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Paper Citation Record · LEDGER

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation

As of 22 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 0 inbound Pith citation observations for arXiv:2607.18924.

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

pith.paper-citation-record.v1
2607.18924 v1

Coverage vector

measured 67 of 67 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T14:02:18.682158Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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67 of 67 outbound references displayed

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Outbound references

Observation 39af379b-a8c1-4f4e-8205-ea070ec12eff · outbound

This paper cites Interdyn: Controllable interactive dynamics with video diffusion models.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Interdyn: Controllable interactive dynamics with video diffusion models

Reference 1

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source=pdf_text observed=2026-08-01T14:02:10.203074Z digest=sha256:ca80c6638f71f73333fafcf93e83e444f6cb4b326655fb947996409cb0f7bafa

Observation 7fbb4757-15e2-4dd4-9e0d-b2f540d621dc · outbound

This paper cites ReCamMaster: Camera-Controlled Generative Rendering from A Single Video.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation ReCamMaster: Camera-Controlled Generative Rendering from A Single Video

Reference 2

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Observation 3f4a87ab-801e-4748-923e-0df4153575e9 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 3

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Observation 9c7bcb2a-5ced-4b84-aa37-8fbccc67db25 · outbound

This paper cites Qwen2.5-VL Technical Report.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Qwen2.5-VL Technical Report

Reference 4

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Observation 74dad40d-2c8f-45b8-a2fa-d53c2f3b32bc · outbound

This paper cites VideoPhy: Evaluating Physical Commonsense for Video Generation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation VideoPhy: Evaluating Physical Commonsense for Video Generation

Reference 5

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source=pdf_text observed=2026-08-01T14:02:10.644287Z digest=sha256:0077d0ea4957af6d8063f69ceb111b5c280419aff71c8cde2f56d695cb35bc1a

Observation a3f15e8b-0fbc-4760-a54c-db2a3b675253 · outbound

This paper cites VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation

Reference 6

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Observation 4664be17-66b1-4e1f-b5cc-5b9a70c144e2 · outbound

This paper cites Video generation models as world simulators.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Video generation models as world simulators

Reference 7

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source=pdf_text observed=2026-08-01T14:02:10.941318Z digest=sha256:e9636ed202064f9d071d1297e4539ca2c3c993b09cfa5ea8064bc88507af36b8

Observation e59c0482-5063-4e04-8752-261a840c91b4 · outbound

This paper cites Emerging properties in self-supervised vision transformers.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Emerging properties in self-supervised vision transformers

Reference 8

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source=pdf_text observed=2026-08-01T14:02:11.107464Z digest=sha256:5ed1333358ef7bcfba6023571f3c2603d8a722ea75c0ca8827deadfd7f13112b

Observation 9a09e17a-966e-4fd9-9ea0-94a8d690936d · outbound

This paper cites Visual vibrometry: Estimating material properties from small motion in video.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Visual vibrometry: Estimating material properties from small motion in video

Reference 10

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source=pdf_text observed=2026-08-01T14:02:11.382332Z digest=sha256:7ddac748ff22373a0ccf72bbad03fc4214eba9e92f4de6f668e09d68b829e833

Observation 85148bf2-772a-4a1c-a1f7-c9c63b26f815 · outbound

This paper cites Objaverse-xl: A universe of 10m+ 3d objects.Advances in Neural Information Processing Systems, 36:35799–35813, 2023.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Objaverse-xl: A universe of 10m+ 3d objects.Advances in Neural Information Processing Systems, 36:35799–35813, 2023

Reference 11

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source=pdf_text observed=2026-08-01T14:02:11.493993Z digest=sha256:43f15441bf68c10ac202e39deeac92abac1cebd4a3bc4638f09a04abc48c68ab

Observation b6c54a3a-44a4-4ce9-ae84-8c533c2b345e · outbound

This paper cites Blenderproc2: A procedural pipeline for photorealistic rendering.Journal of Open Source Software, 8(82): 4901, 2023.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Blenderproc2: A procedural pipeline for photorealistic rendering.Journal of Open Source Software, 8(82): 4901, 2023

Reference 12

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Observation dbc2bd1b-9635-4b0b-82d7-f28982aa556e · outbound

This paper cites Mirrorverse: Pushing diffusion models to realistically reflect the world.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Mirrorverse: Pushing diffusion models to realistically reflect the world

