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Paper Citation Record · LEDGER

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios

As of 18 August 2026, this Paper Citation Record lists 87 of 87 outbound references and 3 inbound Pith citation observations for arXiv:2605.27589.

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

pith.paper-citation-record.v1
2605.27589 v1

Coverage vector

measured 87 of 87 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T18:23:22.987086Z

measured 90 of 90 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:23:57.855823Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T00:42:28.645519Z

Reference resolution

87 of 87 outbound references displayed

  • verified exact29
  • verified fuzzy0
  • unresolved53
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9817bffe-18d3-4a50-837e-55dd37ce36a5 · outbound

This paper cites Don’t just assume; look and answer: Overcoming priors for visual question answering.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Don’t just assume; look and answer: Overcoming priors for visual question answering

Reference 1

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:7a40eb6f98cefb2124fea639ad7081d7b23e7b29ff63fe0940e005e2902e2f74

Observation c75cbfc4-9f54-4357-a9ff-a898761b3113 · outbound

This paper cites CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning

Reference 2

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arxiv_id, observed 2026-06-29T18:23:50.372993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:3d972bbf5bbb9b235bd20bf213585d9d7d6a5bc822baeac9d0e68ab181cfab13

Observation 7cfd86f1-b242-4fd6-92ef-9e9ec2370a0f · outbound

This paper cites World Simulation with Video Foundation Models for Physical AI.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios World Simulation with Video Foundation Models for Physical AI

Reference 3

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local_arxiv, observed 2026-06-29T18:23:50.356445Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:7a50e50f8b7f4a14051c791a51ec2b7fe7f032957d6e9e032c44874aa17f5321

Observation 9aab2aee-4dec-4410-9613-f22203df1d5c · outbound

This paper cites Diffusion for world modeling: Visual details matter in atari.Advances in Neural Information Processing Systems, 37:58757–58791, 2024.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Diffusion for world modeling: Visual details matter in atari.Advances in Neural Information Processing Systems, 37:58757–58791, 2024

Reference 4

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:02bc34dd643414f7cbb2805e0e5ca7f934ffeddb041673aaace5e7f1af4d0735

Observation d6b6c614-3f3b-4e95-be0e-e4f949ff3ca4 · outbound

This paper cites Craft: A benchmark for causal reasoning about forces and interactions.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Craft: A benchmark for causal reasoning about forces and interactions

Reference 5

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:6e06eadc88794ac29c39e36668a438883989969f288ddba5ee6e170baf4838b5

Observation 12a4c019-abaa-4e24-8929-201afb63a3e9 · outbound

This paper cites Video pretraining (vpt): Learning to act by watching unlabeled online videos.Advances in Neural Information Processing Systems, 35:24639–24654, 2022.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Video pretraining (vpt): Learning to act by watching unlabeled online videos.Advances in Neural Information Processing Systems, 35:24639–24654, 2022

Reference 6

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:6dbfe5f07d0fb402e1aec5c51bd096337054a7f37d777a06ad8b17914f365a3e

Observation 3cc44c25-4f97-4711-981d-5fdb8aba95aa · outbound

This paper cites Phyre: A new benchmark for physical reasoning.Advances in Neural Information Processing Systems, 32, 2019.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Phyre: A new benchmark for physical reasoning.Advances in Neural Information Processing Systems, 32, 2019

Reference 7

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:802967ba50427610882c5485145d92429ec1862b3b5823acd8debad04ec1af56

Observation c91c5537-f295-4cd6-b394-257b7eeb2e4d · outbound

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

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios VideoPhy: Evaluating Physical Commonsense for Video Generation

Reference 8

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local_arxiv, observed 2026-06-29T18:23:50.440484Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:f9ec197b1ddc9ebe7d9a6a7b3b0c717c3b945852fc185c91a14ee440d0676974

