Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop | Paper Citation Record

Observation 4e0b955b-a324-4a2b-924d-dfa366547f99 · outbound

This paper cites Claude 3.5 sonnet, 2024.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Claude 3.5 sonnet, 2024

Reference 1

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Observation 429afd48-6d0a-4214-af27-db9bc1c5e853 · outbound

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

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 2

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Observation 1c3f1333-78b1-4aa8-81a4-80bbbc9eabb9 · outbound

This paper cites Align your latents: High-resolution video synthesis with la- tent diffusion models.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Align your latents: High-resolution video synthesis with la- tent diffusion models

Reference 3

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Observation ee774c63-aa5f-44e6-8ec3-90fbe6c1e087 · outbound

This paper cites Nodetopython.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Nodetopython

Reference 4

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Observation 6ab1b396-7d61-499c-a551-bdb0131cc0d9 · outbound

This paper cites Video generation models as world simulators.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Video generation models as world simulators

Reference 5

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Observation 474f2729-1ef6-4db4-a0b8-9f0d44144c85 · outbound

This paper cites Language Models are Few-Shot Learners.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Language Models are Few-Shot Learners

Reference 6

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Observation 85853686-2bfe-4406-b7f0-3300a032fbf8 · outbound

This paper cites A naturalistic open source movie for opti- cal flow evaluation.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop A naturalistic open source movie for opti- cal flow evaluation

Reference 7

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This paper cites Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Gi- ancarlo Baldan, and Oscar Beijbom.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Gi- ancarlo Baldan, and Oscar Beijbom

Reference 8

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Observation 52af7bf5-039c-430e-a52b-39b18d5b0b79 · outbound

This paper cites Coda: Col- laborative novel box discovery and cross-modal alignment for open-vocabulary 3d object detection.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Coda: Col- laborative novel box discovery and cross-modal alignment for open-vocabulary 3d object detection

Reference 9

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Observation 3992fc34-af5d-4058-a1cf-e50db22e042a · outbound

This paper cites VideoCrafter1: Open Diffusion Models for High-Quality Video Generation.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop VideoCrafter1: Open Diffusion Models for High-Quality Video Generation

Reference 10

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Observation 9b95e5eb-8399-4ade-87fa-b44835da3b5e · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Evaluating Large Language Models Trained on Code

Reference 11

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Observation c3f4ce76-579a-4426-a9d2-09fa05287af8 · outbound

This paper cites Blender - a 3D modelling and rendering package.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Blender - a 3D modelling and rendering package

Reference 12

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Observation e3b0837e-6f57-459b-b6fc-c3d3d8420913 · outbound

This paper cites Procthor: Large-scale embodied ai using procedural generation.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Procthor: Large-scale embodied ai using procedural generation

Reference 13

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Observation 60138d53-0fda-4576-b76d-dbb02aef2c3c · outbound

This paper cites Pla: Language-driven open- vocabulary 3d scene understanding.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Pla: Language-driven open- vocabulary 3d scene understanding

Reference 14

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Observation c404d304-0ce0-41c2-85c5-50f6aea6b5e4 · outbound

This paper cites The faiss library,.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop The faiss library,

Reference 15

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Observation 6c30c661-20a2-4fe8-8936-2c7b4589da87 · outbound

This paper cites Motsynth: How can synthetic data help pedestrian detection and tracking? In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 10849–10859, 2021.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Motsynth: How can synthetic data help pedestrian detection and tracking? In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 10849–10859, 2021

Reference 16

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Observation 33a67150-33f3-45c2-86e1-e6b51a6460b1 · outbound

This paper cites Large language models for code analysis: Do LLMs really do their job? In 33rd USENIX Security Symposium (USENIX Security 24) , pages 829–846, Philadelphia, PA, 2024.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Large language models for code analysis: Do LLMs really do their job? In 33rd USENIX Security Symposium (USENIX Security 24) , pages 829–846, Philadelphia, PA, 2024

Reference 17

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Observation 499c43f1-42fb-4228-9b4f-b453e3840134 · outbound

This paper cites Chat- edit-3d: Interactive 3d scene editing via text prompts.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Chat- edit-3d: Interactive 3d scene editing via text prompts

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.751617Z

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Observation 969ee485-bb9c-485c-9bdb-fb25acbae0fa · outbound

This paper cites Scenescape: Text-driven consistent scene generation.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Scenescape: Text-driven consistent scene generation

Reference 19

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Observation 0932d4c8-4758-4f77-bff2-fc077a2d6cfa · outbound

This paper cites Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoning.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoning

Reference 20

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Observation 2de56a9e-145c-48db-8c90-d185a31cb9b6 · outbound