Reference 13

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Observation 8f24475b-81d0-4c34-a08a-cc3bf0ea5be8 · outbound

This paper cites Scaling rectified flow trans- formers for high-resolution image synthesis.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Scaling rectified flow trans- formers for high-resolution image synthesis

Reference 14

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Observation 36521154-34d1-472c-8d91-f61a6fffa3d2 · outbound

This paper cites Narrlv: Towards a comprehensive narrative-centric evaluation for long video generation models.arXiv preprint arXiv:2507.11245, 2025.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Narrlv: Towards a comprehensive narrative-centric evaluation for long video generation models.arXiv preprint arXiv:2507.11245, 2025

Reference 15

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Observation 414a52ce-de73-4b39-a273-75fa66a036f7 · outbound

This paper cites Force prompting: Video generation models can learn and generalize physics-based control signals.arXiv preprint arXiv:2505.19386, 2025.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Force prompting: Video generation models can learn and generalize physics-based control signals.arXiv preprint arXiv:2505.19386, 2025

Reference 16

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Observation f5498bbb-d82c-4515-9c6b-28884e5eeeba · outbound

This paper cites the public 3d asset library.Avaliable online: https://polyhaven.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation the public 3d asset library.Avaliable online: https://polyhaven

Reference 17

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source=pdf_text observed=2026-08-01T14:02:12.255998Z digest=sha256:dc247b16390668d4e4ded3e8703663dd9f8d76d32c10274526d680834f6a7f55

Observation 59e4de18-6711-443b-b664-7bd091691f9e · outbound

This paper cites Videoscore: Building automatic metrics to simulate fine-grained human feedback for video generation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Videoscore: Building automatic metrics to simulate fine-grained human feedback for video generation

Reference 18

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source=pdf_text observed=2026-08-01T14:02:12.452794Z digest=sha256:6eeb10b9d7b8c1c859f23145b9b7984c4f665c6ff0ff04a4ef501e8eab2e7626

Observation c66b3ab8-8f0b-4480-b182-605d3df6f175 · outbound

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

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers

Reference 19

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Observation 298fafe7-8e26-4f8a-a472-8573cbc16d2e · outbound

This paper cites Taming hallucinations: Boosting mllms’ video understanding via counterfactual video generation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Taming hallucinations: Boosting mllms’ video understanding via counterfactual video generation

Reference 20

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Observation 8236003d-eeca-469f-b20b-fd27879f3bad · outbound

This paper cites Vbench: Comprehensive benchmark suite for video generative models.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Vbench: Comprehensive benchmark suite for video generative models

Reference 21

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source=pdf_text observed=2026-08-01T14:02:12.906085Z digest=sha256:b58362fcf0062f57f3325f6bce60ff561503eaf9cf88f85c725bc36d4d4af371

Observation b3318902-9b5d-4783-83c0-5cd457231e6e · outbound

This paper cites VBench++: Comprehensive and Versatile Benchmark Suite for Video Generative Models.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation VBench++: Comprehensive and Versatile Benchmark Suite for Video Generative Models

Reference 22

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Observation 1171ecd3-deaa-4f37-a348-2e269ad19b05 · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.ACM Trans.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation 3d gaussian splatting for real-time radiance field rendering.ACM Trans

Reference 23

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Observation 71c16b8c-6476-46c1-8536-145a8da26bf7 · outbound

This paper cites Auto-Encoding Variational Bayes.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Auto-Encoding Variational Bayes

Reference 24

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source=pdf_text observed=2026-08-01T14:02:13.337571Z digest=sha256:18b3a7f46f9339552d28a9d30043cdad6c0304ef15ff633169b129b0f38d483f

Observation 6b29c610-c81e-48ed-87f9-a65e074070bf · outbound

This paper cites Segment anything.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Segment anything

Reference 25

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source=pdf_text observed=2026-08-01T14:02:13.525719Z digest=sha256:3f102d73602070c4a337aecf32dcd61c875df9ecaba16eebc454a8cd86f40e92

Observation f8b4d62d-40c2-4427-971a-387b84b56092 · outbound

This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 26

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source=pdf_text observed=2026-08-01T14:02:13.675414Z digest=sha256:d7903bb76f92da3a4a1d078ff49d955ec8d19938b2d38991673f475c1c19d485

