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Paper Citation Record · LEDGER

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models

As of 10 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2507.15824.

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

pith.paper-citation-record.v1
2507.15824 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:27:03.245735Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

  • verified exact0
  • verified fuzzy9
  • unresolved28
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dd05d835-036a-4d73-a28f-484ef0c0855e · outbound

This paper cites Cosmos World Foundation Model Platform for Physical AI.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Cosmos World Foundation Model Platform for Physical AI

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6d342f1d-ad5c-427e-b5bd-651c97f9a05e · outbound

This paper cites Impossible Videos.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Impossible Videos

Reference 2

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source=pdf_text observed=2026-08-06T15:27:00.284729Z digest=sha256:42eefe7b971edf6129c9731db18285e8d4a4240ef1a1b2a6fc33bbcf28f60865

Observation ab5d0084-29aa-49f1-8b60-e22e7e23eb9f · outbound

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

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models VideoPhy: Evaluating Physical Commonsense for Video Generation

Reference 3

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source=pdf_text observed=2026-08-06T15:27:00.383675Z digest=sha256:04d2fc62b7c6bc4c2f31e491c309910374af46e18de27662278fa43e23b7678a

Observation 5408ffb6-a523-4df4-b901-5475e57ec79a · outbound

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

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation

Reference 4

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source=pdf_text observed=2026-08-06T15:27:00.441134Z digest=sha256:d4e8aa4d4ae84876f85e12a84b4c0235f7938ba198301b8780e984b52a1e5a5c

Observation 0cd747e2-bf7b-4097-86cf-cb7ba2c3b498 · outbound

This paper cites PIQA: Reasoning about Physical Commonsense in Natural Language.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models PIQA: Reasoning about Physical Commonsense in Natural Language

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:00.511632Z digest=sha256:a3a3cebec9d1d4e42a5b9e1d8694f7d50bf2978301e84b549c079327b08609e0

Observation 68e9ff5b-fc7e-4e3a-ab78-bdd91f96d9c4 · outbound

This paper cites an unresolved cited work.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Unresolved cited work

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 06aaccd1-4251-4057-a12d-a536cd6bce6d · outbound

This paper cites an unresolved cited work.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Unresolved cited work

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:00.668523Z digest=sha256:aa03a3cc5e51bb9622d1125981373281ee4175bca54cb0ed91e674dfaac0a341

Observation 443a8733-255a-4e0c-a0c6-9a7208b88e23 · outbound

This paper cites an unresolved cited work.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Unresolved cited work

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:00.772417Z digest=sha256:44d74f4b349cade6966990080debc19b4ee73df3fcdf53587a3656cdf0bf4462

Observation 203b6b81-9be3-4821-981a-47ddeeb5ec0b · outbound

This paper cites Gemini 2.5 Pro.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Gemini 2.5 Pro

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-06T15:27:04.137144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:00.825849Z digest=sha256:dc365b9418f9ed4d497f132c570a56f635ea72b08547c787d317f6f45f8fb4bd

Observation b1f2d662-8e71-42d6-872c-e817f9b13f2b · outbound

This paper cites Gemini 2.5 Flash.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Gemini 2.5 Flash

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:00.897645Z digest=sha256:ca38e9a7871f7f6caf117f03e630c2c49c3c9111b96349dd9dd4c7e3f8b8620f

Observation 49e730d7-c9ba-457e-b563-20e622c9018f · outbound

This paper cites an unresolved cited work.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Unresolved cited work

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:00.996067Z digest=sha256:dde31be3e8908ea37328009c21f433c7b6f0ff81cb3c80926d34bb6f8a5cea7c

Observation e9be4478-8ace-4043-8239-d84d8ea79e36 · outbound

This paper cites LTX-Video: Realtime Video Latent Diffusion.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models LTX-Video: Realtime Video Latent Diffusion

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:01.156060Z digest=sha256:9803daea762a414122b2a8d665cd8bb478844377ab66f2f03585d5b639f24f78

Observation a72f13bd-15f5-4954-abc2-fc2f681ef209 · outbound

This paper cites Pre-Trained Video Generative Models as World Simulators.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Pre-Trained Video Generative Models as World Simulators

Reference 13

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source=pdf_text observed=2026-08-06T15:27:01.234367Z digest=sha256:38c97c1b3b922d2fe8067b050f426dcf738f931c4fba013bb6c860dad35317da