This paper cites Retrieval-augmented generation for large language models: A survey, 2024.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Retrieval-augmented generation for large language models: A survey, 2024

Reference 21

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Observation 177f69b9-b3ee-4ac8-8141-9010bf2c68e3 · outbound

This paper cites Procedural model- ing of plant ecosystems maximizing vegetation cover.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Procedural model- ing of plant ecosystems maximizing vegetation cover

Reference 22

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Observation e2bf620b-c78f-45dd-959a-8f03d97ca2db · outbound

This paper cites StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text

Reference 23

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Observation 1e2642f4-5c35-4242-976c-683888ef329a · outbound

This paper cites Video dif- fusion models.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Video dif- fusion models

Reference 24

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Observation 2ec31712-300e-4a8f-8e97-ff60bd22cb14 · outbound

This paper cites CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers

Reference 25

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Observation 62e5d7c8-f027-4687-bced-0a175f48b241 · outbound

This paper cites An inverse procedural modeling pipeline for svbrdf maps.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop An inverse procedural modeling pipeline for svbrdf maps

Reference 26

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Observation a7a9e8fe-9296-4dad-aa8e-930b9b1f609d · outbound

This paper cites Generating procedural materials from text or image prompts.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Generating procedural materials from text or image prompts

Reference 27

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Observation 6eefcbae-b7af-463b-a0dc-464d95f16f38 · outbound

This paper cites Scenecraft: An llm agent for synthesizing 3d scenes as blender code.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Scenecraft: An llm agent for synthesizing 3d scenes as blender code

Reference 28

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Observation c805efab-2120-4447-9ea3-76328c9cc8ec · outbound

This paper cites VBench: Com- prehensive benchmark suite for video generative models.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop VBench: Com- prehensive benchmark suite for video generative models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.671058Z

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Observation 241183cb-7a56-40d0-854b-071a1d6aa9b1 · outbound

This paper cites Putting nerf on a diet: Semantically consistent few-shot view synthesis.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Putting nerf on a diet: Semantically consistent few-shot view synthesis

Reference 30

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Observation 79c212f0-9173-4eac-a29f-a315a72617bb · outbound

This paper cites Zero-shot text-guided object genera- tion with dream fields.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Zero-shot text-guided object genera- tion with dream fields

Reference 31

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Observation e9c50abc-5531-4aa5-8a30-5ac82721b9a8 · outbound

This paper cites Shap-e: Generating condi- tional 3d implicit functions, 2023.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Shap-e: Generating condi- tional 3d implicit functions, 2023

Reference 32

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Observation c4f428c0-9c6e-469e-8f86-eb9074169167 · outbound

This paper cites Clip-mesh: Gen- erating textured meshes from text using pretrained image- text models.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Clip-mesh: Gen- erating textured meshes from text using pretrained image- text models

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.638834Z

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Observation 7fbb4aaa-f38c-462d-af19-d1fc95f9443d · outbound

This paper cites Kling AI.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Kling AI

Reference 34

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Observation 2e196612-1c84-4548-968f-a164b465bb5b · outbound

This paper cites Understanding Pure CLIP Guidance for Voxel Grid NeRF Models.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Understanding Pure CLIP Guidance for Voxel Grid NeRF Models

Reference 35

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Observation b7887cc3-e62d-4809-8dbc-a2e1b1bf1940 · outbound

This paper cites Retrieval-augmented genera- tion for knowledge-intensive nlp tasks, 2021.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Retrieval-augmented genera- tion for knowledge-intensive nlp tasks, 2021

Reference 36

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Observation 3ef01c26-eec3-486a-b580-f74189161408 · outbound

This paper cites Loogle: Can long-context language models under- stand long contexts?, 2024.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Loogle: Can long-context language models under- stand long contexts?, 2024

Reference 37

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Observation d13f6431-dac3-473a-9bcf-85d068ed7a5e · outbound

This paper cites Uni3D-LLM: Unifying Point Cloud Perception, Generation and Editing with Large Language Models.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Uni3D-LLM: Unifying Point Cloud Perception, Generation and Editing with Large Language Models

Reference 38

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Observation d9a338da-ec81-475a-b035-6a7600001be8 · outbound

This paper cites What Makes Good In-Context Examples for GPT-$3$?.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop What Makes Good In-Context Examples for GPT-$3$?

