Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T11:51:36.776949Z
Paper Citation Record · LEDGER
As of 13 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 0 inbound Pith citation observations for arXiv:2411.18644.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T11:51:36.776949Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
79 of 79 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 4e0b955b-a324-4a2b-924d-dfa366547f99 · outbound
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 1c3f1333-78b1-4aa8-81a4-80bbbc9eabb9 · outbound
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Observation 9b95e5eb-8399-4ade-87fa-b44835da3b5e · outbound
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Evaluating Large Language Models Trained on Code
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Observation c3f4ce76-579a-4426-a9d2-09fa05287af8 · outbound
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Blender - a 3D modelling and rendering package
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Observation e3b0837e-6f57-459b-b6fc-c3d3d8420913 · outbound
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Procthor: Large-scale embodied ai using procedural generation
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Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Pla: Language-driven open- vocabulary 3d scene understanding
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Observation c404d304-0ce0-41c2-85c5-50f6aea6b5e4 · outbound
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop The faiss library,
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Observation 6c30c661-20a2-4fe8-8936-2c7b4589da87 · outbound
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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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
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
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Observation 969ee485-bb9c-485c-9bdb-fb25acbae0fa · outbound
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
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoning
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Observation 2de56a9e-145c-48db-8c90-d185a31cb9b6 · outbound
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
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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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
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Video dif- fusion models
Reference 24
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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
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
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Reference 27
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Observation 6eefcbae-b7af-463b-a0dc-464d95f16f38 · outbound
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
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop VBench: Com- prehensive benchmark suite for video generative models
Reference 29
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Observation 241183cb-7a56-40d0-854b-071a1d6aa9b1 · outbound
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
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
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
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
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Observation 7fbb4aaa-f38c-462d-af19-d1fc95f9443d · outbound
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
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
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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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
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
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
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
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Reference 41
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Observation 20f3fb42-7f38-4b79-9d41-3437e8bbda50 · outbound
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Reference 42
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Observation 0c6bd81b-e898-42e8-b459-840983d909dc · outbound
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
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
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
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
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Gpt-4o mini: advancing cost-efficient intelligence
Reference 47
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Observation cc83f082-d0bf-4aa2-9d8d-d9b60a586869 · outbound
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Infinite photore- alistic worlds using procedural generation
Reference 48
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Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Infinigen indoors: Photorealistic in- door scenes using procedural generation
Reference 49
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Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Increasing generality in machine learning through procedural content generation
Reference 50
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Reference 51
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Observation 4b5cdec3-c15e-43a5-83f0-b1251dc6c522 · outbound
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Reference 52
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Reference 53
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Reference 54
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Observation 2616dbfe-f1e9-4bc6-8bc3-98aba7f8bdfc · outbound
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
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Reference 56
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Observation 35c42830-7f81-4b6b-b2ab-a945fc0c9899 · outbound
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
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Reference 58
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Reference 59
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Observation 9c7437bd-1edc-4ed2-a203-322ea7c6161b · outbound
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
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Observation 53c526c2-ba5b-4e16-a0a2-fce03a11a694 · outbound
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Reference 61
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Observation 13c5745f-5957-4fdf-9a45-66a25d844e47 · outbound
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
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Observation 695716ce-a244-46b1-961b-36b4d7dd316d · outbound
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Reference 63
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Observation dc20be2e-b9ae-47a5-896a-0dddb2693112 · outbound
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Gos: A large-scale annotated outdoor scene synthetic dataset
Reference 64
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Observation 125f1ea9-6c4e-4db1-873d-a3e5249dfef2 · outbound
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
Source-reported events for the cited work
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Reference 66
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Observation ff47d7b2-d3f4-4b38-9571-27fc760b2ef3 · outbound
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
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Observation 93ea9d9f-29fc-4392-b60f-281b28568756 · outbound
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Physcene: Physically interactable 3d scene synthesis for embodied ai
Reference 68
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Observation cf5818cf-29ff-4351-bad2-42eae1ddae56 · outbound
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop pixelnerf: Neural radiance fields from one or few images
Reference 69
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Observation 742c0fce-3b61-41b4-92e6-a49e092886c0 · outbound
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
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Observation 73389964-6bf4-4433-9121-0a6f28194f2d · outbound
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Reference 71
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Observation 8d8b72c9-1337-44e8-93b4-dc69c6df7172 · outbound
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop SceneX: Procedural Controllable Large-scale Scene Generation
Reference 72
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Observation e0320b56-3a70-4714-9721-461f07452cf9 · outbound
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
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Observation ec822d50-6b77-41c7-95d2-dfb16a09b238 · outbound
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Llafs: When large language models meet few-shot segmentation
Reference 74
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Observation aae77f5c-45bb-4943-9fb1-9538a2a013e6 · outbound
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
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Observation 3c717d97-202c-4d83-bec2-e08ee73f7471 · outbound
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Unresolved cited work
Reference 76
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Observation 2ebce5d7-816f-4eba-8f24-1f1b9298a09e · outbound
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Unresolved cited work
Reference 77
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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ab4b681b-48d3-4f99-928c-e45bfe0700fc · outbound
Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop Unresolved cited work
Reference 78
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f839dd52-862c-40e8-9477-4d47b9822ad9 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
No inbound Pith citation observations are available.