Observation 2dc8fd89-4e71-47a0-8c81-0f5c24d823d7 · outbound

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

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation

Reference 9

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arxiv_id, observed 2026-06-29T18:23:50.403328Z

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:a3dc660b41c582bc71d343f6d1e2893dcf54321e7e608acec31f5d7922939a02

Observation 38e11ad2-a35f-4070-b045-60fdc2c9e13d · outbound

This paper cites Revisiting Feature Prediction for Learning Visual Representations from Video.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Revisiting Feature Prediction for Learning Visual Representations from Video

Reference 10

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:8fa021aaad1545c35f84ed017916f56cbc4c5328a4d75a2dfd3d86e2e6cff800

Observation 46fb538a-0dc0-4ca4-a3ee-3eb9bcefe0d3 · outbound

This paper cites Using thematic analysis in psychology.Qualitative research in psychology, 3(2):77–101, 2006.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Using thematic analysis in psychology.Qualitative research in psychology, 3(2):77–101, 2006

Reference 11

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:10233e0466afe0427ed1b9c25f0411230dc33a6655841bb9177c258be98ebcfd

Observation 2f86de51-cc75-4292-82dc-5ceede2f945c · outbound

This paper cites an unresolved cited work.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Unresolved cited work

Reference 12

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:05d6e8bc9a652affd94fbc9282c00966f554c6f7f25c0426fbce6c96cc01bf9f

Observation 91cfe143-d622-467a-a4ca-2d2f5448dc01 · outbound

This paper cites Genie: Generative interactive environments.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Genie: Generative interactive environments

Reference 13

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:447743c386660e173d55909ec0a9ef48434918b9beb6e191732f4cfe839f0a43

Observation b9c39e98-a094-4114-bb39-cdbb2312030c · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios nuscenes: A multimodal dataset for autonomous driving

Reference 14

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:535685dc8b6de8be7de8ea16c17142aa087e94d445cfe82aa032301fa9a392bc

Observation 70f85be1-409b-42f7-a307-60c01363c5cf · outbound

This paper cites VRAG: Learning World Models for Interactive Video Generation.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios VRAG: Learning World Models for Interactive Video Generation

Reference 15

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local_arxiv, observed 2026-06-29T18:23:50.443323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:e394c205e2ce60d60d0e9d6697a9c6c60a3e8b340ba6483d494d6570fa66cbca

Observation 2893582a-4971-4839-a496-b1445e394b71 · outbound

This paper cites Unveiling causal reasoning in large language models: Reality or mirage?Advances in Neural Information Processing Systems, 37:96640–96670, 2024.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Unveiling causal reasoning in large language models: Reality or mirage?Advances in Neural Information Processing Systems, 37:96640–96670, 2024

Reference 16

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:ea60d8eca54f922163d699d359adc7fda69370a0b37b95dec43963daa680dfb1

Observation 94a86343-012c-469a-8188-95c222dcff54 · outbound

This paper cites Veo 3.1 technical report.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Veo 3.1 technical report

Reference 17

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:7d82cb6b1939bad10adb30b39181ceef39a524326134f75cfd91661871fb3735

Observation 39d58627-e050-4e19-bd4d-81297e23212e · outbound

This paper cites Worldscore: A unified evaluation benchmark for world generation.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Worldscore: A unified evaluation benchmark for world generation

Reference 18

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:c56e78f58739cf01231edb9bb588050f0f0712b2654bbe7d3695b74c2a193da3

Observation 5447d01b-d4c6-4827-988c-d999c60e73cf · outbound

This paper cites CausalVQA: A Physically Grounded Causal Reasoning Benchmark for Video Models.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios CausalVQA: A Physically Grounded Causal Reasoning Benchmark for Video Models

Reference 19

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arxiv_id, observed 2026-06-29T18:23:50.387373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:8f9104cd7637a17af1b334f9aa055959717558889a137380192e1142fa3a933a

