Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-12T23:01:13.546110Z
Paper Citation Record · LEDGER
World Simulation with Video Foundation Models for Physical AI
As of 5 August 2026, this Paper Citation Record lists 100 of 103 outbound references and 100 inbound Pith citation observations for arXiv:2511.00062.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T18:05:46.912489Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
100 of 103 outbound references displayed
- verified exact62
- verified fuzzy34
- unresolved1
- parse uncertain1
- malformed identifier0
- metadata mismatch2
External citation measurements
0
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
Observation ab3cb743-68a0-4ace-b948-d3a1d9d89180 · outbound
This paper cites V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.
World Simulation with Video Foundation Models for Physical AI V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.764797Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 412f4703-524d-4c24-8067-82cce219e50b · outbound
This paper cites Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models.
World Simulation with Video Foundation Models for Physical AI Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.610147Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8d4e97d9-0307-45a8-9a93-615803083ce8 · outbound
This paper cites Recammaster: Camera-controlled generative rendering from a single video.
World Simulation with Video Foundation Models for Physical AI Recammaster: Camera-controlled generative rendering from a single video
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.114818Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 05cfa97a-37d4-47f8-a963-f576c59a03bb · outbound
This paper cites Syncammaster: Synchronizing multi-camera video generation from diverse viewpoints.
World Simulation with Video Foundation Models for Physical AI Syncammaster: Synchronizing multi-camera video generation from diverse viewpoints
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.080265Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8ad112cd-35b9-4b7d-9eab-055948c21a6f · outbound
This paper cites Qwen2.5-VL Technical Report.
World Simulation with Video Foundation Models for Physical AI Qwen2.5-VL Technical Report
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.900179Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8c71e354-e252-43f9-8c9c-d59d67da6b9d · outbound
This paper cites Genie 3: A new frontier for world models.
World Simulation with Video Foundation Models for Physical AI Genie 3: A new frontier for world models
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.090308Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation c17a0f9c-3cfe-4b8b-a98d-f1dec6f899ab · outbound
This paper cites VideoPhy: Evaluating Physical Commonsense for Video Generation.
World Simulation with Video Foundation Models for Physical AI VideoPhy: Evaluating Physical Commonsense for Video Generation
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T11:34:37.994076Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation feea1a15-9db2-4ab4-8253-1d0e571742b9 · outbound
This paper cites VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation.
World Simulation with Video Foundation Models for Physical AI VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.918325Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8b76e304-375e-4841-a6bc-bf9387a2be39 · outbound
This paper cites GR00T N1: An Open Foundation Model for Generalist Humanoid Robots.
World Simulation with Video Foundation Models for Physical AI GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.924336Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 87aa9c59-6556-4152-a084-af0d4e6de054 · outbound
This paper cites an unresolved cited work.
World Simulation with Video Foundation Models for Physical AI Unresolved cited work
Reference 10
- Resolution
- unresolved
- raw_fallback, observed 2026-05-12T23:01:14.108994Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation d5e3258f-1975-43a1-a456-a2d2404812eb · outbound
This paper cites IntPhys 2: Benchmarking Intuitive Physics Understanding In Complex Synthetic Environments.
World Simulation with Video Foundation Models for Physical AI IntPhys 2: Benchmarking Intuitive Physics Understanding In Complex Synthetic Environments
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.930429Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation be046de4-45a5-4780-8d99-c997383fe7c2 · outbound
This paper cites Agibot world colosseo: A large-scale manipulation platform for scalable and intelligent embodied systems.
World Simulation with Video Foundation Models for Physical AI Agibot world colosseo: A large-scale manipulation platform for scalable and intelligent embodied systems
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.120244Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 78979042-1691-4b31-97a4-7a2df6df84a2 · outbound
This paper cites Planning with Reasoning using Vision Language World Model.
World Simulation with Video Foundation Models for Physical AI Planning with Reasoning using Vision Language World Model
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.939379Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b4249491-da51-4d0b-938f-825a0180ee23 · outbound
This paper cites Video depth anything: Consistent depth estimation for super-long videos.
World Simulation with Video Foundation Models for Physical AI Video depth anything: Consistent depth estimation for super-long videos
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.130867Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b2e3c0e0-06c0-4587-9278-38e3d2fc6054 · outbound
This paper cites On the Importance of Noise Scheduling for Diffusion Models.
World Simulation with Video Foundation Models for Physical AI On the Importance of Noise Scheduling for Diffusion Models
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.947275Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 55b562ef-1d13-4b22-996a-c77360e10b06 · outbound
This paper cites Diffusion policy: Visuomotor policy learning via action diffusion.
World Simulation with Video Foundation Models for Physical AI Diffusion policy: Visuomotor policy learning via action diffusion
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.152163Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 9458ccae-8aac-41b5-afea-ceabf2f6645d · outbound
This paper cites Delta lake: Open-source storage framework that enables building lakehouses.https: //delta.io/.
World Simulation with Video Foundation Models for Physical AI Delta lake: Open-source storage framework that enables building lakehouses.https: //delta.io/
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.158787Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 49a52bbf-cba0-4db8-bdb9-078863bdba7e · outbound
This paper cites Veo 3, 5 2025.
World Simulation with Video Foundation Models for Physical AI Veo 3, 5 2025
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.163715Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation c29ec697-2aeb-436e-ade5-3d8d1c0c930d · outbound
This paper cites Worldscore: A unified evaluation benchmark for world generation.
World Simulation with Video Foundation Models for Physical AI Worldscore: A unified evaluation benchmark for world generation
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.954077Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 29ff6d43-a026-4531-8901-be2947ef9b2f · outbound
This paper cites Scaling rectified flow transformers for high-resolution image synthesis.
World Simulation with Video Foundation Models for Physical AI Scaling rectified flow transformers for high-resolution image synthesis
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.176994Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3464cb8c-58e6-4fa1-906f-ac882462c28b · outbound
This paper cites LLM-based Realistic Safety-Critical Driving Video Generation.
World Simulation with Video Foundation Models for Physical AI LLM-based Realistic Safety-Critical Driving Video Generation
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.962088Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1f8223a3-7728-4dc5-845a-deb5eb77378a · outbound
This paper cites Diffusion models and gaussian flow matching: Two sides of the same coin.
World Simulation with Video Foundation Models for Physical AI Diffusion models and gaussian flow matching: Two sides of the same coin
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.195347Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation edea4d0f-8dc8-424d-9fcb-f19dc243d1b4 · outbound
This paper cites Seedance 1.0: Exploring the Boundaries of Video Generation Models.
World Simulation with Video Foundation Models for Physical AI Seedance 1.0: Exploring the Boundaries of Video Generation Models
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.971409Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation eaa9cbc9-f6d9-4048-9310-6e68115ac020 · outbound
This paper cites YOLOX: Exceeding YOLO Series in 2021.
World Simulation with Video Foundation Models for Physical AI YOLOX: Exceeding YOLO Series in 2021
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:31:31.716715Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3dadca2a-d312-45cb-9b6f-62d0f3855602 · outbound
This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.
World Simulation with Video Foundation Models for Physical AI DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.986635Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8dc1b711-ac24-4cf6-b365-8735ce972af6 · outbound
This paper cites T2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video Generation.
