc32ef3957

Observation 3ad0f58f-248b-490b-94a0-b992e527141e · outbound

This paper cites Lift-attend-splat: Bird’s-eye-view camera-lidar fusion using transformers, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Lift-attend-splat: Bird’s-eye-view camera-lidar fusion using transformers, 2024

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.836102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.425270Z digest=sha256:e6345ed8960261da845c788a8a82e9dfa5d53f26dd4106287313ba514c6d22b3

Observation ea9c71a9-1651-4e93-a135-1f6b7c18751e · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.

MObI: Multimodal Object Inpainting Using Diffusion Models Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 16

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Unavailable: canonical work link unavailable.

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Observation 983f6922-7551-43d9-9ae9-d78abcdf0186 · outbound

This paper cites Classifier-Free Diffusion Guidance.

MObI: Multimodal Object Inpainting Using Diffusion Models Classifier-Free Diffusion Guidance

Reference 17

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Observation 37b2e307-75ba-444d-8961-ed5250f7f0c7 · outbound

This paper cites Denoising dif- fusion probabilistic models.

MObI: Multimodal Object Inpainting Using Diffusion Models Denoising dif- fusion probabilistic models

Reference 18

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Observation 436074c9-675a-4c56-b87e-7b7892636228 · outbound

This paper cites Rangeldm: Fast realistic lidar point cloud generation, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Rangeldm: Fast realistic lidar point cloud generation, 2024

Reference 19

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raw_fallback, observed 2026-08-10T21:56:18.799535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ed158624-8ff3-4fef-9e97-029e44d57853 · outbound

This paper cites Subjectdrive: Scaling generative data in autonomous driving via subject control, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Subjectdrive: Scaling generative data in autonomous driving via subject control, 2024

Reference 20

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raw_fallback, observed 2026-08-10T21:56:18.783984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation b3bb0344-3905-4d37-9ecb-04d4dc72dd0a · outbound

This paper cites Auto-Encoding Variational Bayes.

MObI: Multimodal Object Inpainting Using Diffusion Models Auto-Encoding Variational Bayes

Reference 21

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source=pdf_text observed=2026-08-10T21:56:17.459541Z digest=sha256:0988b5ab282dbe855a389253a8e9871769e7c5b35a0d1bd741b9a9f0a9ca4ce1

Observation 6d0a0da8-d37c-49eb-b21e-6953b82b0639 · outbound

This paper cites Logen: Toward lidar object generation by point dif- fusion.

MObI: Multimodal Object Inpainting Using Diffusion Models Logen: Toward lidar object generation by point dif- fusion

Reference 22

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.464824Z digest=sha256:31640c507595854c418005ed7a8b45c1bdcd79e9523c5536761ab37edec8d7e4

Observation 469240ef-56a3-4c90-a5d3-0b3fc5e762ac · outbound

This paper cites Segment Anything.

MObI: Multimodal Object Inpainting Using Diffusion Models Segment Anything

Reference 23

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Observation ce39912a-5252-4f2b-8467-5745d75a6a81 · outbound

This paper cites Challenges in au- tonomous vehicle testing and validation.

MObI: Multimodal Object Inpainting Using Diffusion Models Challenges in au- tonomous vehicle testing and validation

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 57ba7a44-af7f-4f18-864f-492a9073bcfb · outbound

This paper cites Efros, and Krishna Kumar Singh.

MObI: Multimodal Object Inpainting Using Diffusion Models Efros, and Krishna Kumar Singh

Reference 25

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raw_fallback, observed 2026-08-10T21:56:18.750128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 305a4560-28a1-47e8-9f8d-6fd3348fcea6 · outbound

This paper cites Lift3d: Synthesize 3d training data by lift- ing 2d gan to 3d generative radiance field.

MObI: Multimodal Object Inpainting Using Diffusion Models Lift3d: Synthesize 3d training data by lift- ing 2d gan to 3d generative radiance field

Reference 26

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raw_fallback, observed 2026-08-10T21:56:18.734014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.485834Z digest=sha256:a2fb95ed68bddb8a4b263d2120aebdbbf655ec7511eb04a6d07399b508a8b81e

Observation 0c6e2faf-b88d-48fc-85af-79861b4d160e · outbound

This paper cites DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model.

