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Paper Citation Record · LEDGER

Inferring Dynamic Physical Properties from Video Foundation Models

As of 4 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 1 inbound Pith citation observation for arXiv:2510.02311.

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

pith.paper-citation-record.v1
2510.02311 v2

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-18T10:08:11.191706Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-03T06:30:56.289259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T16:39:48.066744Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-05-11T08:25:59.547530Z

Reference resolution

13 of 13 outbound references displayed

  • verified exact9
  • verified fuzzy0
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c0a10ac1-b6f2-4aeb-9670-ff93d76bbf30 · outbound

This paper cites V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.

Inferring Dynamic Physical Properties from Video Foundation Models V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-05-18T10:11:14.124897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T19:08:37.559938+00:00.

source=pdf_text observed=2026-05-18T10:08:11.191706Z digest=sha256:65ba3693b626d504d6c84a9c11efda8a8c242184591e00e51ad752504df77a86

Observation 25ada730-dc2c-4e25-add8-77e9bf2b3b62 · outbound

This paper cites FitVid: Overfitting in Pixel-Level Video Prediction.

Inferring Dynamic Physical Properties from Video Foundation Models FitVid: Overfitting in Pixel-Level Video Prediction

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-18T10:11:14.091739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-18T10:08:11.191706Z digest=sha256:120377a6712605725d48f59b584aa02f5d5c1a296ea4e7cd00e5a880cbc8b38b

Observation 2c61c12a-ae81-41a1-80d8-439fcb491d72 · outbound

This paper cites Physion: Evaluating Physical Prediction from Vision in Humans and Machines.

Inferring Dynamic Physical Properties from Video Foundation Models Physion: Evaluating Physical Prediction from Vision in Humans and Machines

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T10:11:14.077792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-18T10:08:11.191706Z digest=sha256:4a7c82ad0cd055cc6b67b383cdf23fd23f7e6224f093dcaa6f488ffb52170cc6

Observation 194b5971-ad98-4a16-93d3-226a9de2c8f6 · outbound

This paper cites IntPhys 2: Benchmarking Intuitive Physics Understanding In Complex Synthetic Environments.

Inferring Dynamic Physical Properties from Video Foundation Models IntPhys 2: Benchmarking Intuitive Physics Understanding In Complex Synthetic Environments

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-18T10:11:14.120780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-18T10:08:11.191706Z digest=sha256:1212d3cf6bc3ebb78abcad67be2db4f21cc16a00c3a7c859909e6bcc187cd3ad

Observation e204a321-5500-4328-b1d4-f98b59084edc · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

Inferring Dynamic Physical Properties from Video Foundation Models Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-05-18T10:11:14.086677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-18T10:08:11.191706Z digest=sha256:2eb44e9ed34d2bca0a232b81bc8b6ac119273a21d7d3a093078e3ed59a019efc

Observation 64f14fa2-5282-44f5-8c67-dc7ac03c36e9 · outbound

This paper cites Qwen2.5-Coder Technical Report.

Inferring Dynamic Physical Properties from Video Foundation Models Qwen2.5-Coder Technical Report

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-05-18T10:11:14.082077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-18T10:08:11.191706Z digest=sha256:92b2f5a011bd819c03c9eb7e31a50bc87eee754bd1b3c47f0cd19111d691153f

Observation 8f10d0c5-415c-4151-9c61-adcd2913227a · outbound

This paper cites GPT-4o System Card.

Inferring Dynamic Physical Properties from Video Foundation Models GPT-4o System Card

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-05-18T10:11:14.111332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-18T10:08:11.191706Z digest=sha256:b2c77b8614ea1b67ff2c1def4dfd3cb64c5080cb39bfe8bfc29932f03a6443dd

Observation b6a5120a-34cd-4f83-a67b-cc8af5fa2d0a · outbound

This paper cites Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models.

Inferring Dynamic Physical Properties from Video Foundation Models Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models

Reference 8

Resolution
metadata mismatch
local_arxiv, observed 2026-05-18T10:11:14.115902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-18T10:08:11.191706Z digest=sha256:23243830c971261b285b7a197d96deb17d5807955c5f0ca8522c8718ae4700e7

Observation dece223c-3007-4452-9fe6-297a53a2619b · outbound

This paper cites Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection.

Inferring Dynamic Physical Properties from Video Foundation Models Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-18T10:11:14.130025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-18T10:08:11.191706Z digest=sha256:942949cc8bd800038433ad4771c876f53275749f3c0a3b87df0226a853f29ffd

Observation 868c8a6e-4262-4fed-ab85-efd457621413 · outbound

This paper cites PhyX: Does Your Model Have the "Wits" for Physical Reasoning?.

Inferring Dynamic Physical Properties from Video Foundation Models PhyX: Does Your Model Have the "Wits" for Physical Reasoning?

Reference 10

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T10:11:14.096550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-18T10:08:11.191706Z digest=sha256:f994bbab8bb28acca42ab9df9f90f3af21c6e2f9d11f982fea8335198abd59e7

Observation 5f8f1274-55a1-446f-ab0f-b7a5fb363915 · outbound

This paper cites MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation.

Inferring Dynamic Physical Properties from Video Foundation Models MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-18T10:11:14.101774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-18T10:08:11.191706Z digest=sha256:3861c10e05562d205440ebe0fcf184236b7eb439240aae92b548ab77515d8b08

Observation 017c72d4-1fc6-41bc-8bf1-75af5e07c270 · outbound

This paper cites Neural Material: Learning Elastic Constitutive Material and Damping Models from Sparse Data.

Inferring Dynamic Physical Properties from Video Foundation Models Neural Material: Learning Elastic Constitutive Material and Damping Models from Sparse Data

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-05-18T10:11:14.106149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-18T10:08:11.191706Z digest=sha256:cb698ff6c15ec3e22d14d90dea83a36e026c567f85b308bd14782573cfa9fc9a

Observation ef303f17-9cd3-4915-8ba7-9fdc6dcca5a2 · outbound

This paper cites an unresolved cited work.

Inferring Dynamic Physical Properties from Video Foundation Models Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-05-18T10:11:15.546908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-18T10:08:11.191706Z digest=sha256:63d3d65380961d69c9a5e736f83a3a72e916f6fa86a1532e5aa90f766df523f5

Pith citing papers

Observation 08474cbc-18c0-4378-b47a-4d08e5a0a34c · inbound

PhysInOne: Visual Physics Learning and Reasoning in One Suite cites this paper.

PhysInOne: Visual Physics Learning and Reasoning in One Suite Inferring Dynamic Physical Properties from Video Foundation Models

Reference 96

Resolution
verified exact
local_arxiv, observed 2026-05-11T08:25:59.551046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T16:39:48.066744Z digest=sha256:7c43bc4eb2ebc8a3246ee8eed086604346fb8ba6dcab67fafbdf9521cceb97b1