World Simulation with Video Foundation Models for Physical AI T2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video Generation
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.994170Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f99882ba-cb42-46ea-9153-109dca9c5367 · outbound
This paper cites World Models.
World Simulation with Video Foundation Models for Physical AI World Models
Reference 27
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:14.002924Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 906f848f-38b0-44f0-99bf-c1808cfbddd3 · outbound
This paper cites LTX-Video: Realtime Video Latent Diffusion.
World Simulation with Video Foundation Models for Physical AI LTX-Video: Realtime Video Latent Diffusion
Reference 28
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:14.011752Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 4a1f96cd-9daa-47a3-b344-64bcabdb5e9f · outbound
This paper cites Dream to Control: Learning Behaviors by Latent Imagination.
World Simulation with Video Foundation Models for Physical AI Dream to Control: Learning Behaviors by Latent Imagination
Reference 29
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:14.018849Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation aa7ef977-8a45-4454-abc7-f06974e97305 · outbound
This paper cites Generalized Neighborhood Attention: Multi-dimensional Sparse Attention at the Speed of Light.
World Simulation with Video Foundation Models for Physical AI Generalized Neighborhood Attention: Multi-dimensional Sparse Attention at the Speed of Light
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.026420Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1aac1657-8923-4a1e-9f87-cc03d0c41c31 · outbound
This paper cites UniRelight: Learning Joint Decomposition and Synthesis for Video Relighting.
World Simulation with Video Foundation Models for Physical AI UniRelight: Learning Joint Decomposition and Synthesis for Video Relighting
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.035929Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation cd329c03-ce76-45d0-9f9d-4782b071fd88 · outbound
This paper cites simple diffusion: End-to-end diffusion for high resolution images.
World Simulation with Video Foundation Models for Physical AI simple diffusion: End-to-end diffusion for high resolution images
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.264196Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f9dcd7e3-e2e4-4e43-8037-dba17d16ab2d · outbound
This paper cites ViPE: Video Pose Engine for 3D Geometric Perception.
World Simulation with Video Foundation Models for Physical AI ViPE: Video Pose Engine for 3D Geometric Perception
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T16:41:08.910540Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3842889c-98aa-432d-93c6-397d01e3b08f · outbound
This paper cites LET-3D-AP: Longitudinal Error Tolerant 3D Average Precision for Camera-Only 3D Detection.
World Simulation with Video Foundation Models for Physical AI LET-3D-AP: Longitudinal Error Tolerant 3D Average Precision for Camera-Only 3D Detection
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.050176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation d4e9e9b6-b193-4e97-8800-42732f720e3e · outbound
This paper cites GPT-4o System Card.
World Simulation with Video Foundation Models for Physical AI GPT-4o System Card
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:14.056202Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 284aa987-6557-4fc1-aa91-dcc35acd264d · outbound
This paper cites DreamGen: Unlocking Generalization in Robot Learning through Video World Models.
World Simulation with Video Foundation Models for Physical AI DreamGen: Unlocking Generalization in Robot Learning through Video World Models
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T23:50:45.800685Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f0765cd3-e892-4bbe-9d26-fa149d80302a · outbound
This paper cites RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose.
World Simulation with Video Foundation Models for Physical AI RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.070641Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 6dd5d3a1-74ef-486c-b209-98da15fff0a2 · outbound
This paper cites Elucidating the design space of diffusion-based generative models.NeurIPS.
World Simulation with Video Foundation Models for Physical AI Elucidating the design space of diffusion-based generative models.NeurIPS
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.304402Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3537471d-bbb2-4c45-8296-29eb79762abc · outbound
This paper cites DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.
World Simulation with Video Foundation Models for Physical AI DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
Reference 39
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:14.075355Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 665fad89-9f5f-469c-a9e5-a035537641f5 · outbound
This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.
World Simulation with Video Foundation Models for Physical AI HunyuanVideo: A Systematic Framework For Large Video Generative Models
Reference 40
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.624574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b29f4ddb-f6b4-498a-9da7-c2e97480c021 · outbound
This paper cites Kling.
World Simulation with Video Foundation Models for Physical AI Kling
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.321923Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f2ee8ce3-f025-44bc-a2cf-8780d356ba4e · outbound
This paper cites BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers.
World Simulation with Video Foundation Models for Physical AI BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.632850Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 5b6e1514-92d1-45c1-ada2-7903ddd6408a · outbound
This paper cites Won- derplay: Dynamic 3d scene generation from a single image and actions.arXiv preprint arXiv:2505.18151.
World Simulation with Video Foundation Models for Physical AI Won- derplay: Dynamic 3d scene generation from a single image and actions.arXiv preprint arXiv:2505.18151
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.639296Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation cbcafa83-5f1e-4391-ab60-06f49959080b · outbound
This paper cites Torchtitan: One-stop pytorch native solution for production ready LLM pretraining.
World Simulation with Video Foundation Models for Physical AI Torchtitan: One-stop pytorch native solution for production ready LLM pretraining
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.099057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8dd4a2d0-814a-4cef-b4ad-421c3dd83fff · outbound
This paper cites Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation.
World Simulation with Video Foundation Models for Physical AI Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation
Reference 45
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T21:28:42.077022Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation adbef28e-01d6-4b66-b831-e5918f9aadb2 · outbound
This paper cites Flow Matching for Generative Modeling.
World Simulation with Video Foundation Models for Physical AI Flow Matching for Generative Modeling
Reference 46
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.653660Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 44d2be4c-486d-448f-9aa2-ea991d47a487 · outbound
This paper cites Improving Video Generation with Human Feedback.
World Simulation with Video Foundation Models for Physical AI Improving Video Generation with Human Feedback
Reference 47
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T15:30:03.116566Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f99bbb63-c9bd-4b33-aa44-b2e411deb33e · outbound
This paper cites Dynamicscaler: Seamless and scalable video generation for panoramic scenes.
World Simulation with Video Foundation Models for Physical AI Dynamicscaler: Seamless and scalable video generation for panoramic scenes
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.138025Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 08efc4e9-13c8-481a-aca0-8d5367ee7e4b · outbound
This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.
World Simulation with Video Foundation Models for Physical AI Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
Reference 49
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.667121Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation fd492237-9055-48ba-a752-7c5e6a233445 · outbound
This paper cites Simplifying, Stabilizing and Scaling Continuous-Time Consistency Models.
World Simulation with Video Foundation Models for Physical AI Simplifying, Stabilizing and Scaling Continuous-Time Consistency Models
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:26:23.772771Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ef66dd02-13ac-41d7-9beb-570513e9222e · outbound
This paper cites LATR: 3D Lane Detection from Monocular Images with Transformer.
World Simulation with Video Foundation Models for Physical AI LATR: 3D Lane Detection from Monocular Images with Transformer
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.682645Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation e9e99ea9-b2e0-4f61-a539-5affb253ebf9 · outbound
This paper cites Hailuo.
World Simulation with Video Foundation Models for Physical AI Hailuo
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.206489Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b073b607-1fdc-4a9e-a313-abd9b69fd17e · outbound
This paper cites Do generative video models understand physical principles?.
World Simulation with Video Foundation Models for Physical AI Do generative video models understand physical principles?