MObI: Multimodal Object Inpainting Using Diffusion Models DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.492015Z digest=sha256:42bf4026934bc35e826cae33243309befa89b5894c6b8e3546d068fac6c4df42

Observation 1b1ec102-21be-4c96-8731-f664d3ade34e · outbound

This paper cites Exploring geometric consistency for monocular 3d object detection.

MObI: Multimodal Object Inpainting Using Diffusion Models Exploring geometric consistency for monocular 3d object detection

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.718662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.497164Z digest=sha256:78d97d8a4df36c38705547f4f1387f187ffaaa6efb545e24ab5d7d94027f9aa6

Observation 8cba1310-bb21-4f93-96b8-83092fb11df3 · outbound

This paper cites Bevfusion: A simple and robust lidar-camera fusion framework, 2022.

MObI: Multimodal Object Inpainting Using Diffusion Models Bevfusion: A simple and robust lidar-camera fusion framework, 2022

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.703286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.501798Z digest=sha256:7a91005183c7cfc13118c3393b28e2d42e476912160ce6b0885d5c917baaa004

Observation bd5ac471-f523-4d4e-a305-bd178c5025ca · outbound

This paper cites Drive-1-to-3: Enriching Diffusion Priors for Novel View Synthesis of Real Vehicles.

MObI: Multimodal Object Inpainting Using Diffusion Models Drive-1-to-3: Enriching Diffusion Priors for Novel View Synthesis of Real Vehicles

Reference 30

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.506321Z digest=sha256:439f688deb7589172a0ec1366693a4270156cc702d8c468690cef97654824feb

Observation 4534147c-cd8d-4643-ae89-6b68568a61f3 · outbound

This paper cites St-gan: Spatial transformer generative adversarial networks for image compositing.

MObI: Multimodal Object Inpainting Using Diffusion Models St-gan: Spatial transformer generative adversarial networks for image compositing

Reference 31

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raw_fallback, observed 2026-08-10T21:56:18.687570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.511348Z digest=sha256:1e91a9d54552b47bb7dd9939f6dda6f4dd7f52c98b62b47994314c47353683e2

Observation c4a100ad-469f-47bd-8c4d-59c2b2b75c05 · outbound

This paper cites Pseudo Numerical Methods for Diffusion Models on Manifolds.

MObI: Multimodal Object Inpainting Using Diffusion Models Pseudo Numerical Methods for Diffusion Models on Manifolds

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.515918Z digest=sha256:ce5f93524d1cfc3625d8a2f91b46d08daa9610ec66fe8575b3fa10bc3814b948

Observation 5cc4de9a-98f5-477b-9760-a1dbc497e3e0 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

MObI: Multimodal Object Inpainting Using Diffusion Models Swin transformer: Hierarchical vision transformer using shifted windows

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.520841Z digest=sha256:e3ba1a9d6a330aadb03815cb5c22e5980a4c2638c61529eeb535febc1a84c588

Observation 947cbaf7-2362-426e-be74-cc04beb84f60 · outbound

This paper cites Bevfusion: Multi- task multi-sensor fusion with unified bird’s-eye view repre- sentation.

MObI: Multimodal Object Inpainting Using Diffusion Models Bevfusion: Multi- task multi-sensor fusion with unified bird’s-eye view repre- sentation

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.660617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.526282Z digest=sha256:07cc503a5d17477797b5f04c1fa74575ba95bc3cf276bad70268d9d01f8f6af1

Observation eb6f9c65-cd49-431c-93d1-e6f4b1af338f · outbound

This paper cites Wovogen: World volume-aware diffusion for con- trollable multi-camera driving scene generation.

MObI: Multimodal Object Inpainting Using Diffusion Models Wovogen: World volume-aware diffusion for con- trollable multi-camera driving scene generation

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.643099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.531152Z digest=sha256:083edb25c467f87ac3fad9650d1e1e5f8a2c644da028452b1dfda25beb30f065

Observation 330b05a6-59ac-4f91-bc63-8efbfdb0bec9 · outbound

This paper cites Object 3dit: Language-guided 3d-aware image editing.