Observation 6c30775e-1d9b-4df1-8129-a98056dff381 · outbound

This paper cites PISA Experiments: Exploring Physics Post-Training for Video Diffusion Models by Watching Stuff Drop.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation PISA Experiments: Exploring Physics Post-Training for Video Diffusion Models by Watching Stuff Drop

Reference 27

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source=pdf_text observed=2026-08-01T14:02:13.815589Z digest=sha256:d5579206b2607b44e6c5f43d9174341f9a44122e0ae619b172d5850c6cba3660

Observation 122cae27-733e-43dc-8f93-fc226916eb47 · outbound

This paper cites C-Drag: Chain-of-Thought Driven Motion Controller for Video Generation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation C-Drag: Chain-of-Thought Driven Motion Controller for Video Generation

Reference 28

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source=pdf_text observed=2026-08-01T14:02:13.955651Z digest=sha256:7aa844d6b0d9165b871330c2f5437522a284a1cf391044d56e64af0c026aa64d

Observation 0f76230f-6272-414c-b1b5-546a806f16a4 · outbound

This paper cites Wonderplay: Dynamic 3d scene generation from a single image and actions.arXiv preprint arXiv:2505.18151, 2025.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Wonderplay: Dynamic 3d scene generation from a single image and actions.arXiv preprint arXiv:2505.18151, 2025

Reference 29

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source=pdf_text observed=2026-08-01T14:02:14.153902Z digest=sha256:c0d3e974c37e85cef94eab7c75baeb0ea30f9c7079692f98e5023ffa47546b2b

Observation 72f9bfd9-dfc1-4fa8-9ad0-bc3841498d13 · outbound

This paper cites Evaluation of text-to-video generation models: A dynamics perspective.Advances in Neural Information Processing Systems, 37:109790–109816, 2024.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Evaluation of text-to-video generation models: A dynamics perspective.Advances in Neural Information Processing Systems, 37:109790–109816, 2024

Reference 30

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source=pdf_text observed=2026-08-01T14:02:14.287991Z digest=sha256:6350eadc72ff27328b76e381d2714eba07f8cbb147c2dbbbdfc23cbbe8d81451

Observation 693ccdc5-3b9f-4ae3-93bb-4e40d6f1c3ff · outbound

This paper cites VMBench: A Benchmark for Perception-Aligned Video Motion Generation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation VMBench: A Benchmark for Perception-Aligned Video Motion Generation

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source=pdf_text observed=2026-08-01T14:02:14.465886Z digest=sha256:0b51c0126c22857ce83294f61aa4380ab6ae598bfbf1518c40cbf1763b2f538b

Observation 84a83991-d812-4afb-b2d7-27147f8af5af · outbound

This paper cites Flow Matching for Generative Modeling.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Flow Matching for Generative Modeling

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source=pdf_text observed=2026-08-01T14:02:14.619727Z digest=sha256:35217f004c111451831ce9014b551e65d4c6f8c9a5ac4a291627ad1719611e9f

Observation a1334b48-ec1b-43eb-b1a4-cc5ba24478a1 · outbound

This paper cites Fr\'echet Video Motion Distance: A Metric for Evaluating Motion Consistency in Videos.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Fr\'echet Video Motion Distance: A Metric for Evaluating Motion Consistency in Videos

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source=pdf_text observed=2026-08-01T14:02:14.761551Z digest=sha256:f5b9e6b9cde7d2c6fe8981f8b4c7a71be7b374ee8370bfeee62b1240a11c9b5e

Observation 566673cd-5a49-450c-b4a3-dea030cbfaec · outbound

This paper cites Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends

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source=pdf_text observed=2026-08-01T14:02:14.937715Z digest=sha256:68a34efe06759c3cd5ebb448d5b0f7bcee0113f0c9f48d59514234ed5fee722c

Observation d5db0cbd-9f5e-4bc3-9791-2d2bc4fc4e1a · outbound

This paper cites Compositional visual generation with composable diffusion models.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Compositional visual generation with composable diffusion models

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source=pdf_text observed=2026-08-01T14:02:15.103676Z digest=sha256:4723c247cf297be5d4bde3a2207d3c8975fc73bbc8dbc68ab84e5db5d6a2b531

Observation 00c24bcb-0285-49a9-acd4-2b6df3d2d066 · outbound

This paper cites Physgen: Rigid-body physics-grounded image-to-video generation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Physgen: Rigid-body physics-grounded image-to-video generation