Reference 53
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T12:47:06.031259Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation edf2c7b8-8352-4d53-ba76-1603399fd485 · outbound
This paper cites RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots.
World Simulation with Video Foundation Models for Physical AI RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots
Reference 54
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:46:30.425882Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 32f39998-bff7-4dce-8971-8a381add6192 · outbound
This paper cites Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning.
World Simulation with Video Foundation Models for Physical AI Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning
Reference 55
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T12:47:10.348602Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f344ecf1-a33d-49c0-8634-5443f93647f8 · outbound
This paper cites Cosmos-Transfer1: Conditional World Generation with Adaptive Multimodal Control.
World Simulation with Video Foundation Models for Physical AI Cosmos-Transfer1: Conditional World Generation with Adaptive Multimodal Control
Reference 56
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.712342Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 6f8d0196-3608-45c3-a9f9-cdf0d070daea · outbound
This paper cites Cosmos World Foundation Model Platform for Physical AI.
World Simulation with Video Foundation Models for Physical AI Cosmos World Foundation Model Platform for Physical AI
Reference 57
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.716640Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ba398b82-ef48-45ec-8759-07d233eea72d · outbound
This paper cites an unresolved cited work.
World Simulation with Video Foundation Models for Physical AI Unresolved cited work
Reference 58
- Resolution
- parse uncertain
- raw_fallback, observed 2026-05-12T23:01:14.248509Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 89c3a877-9d7f-402b-9b79-fefb1ab37802 · outbound
This paper cites Sora.
World Simulation with Video Foundation Models for Physical AI Sora
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.256392Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 2ee28bcd-8222-4143-82a5-fe69c5d9dabd · outbound
This paper cites Training language models to follow instructions with human feedback.NeurIPS.
World Simulation with Video Foundation Models for Physical AI Training language models to follow instructions with human feedback.NeurIPS
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.269581Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 19018ce4-6981-4d95-9720-68469fb6f6d1 · outbound
This paper cites YaRN: Efficient Context Window Extension of Large Language Models.
World Simulation with Video Foundation Models for Physical AI YaRN: Efficient Context Window Extension of Large Language Models
Reference 61
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.721168Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 74b9026e-75e5-420d-80d1-c74b354abed5 · outbound
This paper cites Movie Gen: A Cast of Media Foundation Models.
World Simulation with Video Foundation Models for Physical AI Movie Gen: A Cast of Media Foundation Models
Reference 62
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.725884Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation a2727a34-99a7-459f-adef-a336243af3b0 · outbound
This paper cites Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters.
World Simulation with Video Foundation Models for Physical AI Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.287690Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 66e125d8-e0fc-4ea1-8ee6-072a45efb597 · outbound
This paper cites SAM 2: Segment Anything in Images and Videos.
World Simulation with Video Foundation Models for Physical AI SAM 2: Segment Anything in Images and Videos
Reference 64
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.730843Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 95d616d7-bd92-46a3-b35c-e77a2a868564 · outbound
This paper cites Ren, Justin Lidard, Lars Lien Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Benjamin Burchfiel, Hongkai Dai, and Max Simchowitz.
World Simulation with Video Foundation Models for Physical AI Ren, Justin Lidard, Lars Lien Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Benjamin Burchfiel, Hongkai Dai, and Max Simchowitz
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.310856Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 283d1d9f-ef01-48eb-b6ed-3b806058b365 · outbound
This paper cites Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks.
World Simulation with Video Foundation Models for Physical AI Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks
Reference 66
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.736123Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 32c4917d-c431-423f-97c5-4237fd9f6cbc · outbound
This paper cites Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models.
World Simulation with Video Foundation Models for Physical AI Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models
Reference 67
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T23:01:13.741361Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 654844e1-d016-48e3-a839-c110ecb5fcc1 · outbound
This paper cites Gen3c: 3d-informed world-consistent video generation with precise camera control.
World Simulation with Video Foundation Models for Physical AI Gen3c: 3d-informed world-consistent video generation with precise camera control
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.094409Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 26ee39e3-336d-4d1e-b6ec-aeba3a8aa358 · outbound
This paper cites Gen 3.
World Simulation with Video Foundation Models for Physical AI Gen 3
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.104453Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 769806dc-f5fe-4f9d-be52-832c99f440da · outbound
This paper cites very scattered.
World Simulation with Video Foundation Models for Physical AI very scattered
Reference 70
- Resolution
- verified exact
- doi, observed 2026-05-12T23:01:13.602107Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1a43ad0e-d7a0-4a16-ba2f-6fa68d3d1a41 · outbound
This paper cites Proximal Policy Optimization Algorithms.
World Simulation with Video Foundation Models for Physical AI Proximal Policy Optimization Algorithms
Reference 71
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.746628Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 43e802b8-64de-4ea1-b362-8ab0529edb7b · outbound
This paper cites Text-To-4D Dynamic Scene Generation.
World Simulation with Video Foundation Models for Physical AI Text-To-4D Dynamic Scene Generation
Reference 72
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.753011Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation fc0617d6-52bd-4021-8f69-a2ccb5acd549 · outbound
This paper cites Light field networks: Neural scene representations with single-evaluation rendering.NeurIPS.
World Simulation with Video Foundation Models for Physical AI Light field networks: Neural scene representations with single-evaluation rendering.NeurIPS
Reference 73
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.187667Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 6ea03bf2-a2d8-492f-b240-f06edf88a77c · outbound
This paper cites Stylegan-v: A continuous video generator with the price, image quality and perks of stylegan2.
World Simulation with Video Foundation Models for Physical AI Stylegan-v: A continuous video generator with the price, image quality and perks of stylegan2
Reference 74
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.201259Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 488ccc1b-86f2-49fb-82ce-e6bfcb82f4a9 · outbound
This paper cites cuRobo: Parallelized Collision-Free Minimum-Jerk Robot Motion Generation.
World Simulation with Video Foundation Models for Physical AI cuRobo: Parallelized Collision-Free Minimum-Jerk Robot Motion Generation
Reference 75
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.759032Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8833b5d3-c4f8-445d-920f-8debd9cf26b0 · outbound
This paper cites 1x technologies | safe humanoids for the home.
World Simulation with Video Foundation Models for Physical AI 1x technologies | safe humanoids for the home
Reference 76
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.223399Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 2f7c672a-6f2c-446d-a1bd-d7f359c57fe8 · outbound
This paper cites Open x-embodiment: Robotic learning datasets and rt-x models.
World Simulation with Video Foundation Models for Physical AI Open x-embodiment: Robotic learning datasets and rt-x models
Reference 77
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.228413Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 944ad03f-8f43-4bcd-b564-08fefcf4f9cb · outbound
This paper cites Bridgedata v2: A dataset for robot learning at scale.
World Simulation with Video Foundation Models for Physical AI Bridgedata v2: A dataset for robot learning at scale
Reference 78
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.233658Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 49be7c1a-e43e-48fb-b04d-dd4d4cf4ebe1 · outbound
This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.
World Simulation with Video Foundation Models for Physical AI Wan: Open and Advanced Large-Scale Video Generative Models
Reference 79
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.617255Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 99eae887-fd5f-4c07-9951-138dbeff236e · outbound
This paper cites A comprehensive study of decoder-only llms for text-to-image generation.