MObI: Multimodal Object Inpainting Using Diffusion Models Object 3dit: Language-guided 3d-aware image editing

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.627260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.535766Z digest=sha256:e09e4c9d8779a1a1208b0a5833e2e923d1f0fc78f6fc588551cdcdab4679cfe5

Observation fafdc0b9-2a18-4561-a9e1-f6b40e99318d · outbound

This paper cites Simple open-vocabulary object detection.

MObI: Multimodal Object Inpainting Using Diffusion Models Simple open-vocabulary object detection

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.611089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.540178Z digest=sha256:d6136c9064bdefb2e494da29f3194128cdcef66303e537c87295e73db7c8b9ed

Observation 53f19588-67f1-4955-ac9b-25a2b6aeee54 · outbound

This paper cites Lidar data synthe- sis with denoising diffusion probabilistic models.

MObI: Multimodal Object Inpainting Using Diffusion Models Lidar data synthe- sis with denoising diffusion probabilistic models

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.594970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.544722Z digest=sha256:3f9b453bebc2f0c330f388b61411e9b5e2d266ee6a074fdb08b267cb324309f3

Observation c97af81a-6df5-44d2-8414-c288a6e09f4b · outbound

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

MObI: Multimodal Object Inpainting Using Diffusion Models DINOv2: Learning Robust Visual Features without Supervision

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.549185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.549185Z digest=sha256:d463812972e5b74e54ba4a4317e46ae53dfcf85e3f71d7bd4765d3d0ca75009c

Observation f3004938-7190-4940-b9f2-aa7548a7cfea · outbound

This paper cites Diffusion handles enabling 3d edits for diffusion models by lifting ac- tivations to 3d.

MObI: Multimodal Object Inpainting Using Diffusion Models Diffusion handles enabling 3d edits for diffusion models by lifting ac- tivations to 3d

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.579070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.554266Z digest=sha256:8891ee85e54ff8797f540dc956928f21d59a96f0aacc7d00d81691570cf2f8c5

Observation 2a8a809b-dd46-4af4-bcec-c7e84c6a3953 · outbound

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

MObI: Multimodal Object Inpainting Using Diffusion Models Learning transferable visual models from natural language supervi- sion

Reference 41

Resolution
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no resolver link, observed 2026-08-10T21:56:17.559048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.559048Z digest=sha256:c61651cb4353963083de1ebb70bcc223625eb28f548970e90a30bd6812da3f85

Observation d7455579-c92b-463d-b441-42ff75dd0ba9 · outbound

This paper cites Towards realistic scene generation with lidar diffusion models, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Towards realistic scene generation with lidar diffusion models, 2024

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.552088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.563815Z digest=sha256:2a02943f29d6edda732f7b40470eb8cc05251660df13e3f1f921342485b0acc9

Observation beecb48a-36d5-4b79-a2f4-c45bb384afcf · outbound

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

MObI: Multimodal Object Inpainting Using Diffusion Models High-resolution image synthesis with latent diffusion models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.568755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.568755Z digest=sha256:40fe028d65b5270b579040c5e9a6fdbe42f8a2eec4c691dd133e5e34f8308218

Observation 90dabf68-a43d-4733-a263-333de67b95c9 · outbound

This paper cites U- net: Convolutional networks for biomedical image segmen- tation.

MObI: Multimodal Object Inpainting Using Diffusion Models U- net: Convolutional networks for biomedical image segmen- tation

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.523057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.573468Z digest=sha256:640ecd06198c8f571f113fb74117af9b9b7ae0f09040ddf0e7ec7bbd54f3d92b

Observation 222f795f-7ebd-4a5f-8140-c38329b3e780 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation.

MObI: Multimodal Object Inpainting Using Diffusion Models Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.578145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.578145Z digest=sha256:a14a74d23ab3d47965dbcd4fe1a0c3128ad65ccfdde21f22e9c75fa02fb17e0f

Observation 7b9346af-f29a-4326-9a0c-1e3cf40e6e7f · outbound

This paper cites Jacobs, and Shlomi Fruchter.

MObI: Multimodal Object Inpainting Using Diffusion Models Jacobs, and Shlomi Fruchter

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.496931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.582708Z digest=sha256:c721608831ac6e13f3245c08e17d4a2c17f9b1815c905291223826311ce3cdd7

Observation 37a1e6ee-553c-432b-8264-148279880619 · outbound

This paper cites GenMM: Geometrically and Temporally Consistent Multimodal Data Generation for Video and LiDAR.