Reference 39

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Observation 0629a79d-4538-42af-8938-49c8bcc5d158 · outbound

This paper cites Deep learning for procedural content generation.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Deep learning for procedural content generation

Reference 40

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Observation c530e454-bd4e-434c-a98d-820095b0946b · outbound

This paper cites A multimodal gen- erative ai copilot for human pathology.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop A multimodal gen- erative ai copilot for human pathology

Reference 41

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Observation 20f3fb42-7f38-4b79-9d41-3437e8bbda50 · outbound

This paper cites Ovir-3d: Open-vocabulary 3d in- stance retrieval without training on 3d data.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Ovir-3d: Open-vocabulary 3d in- stance retrieval without training on 3d data

Reference 42

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Observation 0c6bd81b-e898-42e8-b459-840983d909dc · outbound

This paper cites When llms step into the 3d world: A survey and meta-analysis of 3d tasks via multi-modal large language models.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop When llms step into the 3d world: A survey and meta-analysis of 3d tasks via multi-modal large language models

Reference 43

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Observation aa6ff910-867c-498e-a1d2-7e617f4523ef · outbound

This paper cites One Million Scenes for Autonomous Driving: ONCE Dataset.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop One Million Scenes for Autonomous Driving: ONCE Dataset

Reference 44

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Observation 75c98f74-21a1-4d88-866d-d8c7bbe263bd · outbound

This paper cites Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?

Reference 45

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Observation 51a79e46-658e-4238-a5df-47473e2a79b3 · outbound

This paper cites Hello gpt-4o.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Hello gpt-4o

Reference 46

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Observation 0d77cc97-9221-4cee-963b-4102636e98d2 · outbound

This paper cites Gpt-4o mini: advancing cost-efficient intelligence.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Gpt-4o mini: advancing cost-efficient intelligence

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.551335Z

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Observation cc83f082-d0bf-4aa2-9d8d-d9b60a586869 · outbound

This paper cites Infinite photore- alistic worlds using procedural generation.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Infinite photore- alistic worlds using procedural generation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.539053Z

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Observation 173c7417-6187-4002-ad2a-59641741db67 · outbound

This paper cites Infinigen indoors: Photorealistic in- door scenes using procedural generation.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Infinigen indoors: Photorealistic in- door scenes using procedural generation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.525888Z

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Observation 3d1acb60-6376-47bc-b999-8832970406ce · outbound

This paper cites Increasing generality in machine learning through procedural content generation.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Increasing generality in machine learning through procedural content generation

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.513086Z

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Observation 478941de-aef2-4533-9a53-0bd99da99620 · outbound

This paper cites Hypersim: A photorealistic syn- thetic dataset for holistic indoor scene understanding.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Hypersim: A photorealistic syn- thetic dataset for holistic indoor scene understanding

Reference 51

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Observation 4b5cdec3-c15e-43a5-83f0-b1251dc6c522 · outbound

This paper cites Code llama: Open foundation models for code, 2024.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Code llama: Open foundation models for code, 2024

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.493917Z

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Observation 7b823bd7-4367-4f03-aa06-53a2e83e4188 · outbound

This paper cites Procedu- ral content generation in games.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Procedu- ral content generation in games

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.481046Z

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Observation de1524a9-dd7a-4148-b71f-998cfd52479a · outbound

This paper cites Match: Differentiable material graphs for procedural mate- rial capture.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Match: Differentiable material graphs for procedural mate- rial capture

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-12T11:51:36.678247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2616dbfe-f1e9-4bc6-8bc3-98aba7f8bdfc · outbound

This paper cites 3d-gpt: Procedural 3d model- ing with large language models, 2024.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop 3d-gpt: Procedural 3d model- ing with large language models, 2024

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.461519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation de78d63d-ec34-4b9e-9083-1ced24b15702 · outbound

This paper cites From Sora What We Can See: A Survey of Text-to-Video Generation.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop From Sora What We Can See: A Survey of Text-to-Video Generation

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-12T11:51:36.686065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35c42830-7f81-4b6b-b2ab-a945fc0c9899 · outbound

This paper cites Minigpt-3d: Efficiently aligning 3d point clouds with large language models using 2d priors.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Minigpt-3d: Efficiently aligning 3d point clouds with large language models using 2d priors

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.449486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5e8ae297-a759-411a-9770-bb3739d1602d · outbound

This paper cites Plan2scene: Convert- ing floorplans to 3d scenes.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Plan2scene: Convert- ing floorplans to 3d scenes

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.437649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f5f5979b-2eb6-4602-b937-88dd4982242a · outbound

This paper cites ModelScope Text-to-Video Technical Report.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop ModelScope Text-to-Video Technical Report

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T11:51:36.697452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c7437bd-1edc-4ed2-a203-322ea7c6161b · outbound