World Simulation with Video Foundation Models for Physical AI A comprehensive study of decoder-only llms for text-to-image generation
Reference 80
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.274833Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 44c15761-9b25-49a0-aa9c-1407d55be937 · outbound
This paper cites Frame in-n-out: Unbounded con- trollable image-to-video generation.
World Simulation with Video Foundation Models for Physical AI Frame in-n-out: Unbounded con- trollable image-to-video generation
Reference 81
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.770365Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation fb2dc8e2-b8b4-43a5-a17b-f3ce4ba162fb · outbound
This paper cites Koala-36m: A large-scale video dataset improving consistency between fine-grained conditions and video content.
World Simulation with Video Foundation Models for Physical AI Koala-36m: A large-scale video dataset improving consistency between fine-grained conditions and video content
Reference 82
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.296587Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 866afd17-3d65-4d32-95ae-5ddf1427481f · outbound
This paper cites Internvideo2: Scaling foundation models for multimodal video understanding.
World Simulation with Video Foundation Models for Physical AI Internvideo2: Scaling foundation models for multimodal video understanding
Reference 83
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.315657Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f53d5fe8-576d-4941-9640-12dca55e4056 · outbound
This paper cites Controlling Space and Time with Diffusion Models.
World Simulation with Video Foundation Models for Physical AI Controlling Space and Time with Diffusion Models
Reference 84
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.776381Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ed7ba837-e571-4f04-b041-a9f4e77c7902 · outbound
This paper cites Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.
World Simulation with Video Foundation Models for Physical AI Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time
Reference 85
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.125708Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3bdeaf82-ebd2-456b-8442-0534bb253c71 · outbound
This paper cites Exploring video quality assessment on user generated contents from aesthetic and technical perspectives.
World Simulation with Video Foundation Models for Physical AI Exploring video quality assessment on user generated contents from aesthetic and technical perspectives
Reference 86
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.169733Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 68418d26-aa82-45e3-a780-4df51bc9b894 · outbound
This paper cites RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation.
World Simulation with Video Foundation Models for Physical AI RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation
Reference 87
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T22:14:18.432154Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1c2f1d5a-30c3-4efa-972e-32f679470874 · outbound
This paper cites Ties-merging: Resolving interference when merging models.NeurIPS.
World Simulation with Video Foundation Models for Physical AI Ties-merging: Resolving interference when merging models.NeurIPS
Reference 88
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.240424Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 51988b6b-b002-4279-ba30-465ed87158a8 · outbound
This paper cites Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities.
World Simulation with Video Foundation Models for Physical AI Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities
Reference 89
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T22:16:05.189340Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0c3c7d1d-2359-447e-acd6-b3946edd022e · outbound
This paper cites EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents.
World Simulation with Video Foundation Models for Physical AI EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents
Reference 90
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:24:45.426358Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 74b42442-84f4-46f9-b307-b658f57c8fe1 · outbound
This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.
World Simulation with Video Foundation Models for Physical AI CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
Reference 91
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.799820Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f5188f6a-8cf5-40e6-b1b3-820765e7236c · outbound
This paper cites Data-regularized reinforcement learning for diffusion models at scale.
World Simulation with Video Foundation Models for Physical AI Data-regularized reinforcement learning for diffusion models at scale
Reference 92
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.811776Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 252b42ad-53b3-4bc5-a695-a07a8dea90ff · outbound
This paper cites Language models are super mario: Absorbing abilities from homologous models as a free lunch.
World Simulation with Video Foundation Models for Physical AI Language models are super mario: Absorbing abilities from homologous models as a free lunch
Reference 93
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T23:01:14.085751Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8af2157c-8527-42e4-97d2-2543d4aba109 · outbound
This paper cites EWMBench: Evaluating Scene, Motion, and Semantic Quality in Embodied World Models.
World Simulation with Video Foundation Models for Physical AI EWMBench: Evaluating Scene, Motion, and Semantic Quality in Embodied World Models
Reference 94
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.822345Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 2ec731de-1750-4793-9558-1281b08fe6fe · outbound
This paper cites Waver: Wave Your Way to Lifelike Video Generation.
World Simulation with Video Foundation Models for Physical AI Waver: Wave Your Way to Lifelike Video Generation
Reference 95
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.834624Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation e6b72cb2-cb9b-4d0f-ae62-3342d8ab69a7 · outbound
This paper cites GenXD: Generating Any 3D and 4D Scenes.
World Simulation with Video Foundation Models for Physical AI GenXD: Generating Any 3D and 4D Scenes
Reference 96
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.848208Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 49ce5cb8-f139-4fb8-9c88-1d606b8f9a2b · outbound
This paper cites Are Synthetic Videos Useful? A Benchmark for Retrieval-Centric Evaluation of Synthetic Videos.
World Simulation with Video Foundation Models for Physical AI Are Synthetic Videos Useful? A Benchmark for Retrieval-Centric Evaluation of Synthetic Videos
Reference 97
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.858638Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 333d6195-f51a-44ff-bbea-23e061f4f542 · outbound
This paper cites Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency.
World Simulation with Video Foundation Models for Physical AI Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency
Reference 98
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T23:01:13.868632Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ba33fbdf-c62f-4392-a184-c2149205d762 · outbound
This paper cites Unipc: A unified predictor-corrector framework for fast sampling of diffusion models.Advances in Neural Information Processing Systems, 36:49842–49869.
World Simulation with Video Foundation Models for Physical AI Unipc: A unified predictor-corrector framework for fast sampling of diffusion models.Advances in Neural Information Processing Systems, 36:49842–49869
Reference 99
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T23:01:13.875615Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b9d7bddd-8785-4d5c-bb5e-1031eda8cec5 · outbound
This paper cites VLM4D: Towards Spatiotemporal Awareness in Vision Language Models.
World Simulation with Video Foundation Models for Physical AI VLM4D: Towards Spatiotemporal Awareness in Vision Language Models
Reference 100
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:13.883037Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Pith citing papers
Observation 3f536bf9-a60d-45b9-8dfa-2c26111dbfac · inbound
Non-invasive Assessment of Pancreatic Duct Hypertension Using Computational Flow Modeling cites this paper.
Non-invasive Assessment of Pancreatic Duct Hypertension Using Computational Flow Modeling World Simulation with Video Foundation Models for Physical AI
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T18:05:46.912489Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b3a173d5-3c1b-43f1-b9e8-e75981a48582 · inbound
SWITCH: Benchmarking Modeling and Handling of Tangible Interfaces in Long-horizon Embodied Scenarios cites this paper.
SWITCH: Benchmarking Modeling and Handling of Tangible Interfaces in Long-horizon Embodied Scenarios World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T21:14:08.241793Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 19866105-002a-4d37-a1c4-952a478a6906 · inbound
Action-guided generation of 3D functionality segmentation data cites this paper.
