Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-13T23:47:18.378887Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2603.16432.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-13T23:47:18.378887Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T20:36:25.583524Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-08T00:16:16.039225Z
42 of 42 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 12e35fcf-c37c-4ca9-8e7a-922d204bada9 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Discovering governing equations from data by sparse identification of nonlinear dynamical systems
Reference 1
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Unavailable: canonical work link unavailable.
Observation ab3ac489-ddb7-4ee4-a79a-380a116ff2f2 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Neural implicit representations for physical parameter inference from a single video
Reference 2
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Observation 32e4ddfe-25ee-459d-af82-898dd0a3398b · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video
Reference 3
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Observation 5513b9b3-6332-4a99-b8a1-14dcdd712bf4 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Distilling free-form natural laws from experimental data
Reference 4
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Observation 6fad6cfb-38df-4baf-8718-8906c96ff2b4 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video End-to-end differentiable physics for learning and control
Reference 5
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Observation 4fbae62d-c39b-4c38-80af-d0984862ab29 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Reasoning-modulated representations
Reference 6
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Observation f02bc278-beb5-4487-8b4c-dc5777ad942f · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Learning physics from video: Unsupervised physical parameter estimation for continuous dynamical systems
Reference 7
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Observation 85e5c642-0661-4141-84b5-270b348eec8d · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Vid2Param: Modeling of dynamics parameters from video
Reference 8
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Observation b23d2b8b-faa9-4828-b7db-7430a915e607 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Visual interaction networks: Learning a physics simulator from video
Reference 9
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Observation ef73ae54-bd72-477a-88dd-3cf13e2978ee · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Galileo: Perceiving physical object properties by integrating a physics engine with deep learning
Reference 10
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Observation e6115f54-a15f-4e33-aec4-62506aced1ee · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Learning to see physics via visual de-animation
Reference 11
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Observation fb7747b9-ef31-4044-b7b3-980f4ace0490 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Learning physics constrained dynamics using autoencoders
Reference 12
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Observation 06f5402a-b9f0-4c95-9c49-8411facc7328 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Unsupervised Learning of Latent Physical Properties Using Perception-Prediction Networks
Reference 13
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Observation 1db4aa99-585e-4a70-adc7-d26c4349fed3 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Hamiltonian Generative Networks
Reference 14
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Observation 6c449ec9-326c-487c-b4e9-6697aaf59274 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Neural ordinary differential equations
Reference 15
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Observation 516bc847-06f7-4f3c-9a04-09b09e73ef00 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Hamiltonian neural networks
Reference 16
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Observation 7c42f62b-1a33-4dd4-b15b-85d9c42eeeb1 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Lagrangian neural networks
Reference 17
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Observation 83b2dbf4-2ba0-4cf5-aaf4-998ce0fa3ba5 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Learning to simulate complex physics with graph networks
Reference 18
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Observation 05a0bab9-00c5-482d-97ed-4b4267a75c9d · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Interaction networks for learning about objects, relations and physics
Reference 19
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Observation 67f99abe-63bc-435c-b2e4-29c88d65c34a · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Physics 101: Learning physical object properties from unlabeled videos
Reference 20
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Observation 3316f9d7-8720-4fad-878a-da5248fddc35 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video VideoPhy: Evaluating Physical Commonsense for Video Generation
Reference 21
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Observation 1dff4f29-9e3e-45f7-9672-e89549ea78f8 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Do generative video models understand physical principles?
Reference 22
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Observation f750f504-a218-4fcd-97a7-b6fcafcdda61 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems
Reference 23
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Observation 5bc41635-32bd-45f0-a7d2-1591273abba0 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video R-Bench: Graduate-level Multi-disciplinary Benchmarks for LLM & MLLM Complex Reasoning Evaluation
Reference 24
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Observation 0f59def6-ee36-4c1d-b554-60f5e9ec83c0 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video WorldLens: Full-Spectrum Evaluations of Driving World Models in Real World
Reference 25
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Observation a9ad85fb-8212-4bd5-a369-05313b35f774 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video ChatGPT and open-AI models: A preliminary review
Reference 26
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Observation 1667bb38-7a17-4590-8d32-ff11b5668711 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Visual instruction tuning
Reference 27
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Unavailable: canonical work link unavailable.
Observation 5be8b61a-dfda-4b27-bc81-4460efdd1670 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video LLaVA-Video: Video Instruction Tuning With Synthetic Data
Reference 28
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Observation de8e6ea0-6c83-462b-9cec-a8d88273cbc4 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Physics context builders: A modular framework for physical reasoning in vision-language models
Reference 29
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Observation 57466bda-8ad0-4dfa-99b1-f59aa6804d92 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Mimicking the Physicist's Eye:A VLM-centric Approach for Physics Formula Discovery
Reference 30
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Observation 20219d37-858a-4a9a-803a-66820a450077 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Data-driven discovery of coordinates and governing equations
Reference 31
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Observation f2415a40-0bac-41ba-b9b7-fdc9c8faa063 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video MLLM-based Discovery of Intrinsic Coordinates and Governing Equations from High-Dimensional Data
Reference 32
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Observation 6727f560-1578-44dd-b129-903fc1df85f5 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video ContactGaussian-WM: Learning Physics-Grounded World Model from Videos
Reference 33
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Observation 9b4a8b2b-1118-4a8f-a4d5-badefde83d79 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Unresolved cited work
Reference 34
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Observation 4ac407ab-be80-4fdb-949e-b9048d4dc472 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video DiffSim: Taming Diffusion Models for Evaluating Visual Similarity
Reference 35
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Observation 8961102c-1d1c-40af-bf9f-77250146a415 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video A Differentiable Physics Engine for Deep Learning in Robotics
Reference 36
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Observation 063564de-bdd2-4752-99eb-42b190a35b78 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Fast and Feature-Complete Differentiable Physics for Articulated Rigid Bodies with Contact
Reference 37
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Observation 4f3e4aed-1c24-4a12-8c94-c116bad466d7 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video How to train your neural ODE: the world of Jacobian and kinetic regularization
Reference 38
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Observation c15a701f-a633-412a-833f-c99f41923a02 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video How to train your neural ODE: the world of Jacobian and kinetic regularization
Reference 39
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Observation 33754402-b35c-49aa-8865-7c33860eace8 · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Unresolved cited work
Reference 40
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Observation 3c2ea5e7-d399-4879-aea2-46b00e18056f · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets
Reference 41
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Observation 74a01880-85f0-44ba-8866-7d69373f1afe · outbound
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video SAM 2: Segment Anything in Images and Videos
Reference 42
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Observation db7f2479-7d49-4fc4-86dc-966cf7f54d0f · inbound
GAUGE: A Measurement-Grounded Benchmark for Physical Fidelity in Simulation Engines and Video World Models IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.