Observation af6b60e2-c63c-45b3-8c6b-cdf8d396e8b1 · outbound

This paper cites Hessel, A.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Hessel, A

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-06T15:27:04.064421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:01.325311Z digest=sha256:d850c93dddda4d1d117fdd774b3f33c72a935c4703beb8ec6823f72f98b34d14

Observation 6ec4b984-e348-489b-be63-be1a310b892a · outbound

This paper cites GAIA-1: A Generative World Model for Autonomous Driving.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models GAIA-1: A Generative World Model for Autonomous Driving

Reference 15

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source=pdf_text observed=2026-08-06T15:27:01.391505Z digest=sha256:9090db915b928f03460b295803bad4d3e07be4582067a11405676a89193fb086

Observation 4efc76c7-0511-40a7-895d-2155be20621c · outbound

This paper cites an unresolved cited work.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Unresolved cited work

Reference 16

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:01.441313Z digest=sha256:a8982ae8c8e3dc127fca77c440b1eaacc93bc7bff23cf9781da735fced4ce9a8

Observation 746c52b3-4100-4d68-a5ad-ffe926aa39fd · outbound

This paper cites Huang, H.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Huang, H

Reference 17

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raw_fallback, observed 2026-08-06T15:27:04.049667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:01.495108Z digest=sha256:5ce2053ec8004d589614133a867f7285377214f0f42658a41dbce1952e4a166e

Observation d3e8b807-4e35-4a51-9bb8-da81b28bb603 · outbound

This paper cites Huang, Y.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Huang, Y

Reference 18

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raw_fallback, observed 2026-08-06T15:27:04.032429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:01.576906Z digest=sha256:90c1d731eb1ad0c500da3a68db09bdadc6a778aabedb04c117ff68b93af56735

Observation fa7dc48a-ed60-4b45-a638-f94f94f50c2b · outbound

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

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 19

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source=pdf_text observed=2026-08-06T15:27:01.639928Z digest=sha256:ec26a44de5b68deb13620c696bd6b42c860bcc7ff8c2acb041718b443d69f898

Observation 06750cd7-951f-4862-acd7-51c0aaeca1bc · outbound

This paper cites an unresolved cited work.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Unresolved cited work

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:01.712330Z digest=sha256:c60d1395271b1f40eab72cb1f7a8f7d89e8122efcd263e0bf254a44ca4cc1643

Observation 8697019d-a8fc-476f-adc8-4201986812b1 · outbound

This paper cites an unresolved cited work.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Unresolved cited work

Reference 21

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:01.801312Z digest=sha256:cdd6a1e36c3ba99bc554becc1fc13984f23f248ad5c916f4aaa030aa107898c2

Observation 2dac2889-bf4f-47b0-b914-8a8391058d78 · outbound

This paper cites an unresolved cited work.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Unresolved cited work

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:01.865776Z digest=sha256:063d2e482a605e133103a0654a3e74d08b8176d58c5a1db01a2e31b73804e51f

Observation 78df88ff-b6a1-4c01-b8c2-34c05b4f63a7 · outbound

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

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models

Reference 23

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:01.918575Z digest=sha256:eadf31524d5a4d13ed0ad0f8d20edf8698b2e099476c7e36f3af20fd83f8038f

Observation 27178bec-ac2b-4eb9-81d7-9bd31f9552fe · outbound

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

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation

Reference 24

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source=pdf_text observed=2026-08-06T15:27:01.977216Z digest=sha256:04641c5e2b4eb17492ed250242f2c6081e272dba1673ca56d779ae5b49832035

Observation c9861670-97bb-4563-b7f1-469724aed6ba · outbound

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

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Do generative video models understand physical principles?

Reference 25

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no resolver link, observed 2026-08-06T15:27:02.052076Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:02.052076Z digest=sha256:fc90a6c17d06076b7cd8dbaf2ded8c1244b62444a746b2e8434907efca4d07bd

Observation dd65b5ba-7e32-48b4-8fda-d7d3f0d98802 · outbound

This paper cites Sora: Generating videos from text, 2025.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Sora: Generating videos from text, 2025

Reference 26

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raw_fallback, observed 2026-08-06T15:27:03.949098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 83d1dd11-8178-4bb1-b895-5aff8986a35f · outbound

This paper cites Gen-3 Alpha.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Gen-3 Alpha