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source=pdf_text observed=2026-08-01T14:02:15.239485Z digest=sha256:69822e1e7b67098394f208327c28c5b50b4c1622c108f57f25d1385a64a22d46

Observation 23d521e8-72a0-4e82-8e4c-c55990e911a6 · outbound

This paper cites Evalcrafter: Benchmarking and evaluating large video generation models.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Evalcrafter: Benchmarking and evaluating large video generation models

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source=pdf_text observed=2026-08-01T14:02:15.418653Z digest=sha256:9122611041a8ad5935cf09c9166e85e004baf46b894e05a98fcef4aac707c6f0

Observation 46acbb0e-7a42-46c5-aab5-23feb77b89d6 · outbound

This paper cites Omni-effects: Unified and spatially- controllable visual effects generation.arXiv preprint arXiv:2508.07981, 2025.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Omni-effects: Unified and spatially- controllable visual effects generation.arXiv preprint arXiv:2508.07981, 2025

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source=pdf_text observed=2026-08-01T14:02:15.586745Z digest=sha256:b71d954efcb32d9e934e0a111c561a7d0453786b89978e2725a4d0ee6e7f61fa

Observation 67151adc-7dfc-4161-bb42-557c819e6246 · outbound

This paper cites Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation

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source=pdf_text observed=2026-08-01T14:02:15.757818Z digest=sha256:49d89acabce7efc37c7434a1140956b191ad4a4e63db89b299d75726f184cab3

Observation 30b2575e-f8f5-42c3-b994-eafefd21f9a7 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Nerf: Representing scenes as neural radiance fields for view synthesis

Reference 40

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source=pdf_text observed=2026-08-01T14:02:15.926713Z digest=sha256:14776bd1c64fbdb0be1a0608c5ea5956855a768004ffc817303076c1c811a171

Observation 703dc201-a793-414a-a8de-324f9ab3b9c9 · outbound

This paper cites Do generative video models understand physical principles?.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Do generative video models understand physical principles?

Reference 41

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source=pdf_text observed=2026-08-01T14:02:16.069275Z digest=sha256:3ddfe7ef29ef8d18c403b9169090d442c34d1207e250d659d052f132e696cebd

Observation d1830fc2-492a-4075-97ba-60aa6bb71cf2 · outbound

This paper cites an unresolved cited work.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Unresolved cited work

Reference 42

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source=pdf_text observed=2026-08-01T14:02:16.205762Z digest=sha256:e741f295b92b4307386362842261f6b7accdfca48545dbe2eb29305dd7560302

Observation 6e61b543-aaab-4259-b2e4-6f2b3dfc0ec2 · outbound

This paper cites an unresolved cited work.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Unresolved cited work

Reference 43

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source=pdf_text observed=2026-08-01T14:02:16.533810Z digest=sha256:5a0371292c12058e818de39583be790c0b85ae2614f9b2361547a14afdd97225

Observation 8484d829-d3c3-4811-8e3d-32c6422d4266 · outbound

This paper cites Scalable diffusion models with transformers.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Scalable diffusion models with transformers

Reference 44

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source=pdf_text observed=2026-08-01T14:02:16.674411Z digest=sha256:65ed3430c072bc61f1a5fe5c70ced2fa5efe3032538878cedc9b4dcdc4ce5064

Observation acfafd34-ebcd-4684-8db1-d275f6af47c1 · outbound

This paper cites Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k

Reference 45

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source=pdf_text observed=2026-08-01T14:02:16.807981Z digest=sha256:d0a3169986351d715a91ae7a118c3d9530f5012aed1f5ec92c931939d295f3d3

Observation 9c0aba36-e70c-4cb8-955b-d37ac9bb439b · outbound

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

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation High- resolution image synthesis with latent diffusion models

Reference 46

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source=pdf_text observed=2026-08-01T14:02:16.981257Z digest=sha256:6273d16b9fb4cacc73692b8bd719215915641e6491dfd0404ddbb48d3aa7497c

Observation 5024d79d-fa45-472a-b066-44bdb88d0a33 · outbound

This paper cites Learning to generate object interactions with physics-guided video diffusion.arXiv preprint arXiv:2510.02284, 2025.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Learning to generate object interactions with physics-guided video diffusion.arXiv preprint arXiv:2510.02284, 2025