This paper cites Embodiedscan: A holistic multi-modal 3d perception suite towards embodied ai.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Embodiedscan: A holistic multi-modal 3d perception suite towards embodied ai

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.424665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 53c526c2-ba5b-4e16-a0a2-fce03a11a694 · outbound

This paper cites LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-12T11:51:36.705105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13c5745f-5957-4fdf-9a45-66a25d844e47 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models, 2023.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Chain-of-thought prompting elicits reasoning in large language models, 2023

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.411351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 695716ce-a244-46b1-961b-36b4d7dd316d · outbound

This paper cites Using github copilot to solve simple programming problems.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Using github copilot to solve simple programming problems

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.398697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation dc20be2e-b9ae-47a5-896a-0dddb2693112 · outbound

This paper cites Gos: A large-scale annotated outdoor scene synthetic dataset.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Gos: A large-scale annotated outdoor scene synthetic dataset

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.387241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 125f1ea9-6c4e-4db1-873d-a3e5249dfef2 · outbound

This paper cites Sinnerf: Training neural radiance fields on complex scenes from a single image.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Sinnerf: Training neural radiance fields on complex scenes from a single image

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.375992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 768e3953-6da1-4251-a53a-d873a9ce1c8b · outbound

This paper cites Sketch2scene: Au- tomatic generation of interactive 3d game scenes from user’s casual sketches.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Sketch2scene: Au- tomatic generation of interactive 3d game scenes from user’s casual sketches

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T11:51:36.725637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff47d7b2-d3f4-4b38-9571-27fc760b2ef3 · outbound

This paper cites Regionplc: Regional point-language contrastive learning for open-world 3d scene understanding.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Regionplc: Regional point-language contrastive learning for open-world 3d scene understanding

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.363986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 93ea9d9f-29fc-4392-b60f-281b28568756 · outbound

This paper cites Physcene: Physically interactable 3d scene synthesis for embodied ai.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Physcene: Physically interactable 3d scene synthesis for embodied ai

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.351547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cf5818cf-29ff-4351-bad2-42eae1ddae56 · outbound

This paper cites pixelnerf: Neural radiance fields from one or few images.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop pixelnerf: Neural radiance fields from one or few images

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-12T11:51:36.737082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 742c0fce-3b61-41b4-92e6-a49e092886c0 · outbound

This paper cites Procedural modeling of rivers from single image to- ward natural scene production.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Procedural modeling of rivers from single image to- ward natural scene production

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.330862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 73389964-6bf4-4433-9121-0a6f28194f2d · outbound

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

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Text2nerf: Text-driven 3d scene generation with neu- ral radiance fields

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-12T11:51:36.744776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d8b72c9-1337-44e8-93b4-dc69c6df7172 · outbound

This paper cites SceneX: Procedural Controllable Large-scale Scene Generation.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop SceneX: Procedural Controllable Large-scale Scene Generation

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-12T11:51:36.748864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0320b56-3a70-4714-9721-461f07452cf9 · outbound

This paper cites Scenex:procedural control- lable large-scale scene generation via large-language mod- els, 2024.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Scenex:procedural control- lable large-scale scene generation via large-language mod- els, 2024

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.311271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ec822d50-6b77-41c7-95d2-dfb16a09b238 · outbound

This paper cites Llafs: When large language models meet few-shot segmentation.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Llafs: When large language models meet few-shot segmentation

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.298929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation aae77f5c-45bb-4943-9fb1-9538a2a013e6 · outbound

This paper cites Wayvescenes101: A dataset and benchmark for novel view synthesis in autonomous driving, 2024.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Wayvescenes101: A dataset and benchmark for novel view synthesis in autonomous driving, 2024

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.285566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3c717d97-202c-4d83-bec2-e08ee73f7471 · outbound

This paper cites an unresolved cited work.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Unresolved cited work

Reference 76

Resolution: unresolved; raw_fallback, observed 2026-08-12T11:51:37.274117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2ebce5d7-816f-4eba-8f24-1f1b9298a09e · outbound

This paper cites an unresolved cited work.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Unresolved cited work

Reference 77

Resolution: unresolved; raw_fallback, observed 2026-08-12T11:51:37.262767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ab4b681b-48d3-4f99-928c-e45bfe0700fc · outbound

This paper cites an unresolved cited work.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-12T11:51:37.251088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f839dd52-862c-40e8-9477-4d47b9822ad9 · outbound

This paper cites Important: The 〈thinking〉and 〈reflection〉sections are for your internal reasoning process only.

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Important: The 〈thinking〉and 〈reflection〉sections are for your internal reasoning process only

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:51:37.238608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Pith citing papers