Action-guided generation of 3D functionality segmentation data World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-05-17T04:51:31.961334Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ffb8ebf1-a0b8-4ab6-b101-e4f911ddd5bf · inbound
mimic-video: Video-Action Models for Generalizable Robot Control Beyond VLAs cites this paper.
mimic-video: Video-Action Models for Generalizable Robot Control Beyond VLAs World Simulation with Video Foundation Models for Physical AI
Reference 41
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T10:41:00.371735Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0ea168d0-4a6f-44bd-9c15-f0726a94a156 · inbound
LangDriveCTRL: Natural Language Controllable Driving Scene Editing with Multi-modal Agents cites this paper.
LangDriveCTRL: Natural Language Controllable Driving Scene Editing with Multi-modal Agents World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T20:58:31.824406Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 42fe7b14-e06f-41cd-ac2d-85ccf240be77 · inbound
AstraNav-World: World Model for Foresight Control and Consistency cites this paper.
AstraNav-World: World Model for Foresight Control and Consistency World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T19:28:20.868354Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0c5207d5-c917-4f4d-a024-e34e56eab943 · inbound
DriveLaW:Unifying Planning and Video Generation in a Latent Driving World cites this paper.
DriveLaW:Unifying Planning and Video Generation in a Latent Driving World World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T19:38:21.104574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0110820c-4239-499e-a7bd-9fce4a723f27 · inbound
CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding cites this paper.
CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding World Simulation with Video Foundation Models for Physical AI
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T12:37:28.494262Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd8451bc-67de-427e-94c8-e4efbcaf06f5 · inbound
Advancing Open-source World Models cites this paper.
Advancing Open-source World Models World Simulation with Video Foundation Models for Physical AI
Reference 53
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T09:07:00.942546Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f9612596-cb44-414f-bc59-5f979c5d309c · inbound
World-VLA-Loop: Closed-Loop Learning of Video World Model and VLA Policy cites this paper.
World-VLA-Loop: Closed-Loop Learning of Video World Model and VLA Policy World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T03:56:47.126834Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e9d9abb1-f484-4fe4-8a09-de5a2e057d81 · inbound
DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos cites this paper.
DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T17:02:34.267430Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 7332bf28-128b-4f1d-95c3-82f7f3f881f3 · inbound
Rolling Sink: Bridging Limited-Horizon Training and Open-Ended Testing in Autoregressive Video Diffusion cites this paper.
Rolling Sink: Bridging Limited-Horizon Training and Open-Ended Testing in Autoregressive Video Diffusion World Simulation with Video Foundation Models for Physical AI
Reference 3
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-16T07:07:30.032697Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation d218176b-7e28-444f-b351-30d5d2c1c658 · inbound
RISE: Self-Improving Robot Policy with Compositional World Model cites this paper.
RISE: Self-Improving Robot Policy with Compositional World Model World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T02:30:32.148569Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation e8de21ed-7a5e-4bd5-aa18-5e3d79c67d72 · inbound
World Action Models are Zero-shot Policies cites this paper.
World Action Models are Zero-shot Policies World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation fd1e209b-bbf7-4fd5-8078-18c3e1614fa1 · inbound
Controllable Egocentric Video Generation via Occlusion-Aware Sparse 3D Hand Joints cites this paper.
Controllable Egocentric Video Generation via Occlusion-Aware Sparse 3D Hand Joints World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-15T12:20:00.593719Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 829bb067-274d-43b5-9162-ab1af4f452bf · inbound
Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms cites this paper.
Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms World Simulation with Video Foundation Models for Physical AI
Reference 43
- Resolution
- verified exact
- local_arxiv, observed 2026-05-14T01:38:36.297567Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation a553edc2-0934-4d58-81eb-de4ec5248f1e · inbound
TRACE: High-Fidelity 3D Scene Editing via Tangible Reconstruction and Geometry-Aligned Contextual Video Masking cites this paper.
TRACE: High-Fidelity 3D Scene Editing via Tangible Reconstruction and Geometry-Aligned Contextual Video Masking World Simulation with Video Foundation Models for Physical AI
Reference 62
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T02:31:02.007136Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f428f70b-ebc1-4390-bd81-c670992afeec · inbound
Lifting Unlabeled Internet-level Data for 3D Scene Understanding cites this paper.
Lifting Unlabeled Internet-level Data for 3D Scene Understanding World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T22:18:21.015364Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation d7239c86-ffbd-4f65-8fc4-5d87d982b5f2 · inbound
OpenWorldLib: A Unified Codebase and Definition of Advanced World Models cites this paper.
OpenWorldLib: A Unified Codebase and Definition of Advanced World Models World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation d6ab8ce6-250c-4191-aa3f-8b7db6070145 · inbound
OpenWorldLib: A Unified Codebase and Definition of Advanced World Models cites this paper.
OpenWorldLib: A Unified Codebase and Definition of Advanced World Models World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T09:42:23.808691Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation abdbe0d3-d15a-446e-b6c7-e80340e0ec62 · inbound
Action Images: End-to-End Policy Learning via Multiview Video Generation cites this paper.
Action Images: End-to-End Policy Learning via Multiview Video Generation World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 422b8182-9835-4b95-95b1-4473873e0e50 · inbound
SceneScribe-1M: A Large-Scale Video Dataset with Comprehensive Geometric and Semantic Annotations cites this paper.
SceneScribe-1M: A Large-Scale Video Dataset with Comprehensive Geometric and Semantic Annotations World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 83cdf01c-32a7-4a92-9d8d-2a7220f58fed · inbound
MotionScape: A Large-Scale Real-World Highly Dynamic UAV Video Dataset for World Models cites this paper.
MotionScape: A Large-Scale Real-World Highly Dynamic UAV Video Dataset for World Models World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 50bb55b6-4159-413c-abc3-14c00f504715 · inbound
Representations Before Pixels: Semantics-Guided Hierarchical Video Prediction cites this paper.
Representations Before Pixels: Semantics-Guided Hierarchical Video Prediction World Simulation with Video Foundation Models for Physical AI
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 780fa249-5e2b-40b1-9161-f5c2d82e6cbf · inbound
SyncFix: Fixing 3D Reconstructions via Multi-View Synchronization cites this paper.
SyncFix: Fixing 3D Reconstructions via Multi-View Synchronization World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 479e6cdb-9b9b-4c34-8193-940ee358f451 · inbound
ShapeGen: Robotic Data Generation for Category-Level Manipulation cites this paper.
ShapeGen: Robotic Data Generation for Category-Level Manipulation World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0ed5f6d6-1d1c-4220-bacc-ff5fe532e494 · inbound
From Seeing to Simulating: Generative High-Fidelity Simulation with Digital Cousins for Generalizable Robot Learning and Evaluation cites this paper.
From Seeing to Simulating: Generative High-Fidelity Simulation with Digital Cousins for Generalizable Robot Learning and Evaluation World Simulation with Video Foundation Models for Physical AI
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 062bf222-1e5a-4795-80f6-c44d909a736a · inbound
Human Cognition in Machines: A Unified Perspective of World Models cites this paper.
Human Cognition in Machines: A Unified Perspective of World Models World Simulation with Video Foundation Models for Physical AI
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 476c1df0-c9b8-43a1-ba13-518b7294a8ab · inbound
UniGeo: Unifying Geometric Guidance for Camera-Controllable Image Editing via Video Models cites this paper.