MObI: Multimodal Object Inpainting Using Diffusion Models GenMM: Geometrically and Temporally Consistent Multimodal Data Generation for Video and LiDAR

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.587143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.587143Z digest=sha256:278e5234c50801f49455b2228ec47a805f52695348b28be3dc1fc106641f8b8a

Observation 7ef3ab6c-4993-4be2-98bd-f9fdd66848c1 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

MObI: Multimodal Object Inpainting Using Diffusion Models Deep unsupervised learning using nonequilibrium thermodynamics

Reference 48

Resolution
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no resolver link, observed 2026-08-10T21:56:17.592439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.592439Z digest=sha256:d38713bcd966df8b6193cda11ea61c2f27887cc242b25506febb23bcb31e211b

Observation 568ec495-6ffc-4b02-af33-562f1e8a35c5 · outbound

This paper cites Object- stitch: Object compositing with diffusion model.

MObI: Multimodal Object Inpainting Using Diffusion Models Object- stitch: Object compositing with diffusion model

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.470970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.597296Z digest=sha256:3bad4952fdc88fac3604fea1c487b9c7ceb0d980d45d47e7679f6ebf4956f93f

Observation a0e115f2-baca-4447-ae38-1fe82fbac054 · outbound

This paper cites Text2Street: Controllable Text-to-image Generation for Street Views.

MObI: Multimodal Object Inpainting Using Diffusion Models Text2Street: Controllable Text-to-image Generation for Street Views

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.602604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.602604Z digest=sha256:9c4624f8fe64fe5f1665c727ddd1e5fa1592876023db4dab2265f6ac2052c486

Observation b7f0b73f-2569-4807-a59f-ad57ab385ce9 · outbound

This paper cites Neurad: Neural rendering for autonomous driving.

MObI: Multimodal Object Inpainting Using Diffusion Models Neurad: Neural rendering for autonomous driving

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.454725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.608291Z digest=sha256:b42b2bcfbf2f36867ba1bf8e718464bc118aa70c72b86c4069747ed8d497d04a

Observation 599c6803-bec8-40f5-b11f-b33c0c77a246 · outbound

This paper cites Pointaugmenting: Cross-modal augmentation for 3d object 10 detection.

MObI: Multimodal Object Inpainting Using Diffusion Models Pointaugmenting: Cross-modal augmentation for 3d object 10 detection

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.439052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.613252Z digest=sha256:3b94948e9245c60c1d93434735d334cb3509a47929d2b371d22a73343d732c27

Observation 115f6f95-5471-4827-bfa8-a5ddae4f70af · outbound

This paper cites CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulation.

MObI: Multimodal Object Inpainting Using Diffusion Models CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulation

Reference 53

Resolution
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no resolver link, observed 2026-08-10T21:56:17.618547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.618547Z digest=sha256:e6cf4b004e9b89eb6d07fc0ca3f05dd7676cfbc71c82ea9d1b1495847c2d9786

Observation 0c073766-6195-4621-9bdf-8778ccfbd337 · outbound

This paper cites Diffusion models are geometry critics: Single image 3d editing using pre-trained diffusion priors.

MObI: Multimodal Object Inpainting Using Diffusion Models Diffusion models are geometry critics: Single image 3d editing using pre-trained diffusion priors

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.423916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.623800Z digest=sha256:be18ce6d9103d4fc7b09f20d0fd57d43c399d0cf14d67b9ff2fea15127a4cd05

Observation 999e3ac6-500f-405f-9d76-745c245996f3 · outbound

This paper cites an unresolved cited work.

MObI: Multimodal Object Inpainting Using Diffusion Models Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-10T21:56:18.409145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.629079Z digest=sha256:a311b68c890bbb33db8886d5cfc519088af55c8f092bf25dceb42ec0f9b5afd3

Observation 485b0ec7-a3d4-465a-ac3b-ef7c8ae90c12 · outbound

This paper cites Editable scene simulation for autonomous driving via collaborative llm-agents.

MObI: Multimodal Object Inpainting Using Diffusion Models Editable scene simulation for autonomous driving via collaborative llm-agents

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.393597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.633886Z digest=sha256:57d337ab115cc470f1127adb5c0a24e111e1f8662e9a6752ce63d3d57eaf68b4

Observation 717efe7c-fe03-4adf-a795-f1a0ec67116b · outbound

This paper cites Panacea: Panoramic and Controllable Video Generation for Autonomous Driving.