Reference 47

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source=pdf_text observed=2026-08-01T14:02:17.143859Z digest=sha256:a9b8e6b6797cde12cd59a860608706a6dc711b0a1fcb03b6211d1050bf753517

Observation dcc806ba-d00c-41e9-bbcb-02a9bcc869af · outbound

This paper cites Motion-i2v: Consistent and controllable image-to-video generation with explicit motion modeling.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Motion-i2v: Consistent and controllable image-to-video generation with explicit motion modeling

Reference 48

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source=pdf_text observed=2026-08-01T14:02:17.269701Z digest=sha256:2b8c9c3cf1689e51609324ed08bead6b84795a3cbeb3ae12fee7c315ed57ab58

Observation fe27c9ab-efff-4f67-b6a6-666dfb03d131 · outbound

This paper cites DINOv3.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation DINOv3

Reference 49

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source=pdf_text observed=2026-08-01T14:02:17.430344Z digest=sha256:6289833c1408770cf5263af6c2a0406eb91e31a67456be73d5671f254cf39e8c

Observation 72062958-c053-4720-ac06-ccb67ddff37c · outbound

This paper cites T2v- compbench: A comprehensive benchmark for compositional text-to-video generation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation T2v- compbench: A comprehensive benchmark for compositional text-to-video generation

Reference 50

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source=pdf_text observed=2026-08-01T14:02:17.527740Z digest=sha256:7da7ec0e9446792d89285f515a9cc9d4d95bbbd99790bc6b53794ec35fdf6aa6

Observation 9571e6c4-ff18-4c25-b4db-2c61bcdb194c · outbound

This paper cites PhysMotion: Physics-Grounded Dynamics From a Single Image.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation PhysMotion: Physics-Grounded Dynamics From a Single Image

Reference 51

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source=pdf_text observed=2026-08-01T14:02:17.607444Z digest=sha256:490a300111b8b1a1b4425965f199c1fd6a873534da30a7deb891d7bb7694ea43

Observation c97436ff-9316-40f9-ae6b-4c609624593b · outbound

This paper cites Towards Accurate Generative Models of Video: A New Metric & Challenges.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 52

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source=pdf_text observed=2026-08-01T14:02:17.698731Z digest=sha256:84da1a2f1e93643b833d3c85e53e99fbbd283a4f1dadc1ca0fbf703b0c3a3816

Observation 89fa2bec-e56a-4521-b4af-e9638ae24a5e · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Wan: Open and Advanced Large-Scale Video Generative Models

Reference 53

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source=pdf_text observed=2026-08-01T14:02:17.765602Z digest=sha256:c995717b9f62db56b2a6a11464ef10a7d88686912626f71eeb66b01113f32dec

Observation 9d0f0a43-796d-435d-8ed6-837c78888612 · outbound

This paper cites WISA: World Simulator Assistant for Physics-Aware Text-to-Video Generation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation WISA: World Simulator Assistant for Physics-Aware Text-to-Video Generation

Reference 54

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source=pdf_text observed=2026-08-01T14:02:17.849564Z digest=sha256:3fc41255b013dada42c5d024bad6a552adf64f7c87f45b9e413b9569505693f0

Observation 4b83aea1-688c-4e48-a6c9-a8b388e2d883 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 55

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source=pdf_text observed=2026-08-01T14:02:17.930533Z digest=sha256:a8bf2c2ec9597208a22c019d9c03881cc16740145d566dcbc5018d94a5fd6fdf

Observation 26810570-59e6-4e37-85d8-288fca9841aa · outbound

This paper cites Motionctrl: A unified and flexible motion controller for video generation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Motionctrl: A unified and flexible motion controller for video generation

Reference 56

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source=pdf_text observed=2026-08-01T14:02:17.998072Z digest=sha256:8f0c116db88fda3477265e747113d14e87db4588d0fe2c0b3b691e38a47d3ac0

Observation fccec0f7-a0e3-4733-8679-05d40ebfb28e · outbound

This paper cites Physanimator: Physics-guided generative cartoon animation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Physanimator: Physics-guided generative cartoon animation

Reference 57

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source=pdf_text observed=2026-08-01T14:02:18.051417Z digest=sha256:afc53d6eaa52324480e03a97da5154adb1de2721574e78c62f44bc5d897b8fcf