UniGeo: Unifying Geometric Guidance for Camera-Controllable Image Editing via Video Models World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation a36559ad-8a7a-46a8-9299-77092c1d3db8 · inbound
UniGeo: Unifying Geometric Guidance for Camera-Controllable Image Editing via Video Models cites this paper.
UniGeo: Unifying Geometric Guidance for Camera-Controllable Image Editing via Video Models World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 9510abdc-f1c1-4fae-86d0-b88035f03019 · inbound
UniGeo: Unifying Geometric Guidance for Camera-Controllable Image Editing via Video Models cites this paper.
UniGeo: Unifying Geometric Guidance for Camera-Controllable Image Editing via Video Models World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-05T16:51:14.240617Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation a1d3144e-8776-4ac3-b493-34198b3f9357 · inbound
MultiWorld: Scalable Multi-Agent Multi-View Video World Models cites this paper.
MultiWorld: Scalable Multi-Agent Multi-View Video World Models World Simulation with Video Foundation Models for Physical AI
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 7d185eac-58e0-45a9-8009-1b1b9f3e4da6 · inbound
RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation cites this paper.
RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 08d65f79-7c4b-4ebf-98d5-bb5732f81ade · inbound
RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation cites this paper.
RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-15T06:19:50.279253Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation cc575329-78a5-4ad9-8af7-fe0ea9cf7c5d · inbound
Mask World Model: Predicting What Matters for Robust Robot Policy Learning cites this paper.
Mask World Model: Predicting What Matters for Robust Robot Policy Learning World Simulation with Video Foundation Models for Physical AI
Reference 28
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation e736b80b-c559-45cf-96f9-f4ffd6c23873 · inbound
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics cites this paper.
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics World Simulation with Video Foundation Models for Physical AI
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 4e5f7877-17c3-4ec6-a432-db1e23b5cccf · inbound
Hi-WM: Human-in-the-World-Model for Scalable Robot Post-Training cites this paper.
Hi-WM: Human-in-the-World-Model for Scalable Robot Post-Training World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b0566a21-f8cf-4eff-9d9e-a1eba39f51b7 · inbound
Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling cites this paper.
Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 34795d18-378b-4dc0-aa2b-d1cebad163ee · inbound
Learning physically grounded traffic accident reconstruction from public accident reports cites this paper.
Learning physically grounded traffic accident reconstruction from public accident reports World Simulation with Video Foundation Models for Physical AI
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 53bbaa4a-b583-462f-9ea3-f96b48cdd36e · inbound
World Model for Robot Learning: A Comprehensive Survey cites this paper.
World Model for Robot Learning: A Comprehensive Survey World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 096cd1c8-87f2-4264-806f-9488893c8fc6 · inbound
Seeing Realism from Simulation: Efficient Video Transfer for Vision-Language-Action Data Augmentation cites this paper.
Seeing Realism from Simulation: Efficient Video Transfer for Vision-Language-Action Data Augmentation World Simulation with Video Foundation Models for Physical AI
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 530c4c0e-acb4-45b7-a087-145d7c9c3d87 · inbound
RLDX-1 Technical Report cites this paper.
RLDX-1 Technical Report World Simulation with Video Foundation Models for Physical AI
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3014a16a-ab53-4b04-ae5b-40792c4d8723 · inbound
RLDX-1 Technical Report cites this paper.
RLDX-1 Technical Report World Simulation with Video Foundation Models for Physical AI
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 9fb38d36-dac3-47be-8b49-1d3c523199e9 · inbound
Is the Future Compatible? Diagnosing Dynamic Consistency in World Action Models cites this paper.
Is the Future Compatible? Diagnosing Dynamic Consistency in World Action Models World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation c8695a0e-d55a-4eee-ab2c-18803b91979e · inbound
CollabVR: Collaborative Video Reasoning with Vision-Language and Video Generation Models cites this paper.
CollabVR: Collaborative Video Reasoning with Vision-Language and Video Generation Models World Simulation with Video Foundation Models for Physical AI
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T23:01:14.323574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation a07cccf4-f49a-42f0-af2b-663b6299d52d · inbound
Reinforcing VLAs in Task-Agnostic World Models cites this paper.
Reinforcing VLAs in Task-Agnostic World Models World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T04:27:14.277708Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 986f8d80-af33-4be2-8288-fdd7ba5dba9f · inbound
Reinforcing VLAs in Task-Agnostic World Models cites this paper.
Reinforcing VLAs in Task-Agnostic World Models World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T08:14:03.037059Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 516c767b-71c5-4c2f-91d5-68956fcce97e · inbound
Di-BiLPS: Denoising induced Bidirectional Latent-PDE-Solver under Sparse Observations cites this paper.
Di-BiLPS: Denoising induced Bidirectional Latent-PDE-Solver under Sparse Observations World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-14T19:07:50.987224Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation d4c23c5c-4dd4-489f-a9bd-f90ffb6b02f6 · inbound
Coding Agent Is Good As World Simulator cites this paper.
Coding Agent Is Good As World Simulator World Simulation with Video Foundation Models for Physical AI
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T02:23:32.034608Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation a078f570-9f76-4132-8f15-06ccece8828e · inbound
Coding Agent Is Good As World Simulator cites this paper.
Coding Agent Is Good As World Simulator World Simulation with Video Foundation Models for Physical AI
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T14:35:46.852607Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b5ed68ce-66e3-44de-8b02-9e582067c172 · inbound
DriveCtrl: Conditioned Sim-to-Real Driving Video Generation cites this paper.
DriveCtrl: Conditioned Sim-to-Real Driving Video Generation World Simulation with Video Foundation Models for Physical AI
Reference 26
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T21:15:04.787272Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation d91c1c62-87f3-4fc8-a354-8c5c442bcfca · inbound
Pelican-Unify 1.0: A Unified Embodied Intelligence Model for Understanding, Reasoning, Imagination and Action cites this paper.
Pelican-Unify 1.0: A Unified Embodied Intelligence Model for Understanding, Reasoning, Imagination and Action World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T03:19:44.187738Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 173d31fe-008e-4bbe-86ce-73d7b0502d74 · inbound
Pelican-Unify 1.0: A Unified Embodied Intelligence Model for Understanding, Reasoning, Imagination and Action cites this paper.
Pelican-Unify 1.0: A Unified Embodied Intelligence Model for Understanding, Reasoning, Imagination and Action World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T09:46:22.452132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 425ee546-4408-47c4-bd50-17460cbc0c11 · inbound
How to Instruct Your Robot: Dense Language Annotations Power Robot Policy Learning cites this paper.
How to Instruct Your Robot: Dense Language Annotations Power Robot Policy Learning World Simulation with Video Foundation Models for Physical AI
Reference 31
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T15:23:25.279166Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation fa290429-9457-46bb-9934-66c82d90dacd · inbound
Self-supervised Hierarchical Visual Reasoning with World Model cites this paper.
Self-supervised Hierarchical Visual Reasoning with World Model World Simulation with Video Foundation Models for Physical AI
Reference 8
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-20T12:43:16.866382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 95302fe6-4ace-4927-a355-6ff92b627d65 · inbound
Self-supervised Hierarchical Visual Reasoning with World Model cites this paper.