MObI: Multimodal Object Inpainting Using Diffusion Models Panacea: Panoramic and Controllable Video Generation for Autonomous Driving

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.638566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.638566Z digest=sha256:1c71bda63ecefe99bd363f91d1af2a5e61b557b6623ce4a983de7ee1c2ada165

Observation 34474a9c-4138-4a52-96e3-3dcda596dad1 · outbound

This paper cites Objectdrop: Bootstrap- ping counterfactuals for photorealistic object removal and in- sertion, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Objectdrop: Bootstrap- ping counterfactuals for photorealistic object removal and in- sertion, 2024

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.376127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.643562Z digest=sha256:c31ef46977274f33a964f0c626cab042e5d81f23187883cbb9e02ce21d05965e

Observation be6f34f1-6593-483f-ab7a-ef1d941dd7d6 · outbound

This paper cites Drivescape: To- wards high-resolution controllable multi-view driving video generation, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Drivescape: To- wards high-resolution controllable multi-view driving video generation, 2024

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.358909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.648768Z digest=sha256:90e1ab7f52d9ead709204de810541b0a7155e4f448a8d3083d3432c59373ab81

Observation 49e66a03-0e25-4810-a4aa-ed2458aeffa1 · outbound

This paper cites Neural Assets: 3D-Aware Multi-Object Scene Synthesis with Image Diffusion Models.

MObI: Multimodal Object Inpainting Using Diffusion Models Neural Assets: 3D-Aware Multi-Object Scene Synthesis with Image Diffusion Models

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.654761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.654761Z digest=sha256:997d44a8858b17f64fb229222aacc1631e2aa55e04a2d81e5e7e9bb819720c99

Observation 03fbc3cc-656a-4eb3-8746-be76fdde7f8c · outbound

This paper cites Synthetic lidar point cloud generation using deep gen- erative models for improved driving scene object recogni- tion.

MObI: Multimodal Object Inpainting Using Diffusion Models Synthetic lidar point cloud generation using deep gen- erative models for improved driving scene object recogni- tion

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.341392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.660051Z digest=sha256:f02600a8212bfb9faecf7d9abc97257bef8f41c98cee8125fc6e84ea626dc599

Observation c5a06afd-1698-42a5-8614-2d27e2250f53 · outbound

This paper cites X-Drive: Cross-modality consistent multi-sensor data synthesis for driving scenarios.

MObI: Multimodal Object Inpainting Using Diffusion Models X-Drive: Cross-modality consistent multi-sensor data synthesis for driving scenarios

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.665000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.665000Z digest=sha256:4fa9584c66af3f17907fa55f6ac5af4ede9cc2ce5980b56988581ae5f4016034

Observation 288e9a4c-977f-4364-ba3f-b1a77c14b761 · outbound

This paper cites Ultralidar: Learning compact representations for lidar completion and generation, 2023.

MObI: Multimodal Object Inpainting Using Diffusion Models Ultralidar: Learning compact representations for lidar completion and generation, 2023

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.325513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.670311Z digest=sha256:266f58ee3634a9953920b5a661f8ce4a80d1a19c5e977c8e5ba1a3298232d38f

Observation b831dfac-4cf9-4b0a-85b1-23889abe4ff3 · outbound

This paper cites Second: Sparsely embed- ded convolutional detection.

MObI: Multimodal Object Inpainting Using Diffusion Models Second: Sparsely embed- ded convolutional detection

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.309824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.675148Z digest=sha256:441c6eea19506f4294e0b989af48db1def54161a365f165f671faeabeb377e29

Observation 213ebdca-53de-46ac-8a36-3dc3c9b00eb3 · outbound

This paper cites Paint by example: Exemplar-based image editing with diffusion mod- els.

MObI: Multimodal Object Inpainting Using Diffusion Models Paint by example: Exemplar-based image editing with diffusion mod- els

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.680003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.680003Z digest=sha256:a01f917789731cd6ba00f54ac349c32913869011d4f37e12ecb597c130ee644f

Observation 4859d704-e15c-442a-9548-35b8abd91afb · outbound

This paper cites BEVControl: Accurately Controlling Street-view Elements with Multi-perspective Consistency via BEV Sketch Layout.