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-06T15:27:03.931477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:02.234677Z digest=sha256:edf88240f24d75015ea5cdb63252e3b6d9234248fe50b7edd50ed2e301a09406

Observation 2ca34fe6-b039-42c7-8c55-7e16e86dfc42 · outbound

This paper cites Salimans, I.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Salimans, I

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-06T15:27:03.911290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:02.385510Z digest=sha256:7aa00360f68c2186af381570131ed1ba77bec62d6ddf57fbfaf38dd280a9ef1c

Observation bc2a468d-5cd6-4fd3-bffa-f615d734e8e7 · outbound

This paper cites Magi-1: Autoregressive video generation at scale, 2025.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Magi-1: Autoregressive video generation at scale, 2025

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:27:03.893828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:02.553838Z digest=sha256:c327295bd8c31c7929b636073f879bac46ec549eeba72847be35e2293cc3df37

Observation b4ea5221-cc9e-4341-8817-fc93eac75d0a · outbound

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

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 30

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no resolver link, observed 2026-08-06T15:27:02.698103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:02.698103Z digest=sha256:0cf73fc478df24f316daa8793f86f019fdb4a6c3b3b36d3132c0594df397b275

Observation 6f08ae1b-8495-4218-9ab9-857cabf24641 · outbound

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

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Wan: Open and Advanced Large-Scale Video Generative Models

Reference 31

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no resolver link, observed 2026-08-06T15:27:02.864867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:02.864867Z digest=sha256:bdf88841cfa58fb369b23b5111f758e26618ad27823b0f4e004f3dbd32e41e7a

Observation fe0eb035-5071-4400-b47a-e6a17f6bbff8 · outbound

This paper cites WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens

Reference 32

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no resolver link, observed 2026-08-06T15:27:02.986657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:02.986657Z digest=sha256:bc173fe6dd577367f4446c73e2d35407cb5726de3e189df7507456e0089e4bf3

Observation b6464209-3ee2-44bb-89d8-af07f222587f · outbound

This paper cites an unresolved cited work.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Unresolved cited work

Reference 33

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unresolved
raw_fallback, observed 2026-08-06T15:27:03.876651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:03.109495Z digest=sha256:66e27a9ff0c5f7223bcf8abd03633d4657fce01dba8bf01ee18a563425b3e748

Observation 8b847a99-dda7-4fbd-a632-715a95042b47 · outbound

This paper cites an unresolved cited work.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Unresolved cited work

Reference 34

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unresolved
raw_fallback, observed 2026-08-06T15:27:03.857513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:03.230414Z digest=sha256:59b8dca50da340f6709e13b3cf2a73088760deb5d2f6d069395f60657a636d5c

Observation 144296a1-b1b6-42ab-a870-9fc2f61ec084 · outbound

This paper cites MAGVIT: Masked Generative Video Transformer.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models MAGVIT: Masked Generative Video Transformer

Reference 35

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unresolved
no resolver link, observed 2026-08-06T15:27:03.235158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:03.235158Z digest=sha256:5bc9007d5acb50d12ac6cb03a598df3d4f26a3b9f8f15dfce540b4f6932b6d72

Observation 7b25baba-56db-4676-8722-d9ea2ea759f3 · outbound

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

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T15:27:03.240621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:03.240621Z digest=sha256:48bff30735bc84fa6f2caf1ce523a34fc0647a3529d0dd0c7d23d3a19ea85247

Observation b82d2d0f-ccd5-4d98-a987-6b562a6e5018 · outbound

This paper cites are” rather than what agents can “do.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models are” rather than what agents can “do

Reference 37

Resolution
malformed identifier
raw_fallback, observed 2026-08-06T15:27:03.834877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:03.245735Z digest=sha256:9b6f9e3281dee2d3857624d1f69f8032ec22f884e4652dc9446627b398ef0e50

Observation 9e4b52cf-bc2b-4562-9aac-05d737f56107 · outbound

This paper cites an unresolved cited work.

Can Your Model Separate Yolks with a Water Bottle? Benchmarking Physical Commonsense Understanding in Video Generation Models Unresolved cited work

Reference 2025

Resolution
unresolved
raw_fallback, observed 2026-08-06T15:27:04.082066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:27:01.065176Z digest=sha256:506940e2fbbdbdee24fc97fa7d3204e46b7ad58b0202033428f0d302313b5bdc

Pith citing papers

No inbound Pith citation observations are available.