Self-supervised Hierarchical Visual Reasoning with World Model World Simulation with Video Foundation Models for Physical AI
Reference 8
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-06-30T19:05:00.273959Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 88a07589-9b1c-4766-8c1e-09818ccd60fa · inbound
WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform cites this paper.
WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform World Simulation with Video Foundation Models for Physical AI
Reference 46
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T11:03:13.688410Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 5d7afa79-4545-41d9-832b-d6af11a6f445 · inbound
NEWTON: Agentic Planning for Physically Grounded Video Generation cites this paper.
NEWTON: Agentic Planning for Physically Grounded Video Generation World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T10:58:13.800270Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation d1e93c55-63b7-496a-bac3-7e435c202e64 · inbound
PhyWorld: Physics-Faithful World Model for Video Generation cites this paper.
PhyWorld: Physics-Faithful World Model for Video Generation World Simulation with Video Foundation Models for Physical AI
Reference 64
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-20T07:33:07.562468Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 2d959405-5891-4b63-899e-9b1337ae3a52 · inbound
World-Ego Modeling for Long-Horizon Evolution in Hybrid Embodied Tasks cites this paper.
World-Ego Modeling for Long-Horizon Evolution in Hybrid Embodied Tasks World Simulation with Video Foundation Models for Physical AI
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T06:38:05.636274Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 9c206a40-a2dd-4020-a16e-0e2c99729dab · inbound
Accelerating Video Inverse Problem Solvers with Autoregressive Diffusion Models cites this paper.
Accelerating Video Inverse Problem Solvers with Autoregressive Diffusion Models World Simulation with Video Foundation Models for Physical AI
Reference 20
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:13:59.578801Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1a8f9b0a-1dbb-49ec-a680-f27e3d4dae36 · inbound
CRONOS: Benchmarking Counterfactual Physical Consistency in Video Models cites this paper.
CRONOS: Benchmarking Counterfactual Physical Consistency in Video Models World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T04:40:23.268359Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 7cfd86f1-b242-4fd6-92ef-9e9ec2370a0f · inbound
What-If World: A Causal Benchmark for General World Models in Embodied Scenarios cites this paper.
What-If World: A Causal Benchmark for General World Models in Embodied Scenarios World Simulation with Video Foundation Models for Physical AI
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T18:23:50.356445Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 68f05e78-715d-4bcd-a2b8-b9b3a4a8522a · inbound
Proprio: Latent Self-Scoring and Inference-Time Refinement for Physically Plausible Video Generation cites this paper.
Proprio: Latent Self-Scoring and Inference-Time Refinement for Physically Plausible Video Generation World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T13:03:26.638052Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 2e702759-30b6-42cf-aadf-a3d2d85f50ad · inbound
Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players cites this paper.
Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T13:53:29.115357Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 226e4e9c-60ca-4416-9714-e137062acefc · inbound
World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications cites this paper.
World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications World Simulation with Video Foundation Models for Physical AI
Reference 108
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T08:43:15.654464Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0713b3dc-b9e4-4d64-a9ae-05704cec4938 · inbound
OptiWorld: Optimal Control for Video World Generation under Physical Constraints cites this paper.
OptiWorld: Optimal Control for Video World Generation under Physical Constraints World Simulation with Video Foundation Models for Physical AI
Reference 91
- Resolution
- verified exact
- local_arxiv, observed 2026-06-28T19:32:35.509546Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 49d26b9e-d761-4967-be0f-f5593d6b32d7 · inbound
$\tau_0$-WM: A Unified Video-Action World Model for Robotic Manipulation cites this paper.
$\tau_0$-WM: A Unified Video-Action World Model for Robotic Manipulation World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-06-28T17:22:24.504637Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ee9ffe6e-34bc-44e0-994b-e200ff4a3f33 · inbound
Beyond Task Success: Behavioral and Representational Diagnostics for WAM and VLA cites this paper.
Beyond Task Success: Behavioral and Representational Diagnostics for WAM and VLA World Simulation with Video Foundation Models for Physical AI
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-06-28T17:22:24.413659Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0866c75f-eb61-44fb-a5c6-f73e10f09d6a · inbound
Dexterity-BEV: Aligning 3D World and Actions for Generalizable Robot Policies Learning cites this paper.
Dexterity-BEV: Aligning 3D World and Actions for Generalizable Robot Policies Learning World Simulation with Video Foundation Models for Physical AI
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T23:06:20.428785Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 47e0ba62-cfe3-4f77-8281-3863146feb2d · inbound
RoboDream: Compositional World Models for Scalable Robot Data Synthesis cites this paper.
RoboDream: Compositional World Models for Scalable Robot Data Synthesis World Simulation with Video Foundation Models for Physical AI
Reference 24
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T23:36:23.584650Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b294cd98-cc39-4856-941a-61a9052f498e · inbound
NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation cites this paper.
NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation World Simulation with Video Foundation Models for Physical AI
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T02:06:27.451431Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ba28d442-6e81-405f-8219-aa41da504410 · inbound
NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation cites this paper.
NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation World Simulation with Video Foundation Models for Physical AI
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T12:34:17.389528Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1177adce-4513-4cb5-997f-ef3e4beaeebd · inbound
PointAction: 3D Points as Universal Action Representations for Robot Control cites this paper.
PointAction: 3D Points as Universal Action Representations for Robot Control World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T03:16:34.866751Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b7c62be3-a5c4-4a6c-a8f0-2cfdb861045b · inbound
OSCAR: Omni-Embodiment Action-Conditioned World Model for Robotics cites this paper.
OSCAR: Omni-Embodiment Action-Conditioned World Model for Robotics World Simulation with Video Foundation Models for Physical AI
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T07:56:47.049610Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 5a214f1b-b761-493a-8343-d66e691ec6f6 · inbound
Dream-Tac: A Unified Tactile World Action Model for Contact-Rich Robot Manipulation cites this paper.
Dream-Tac: A Unified Tactile World Action Model for Contact-Rich Robot Manipulation World Simulation with Video Foundation Models for Physical AI
Reference 3
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-02T23:27:26.854388Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 26aa952f-0ba2-47d9-ab50-2cacda776694 · inbound
MotionWAM: Towards Foundation World Action Models for Real-Time Humanoid Loco-Manipulation cites this paper.
MotionWAM: Towards Foundation World Action Models for Real-Time Humanoid Loco-Manipulation World Simulation with Video Foundation Models for Physical AI
Reference 39
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T01:37:30.721968Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b27474e3-af7a-4011-9ae8-ecbb0a44072b · inbound
Targeting World Models to Compromise Robot Learning Pipelines cites this paper.
Targeting World Models to Compromise Robot Learning Pipelines World Simulation with Video Foundation Models for Physical AI
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-06-27T16:41:03.690648Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8485be8d-3234-48c7-9d2e-6114cd9a9e1a · inbound
Prisma-World: Camera-Controllable Multi-Agent Video World Model cites this paper.
Prisma-World: Camera-Controllable Multi-Agent Video World Model World Simulation with Video Foundation Models for Physical AI
Reference 53
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T00:47:30.157870Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation e6590b4a-8ccb-4bc7-bf74-c81556e78738 · inbound
Echo-Memory: A Controlled Study of Memory in Action World Models cites this paper.