MObI: Multimodal Object Inpainting Using Diffusion Models BEVControl: Accurately Controlling Street-view Elements with Multi-perspective Consistency via BEV Sketch Layout

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.685225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.685225Z digest=sha256:36fac32c672e4096f0be9868aca1efa53e3f11765b4c9f1f401ce7a433c79f48

Observation 50ea3ab9-1c21-4998-80da-c29459aa7a8e · outbound

This paper cites Unisim: A neural closed-loop sensor simulator.

MObI: Multimodal Object Inpainting Using Diffusion Models Unisim: A neural closed-loop sensor simulator

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.690608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.690608Z digest=sha256:e8476cc32714a3797659fdf38b87dacc6cf788a7ad051ff2c8100896122e7553

Observation 8a159840-ff0e-4713-a2d8-732730d85113 · outbound

This paper cites Image sculpting: Precise ob- ject editing with 3d geometry control.

MObI: Multimodal Object Inpainting Using Diffusion Models Image sculpting: Precise ob- ject editing with 3d geometry control

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.695789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.695789Z digest=sha256:1dfdd0f0e23694f8a46f8e9547e8a018027770a4c4597213bd16ad4e66e23f25

Observation 71297ca1-1fc4-4c5e-aa62-82bc5664404c · outbound

This paper cites CustomNet: Zero-shot Object Customization with Variable-Viewpoints in Text-to-Image Diffusion Models.

MObI: Multimodal Object Inpainting Using Diffusion Models CustomNet: Zero-shot Object Customization with Variable-Viewpoints in Text-to-Image Diffusion Models

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.700708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.700708Z digest=sha256:7ba5cd7d39117f5356ef9070f66185d585b7c6030793a7fde82f49189d013e43

Observation dd182fbb-1323-4358-8e89-a5c0f121f271 · outbound

This paper cites Cutmix: Regu- larization strategy to train strong classifiers with localizable features.

MObI: Multimodal Object Inpainting Using Diffusion Models Cutmix: Regu- larization strategy to train strong classifiers with localizable features

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.705609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.705609Z digest=sha256:75697c9835de4e99e106eb52098523c075a025af1a24fd31fe1239a5e0d4afa3

Observation d401580e-7a4f-49cf-8029-b6641e72d82a · outbound

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

MObI: Multimodal Object Inpainting Using Diffusion Models Adding conditional control to text-to-image diffusion models

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:56:18.252192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:56:17.710394Z digest=sha256:083c215c4714361e55c11bfef92e5f02452133a557fe3d08bd3c3e8d7ce3092a

Observation 5948a2db-566b-478e-9d15-69a47fb94106 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

MObI: Multimodal Object Inpainting Using Diffusion Models The unreasonable effectiveness of deep features as a perceptual metric

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.714885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.714885Z digest=sha256:7baa4d2b38055aef53a8a76405dcd32621c3089b383d45890b3fd2da4cbd2013

Observation 87f578b1-96b1-48c8-a829-cbbe8dd1c479 · outbound

This paper cites Exploring Data Augmentation for Multi-Modality 3D Object Detection.

MObI: Multimodal Object Inpainting Using Diffusion Models Exploring Data Augmentation for Multi-Modality 3D Object Detection

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.719381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 91af7488-f78d-4083-b10b-2e4b0d54dfd9 · outbound

This paper cites Scene-Conditional 3D Object Stylization and Composition.

MObI: Multimodal Object Inpainting Using Diffusion Models Scene-Conditional 3D Object Stylization and Composition

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:17.724151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:17.724151Z digest=sha256:72be9677e64f16d1c8dc78e273832cc3ab20be9aac5c9d9e57ce77f48a54c649

Observation 773076ce-60f6-4c5b-b9f5-e615be42e263 · outbound

This paper cites Learning to generate realistic lidar point clouds, 2022.

MObI: Multimodal Object Inpainting Using Diffusion Models Learning to generate realistic lidar point clouds, 2022

Reference 75

Resolution
malformed identifier
raw_fallback, observed 2026-08-10T21:56:18.225686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Pith citing papers

No inbound Pith citation observations are available.