Observation ba90ebb6-a518-4cc0-8c12-3e6dacd38979 · outbound

This paper cites Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems

Reference 58

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source=pdf_text observed=2026-08-01T14:02:18.123112Z digest=sha256:86e90f5840b75ecb67b4cdc1a31fed2bab36bd568796b70cc28ed5fe55976423

Observation f556f461-947a-4ff2-95fc-dc395931f5f8 · outbound

This paper cites Adding conditional control to text-to-image diffusion models, 2023.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Adding conditional control to text-to-image diffusion models, 2023

Reference 59

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source=pdf_text observed=2026-08-01T14:02:18.188573Z digest=sha256:62b6f2ae66cc853f3c1e86b6b9d4df26abb2b8cc5acbbb919c45e6e092b92b0e

Observation d0b2b008-9992-4eca-a527-0bf009ed72b2 · outbound

This paper cites Tora: Trajectory-oriented diffusion transformer for video generation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Tora: Trajectory-oriented diffusion transformer for video generation

Reference 60

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source=pdf_text observed=2026-08-01T14:02:18.278100Z digest=sha256:99e1a86c9b987fe99e4fd6263a3d50e911e895555272154860749c694580f7fc

Observation 0211c92b-4f20-4d7b-9cb1-8ba264dddddd · outbound

This paper cites Attention never lie: Visual attention defocus reveals and rectifies hallucinations in mllms.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Attention never lie: Visual attention defocus reveals and rectifies hallucinations in mllms

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source=pdf_text observed=2026-08-01T14:02:18.344030Z digest=sha256:e9f3a32008e6dae36303908dbd00bcc7c3e52fe24fe24865292fba2ccc468c70

Observation 587823ea-461d-4097-94a1-78a6f409df20 · outbound

This paper cites Extending one-step image generation from class labels to text via discriminative text representation.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Extending one-step image generation from class labels to text via discriminative text representation

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source=pdf_text observed=2026-08-01T14:02:18.402859Z digest=sha256:9a6cc3f580b4c4e94ef29da806c45b4eb30afe86d0932433e77e1cfc15f89551

Observation 12a80ab6-ce59-46f4-b579-44a15519e5f7 · outbound

This paper cites VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness

Reference 63

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source=pdf_text observed=2026-08-01T14:02:18.467232Z digest=sha256:96bbf0612f84ec4aaa088baca9cbc4270501ecf685b25a086025fbcb46f3ba9a

Observation 50ceef46-4673-42a3-9516-a86c91894d2f · outbound

This paper cites Open-Sora: Democratizing Efficient Video Production for All.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Open-Sora: Democratizing Efficient Video Production for All

Reference 64

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source=pdf_text observed=2026-08-01T14:02:18.505231Z digest=sha256:742e4d2d5d5bdd8216cdd665beb175b223c0ae28681b073686eaba409bddc209

Observation c438d6d5-5918-4e6b-9a0e-23f0ad30361b · outbound

This paper cites passes the criterion.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation passes the criterion

Reference 65

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source=pdf_text observed=2026-08-01T14:02:18.578051Z digest=sha256:34eaf3c618a088c189f2fcb2bcf17140c9b4ccdfaa1e5da2beff44a9858284c6

Observation 1bc49aa8-8505-4a26-a13a-6c84738bf56e · outbound

This paper cites an unresolved cited work.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Unresolved cited work

Reference 67

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source=pdf_text observed=2026-08-01T14:02:18.643398Z digest=sha256:f2a88dd3d9df3e57792f2ebfa84b571ca41b3a37b307a4601a59ffe1acb03b23

Observation 3b6ba6e2-b355-43fa-b8ed-d7544ba9999a · outbound

This paper cites yes" if the anomaly exists or.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation yes" if the anomaly exists or

Reference 68

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source=pdf_text observed=2026-08-01T14:02:18.682158Z digest=sha256:0a53415cd355277bda6671ebe8738cfee7c158f3d020c4c82e94f1cfeca42d1c

Observation 5ce67969-a8b9-48f9-9aed-00c75f726496 · outbound

This paper cites an unresolved cited work.

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation Unresolved cited work

Reference 2025

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source=pdf_text observed=2026-08-01T14:02:16.366309Z digest=sha256:965a60ff910950c71cc0f0caa53355a304feb3d66a4304eed4d0e93576c6f25f

Pith citing papers

No inbound Pith citation observations are available.