Echo-Memory: A Controlled Study of Memory in Action World Models World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T00:57:29.762501Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation decda045-f23d-4377-8905-fc6f7ecfd57a · inbound
MemoryVLA++: Temporal Modeling via Memory and Imagination in Vision-Language-Action Models cites this paper.
MemoryVLA++: Temporal Modeling via Memory and Imagination in Vision-Language-Action Models World Simulation with Video Foundation Models for Physical AI
Reference 64
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T01:57:32.223652Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8e9fe27f-cdae-47c3-a8db-356965475274 · inbound
Hierarchical Policies from Verbal and Egocentric Human Signals for Natural Human-Robot Interaction cites this paper.
Hierarchical Policies from Verbal and Egocentric Human Signals for Natural Human-Robot Interaction World Simulation with Video Foundation Models for Physical AI
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T04:57:38.603718Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation bb4167c1-d3f8-43e7-8d01-f4cdd868012f · inbound
Envision4D: Envisioning Visual Futures via Feed-forward 4D Gaussian Splatting for Autonomous Driving cites this paper.
Envision4D: Envisioning Visual Futures via Feed-forward 4D Gaussian Splatting for Autonomous Driving World Simulation with Video Foundation Models for Physical AI
Reference 47
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T04:37:36.898884Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 7e5f1ff1-3baf-4992-b0b3-3dc0fbbafba8 · inbound
WorldOlympiad: Can Your World Model Survive a Triathlon? cites this paper.
WorldOlympiad: Can Your World Model Survive a Triathlon? World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T05:47:41.258522Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation db0b85f4-8434-45ba-a162-ce39c96f6224 · inbound
World Pilot: Steering Vision-Language-Action Models with World-Action Priors cites this paper.
World Pilot: Steering Vision-Language-Action Models with World-Action Priors World Simulation with Video Foundation Models for Physical AI
Reference 71
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T11:18:03.367479Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f712b579-d06a-42cb-a67e-fab5be5b2317 · inbound
RepWAM: World Action Modeling with Representation Visual-Action Tokenizers cites this paper.
RepWAM: World Action Modeling with Representation Visual-Action Tokenizers World Simulation with Video Foundation Models for Physical AI
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T14:58:33.402657Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 07740f9e-264d-4bb3-9d19-d02040054ca3 · inbound
JoyAI-Sim: A Simulation-Enabled Interconversion Toolchain for the Embodied Data Pyramid cites this paper.
JoyAI-Sim: A Simulation-Enabled Interconversion Toolchain for the Embodied Data Pyramid World Simulation with Video Foundation Models for Physical AI
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T10:34:36.285000Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ea456dda-ca92-4b09-b322-d91e83309386 · inbound
Unified Motion-Action Modeling for Heterogeneous Robot Learning cites this paper.
Unified Motion-Action Modeling for Heterogeneous Robot Learning World Simulation with Video Foundation Models for Physical AI
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T17:28:44.450366Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation a0374d14-7131-4951-9926-ab50da5b3f6f · inbound
PAIWorld: A 3D-Consistent World Foundation Model for Robotic Manipulation cites this paper.
PAIWorld: A 3D-Consistent World Foundation Model for Robotic Manipulation World Simulation with Video Foundation Models for Physical AI
Reference 53
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T21:38:58.746884Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 53cf68d8-2acc-4d4f-96d2-9a873d364131 · inbound
Data-Forcing Distillation: Restoring Diversity and Fidelity in Few-Step Video Generation cites this paper.
Data-Forcing Distillation: Restoring Diversity and Fidelity in Few-Step Video Generation World Simulation with Video Foundation Models for Physical AI
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T21:08:58.095744Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f2a039eb-731e-4d73-81c0-460d909bde03 · inbound
SC3-Eval: Evaluating Robot Foundation Models via Self-Consistent Video Generation cites this paper.
SC3-Eval: Evaluating Robot Foundation Models via Self-Consistent Video Generation World Simulation with Video Foundation Models for Physical AI
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T00:19:13.396326Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 43ee7b49-2995-4cb3-8038-0041d7dca188 · inbound
SC3-Eval: Evaluating Robot Foundation Models via Self-Consistent Video Generation cites this paper.
SC3-Eval: Evaluating Robot Foundation Models via Self-Consistent Video Generation World Simulation with Video Foundation Models for Physical AI
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T18:23:51.418723Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation fd63755f-e389-441f-af67-1969f010d5ae · inbound
Mem-World: Memory-Augmented Action-Conditioned World Models for Persistent Robot Manipulation cites this paper.
Mem-World: Memory-Augmented Action-Conditioned World Models for Persistent Robot Manipulation World Simulation with Video Foundation Models for Physical AI
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T23:39:04.851790Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0186237b-8460-4fd2-ac03-af8946a85dba · inbound
World Engine: Towards the Era of Post-Training for Autonomous Driving cites this paper.
World Engine: Towards the Era of Post-Training for Autonomous Driving World Simulation with Video Foundation Models for Physical AI
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T03:59:33.870765Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 143010e0-b851-4b85-8b31-7d2f1e0053cc · inbound
FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation cites this paper.
FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation World Simulation with Video Foundation Models for Physical AI
Reference 66
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-04T03:29:30.391838Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f6cfe78c-ec3b-4456-92f7-a7984f1a9b44 · inbound
Foresight: Failure Detection for Long-Horizon Robotic Manipulation with Action-Conditioned World Model Latents cites this paper.
Foresight: Failure Detection for Long-Horizon Robotic Manipulation with Action-Conditioned World Model Latents World Simulation with Video Foundation Models for Physical AI
Reference 34
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T10:39:44.765169Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation c884a9f7-45c6-4d56-a02b-b543c1a27859 · inbound
Qwen-AgentWorld: Language World Models for General Agents cites this paper.
Qwen-AgentWorld: Language World Models for General Agents World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T17:09:59.232510Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 345b4521-a0b1-4df9-9d05-5040bfd2a2a2 · inbound
Physics Question Scene Graph: Fine-grained Evaluation of Physical Plausibility in Text-to-Video Generation cites this paper.
Physics Question Scene Graph: Fine-grained Evaluation of Physical Plausibility in Text-to-Video Generation World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-04T19:20:05.904375Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 2e214b17-4e5c-4ee0-8ac1-1fa7967f7900 · inbound
Causal-rCM: A Unified Teacher-Forcing and Self-Forcing Open Recipe for Autoregressive Diffusion Distillation in Streaming Video Generation and Interactive World Models cites this paper.
Causal-rCM: A Unified Teacher-Forcing and Self-Forcing Open Recipe for Autoregressive Diffusion Distillation in Streaming Video Generation and Interactive World Models World Simulation with Video Foundation Models for Physical AI
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T19:50:11.367469Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b0d95287-a3c6-4785-a94c-83f36ee7c640 · inbound
Not All Actions Are Equal: Rethinking Conditioning for Dexterous World Model cites this paper.
Not All Actions Are Equal: Rethinking Conditioning for Dexterous World Model World Simulation with Video Foundation Models for Physical AI
Reference 56
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T13:19:50.401100Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.