Observation bfc4ef56-7b17-4eb3-895a-5e20d9219925 · outbound

This paper cites Physically grounded vision-language models for robotic manipulation.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Physically grounded vision-language models for robotic manipulation

Reference 20

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:0db17319a66d784dabdf4ccc63c298180aed43ed24acf0710c60adcd73d6f9bb

Observation e07c8478-39c6-4e0f-b2fa-be1aff78a821 · outbound

This paper cites Vista: A generalizable driving world model with high fidelity and versatile controllability.Advances in Neural Information Processing Systems, 37:91560–91596, 2024.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Vista: A generalizable driving world model with high fidelity and versatile controllability.Advances in Neural Information Processing Systems, 37:91560–91596, 2024

Reference 21

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:1e0c4532487be641ba0ef65ec4e09d06a76fad1c8de7a5eefb9768b1bcd82fc3

Observation a14a540c-bb22-4d19-960b-51e86d01760c · outbound

This paper cites Shortcut learning in deep neural networks.Nature Machine Intelligence, 2(11):665–673, 2020.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Shortcut learning in deep neural networks.Nature Machine Intelligence, 2(11):665–673, 2020

Reference 22

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:f1873807944ffaa2610439a453dbcd59eb0adec1676d7f14cb90046e35d9a700

Observation 9758491e-52e3-419f-92c0-c140056475ef · outbound

This paper cites CATER: A diagnostic dataset for Compositional Actions and TEmporal Reasoning.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios CATER: A diagnostic dataset for Compositional Actions and TEmporal Reasoning

Reference 23

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:7cd3b4dedd03cc539c6261f009c12bab061574c7c70d57f7ed780b5833c6e41d

Observation e8feec49-3b22-47ea-869e-112fb719c402 · outbound

This paper cites Genie 3: A new frontier for world models.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Genie 3: A new frontier for world models

Reference 24

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:f69af8f9b2b11eb7ad8941c7932c5114870f2033fc35d63881ec1c6eb1af7c76

Observation bb8ee50c-75e4-4aa2-9537-016f91649e4a · outbound

This paper cites Agqa: A benchmark for compositional spatio-temporal reasoning.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Agqa: A benchmark for compositional spatio-temporal reasoning

Reference 25

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:2090fa88a053e3395dc75231ac694f5f5de30cbdb75b8aa9223c74f8a287dcba

Observation 9b918a7f-00bf-4a7a-a66c-bf48fd0a7dd7 · outbound

This paper cites The Essential Role of Causality in Foundation World Models for Embodied AI.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios The Essential Role of Causality in Foundation World Models for Embodied AI

Reference 26

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:65781d9ecb1bbb95065b992332d9af5eb25d6a6119675a7836b325780b397d2e

Observation 7b87d8bf-ad92-4d59-9fae-8665b2feabdd · outbound

This paper cites Mastering Diverse Domains through World Models.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Mastering Diverse Domains through World Models

Reference 27

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local_arxiv, observed 2026-06-29T18:23:50.411638Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:63da1e7bb02ad98b590fac00644d11e842c6163380a9ab17e1443d13ec40cebe

Observation c30405d9-a706-4b6d-baa1-2b79e4a6fbc7 · outbound

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

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios GAIA-1: A Generative World Model for Autonomous Driving

Reference 28

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:17405ef7c156bd8ee73cd8f0085b7316141b0c9bf00f7d0b7c7d8d5b17033f22

Observation 6d2227b6-a2d7-40b1-aa9c-10a6e24ebbf5 · outbound

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

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Vbench: Comprehensive benchmark suite for video generative models

Reference 29

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:14d7dbef0d7f4bb987d1f1d074b52c24c36ea88ae902e51c8be027f93922c064

Observation e3012064-5443-4880-b537-77fdb92113e3 · outbound

This paper cites Vbench++: Comprehensive and versatile benchmark suite for video generative models.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Vbench++: Comprehensive and versatile benchmark suite for video generative models.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

Reference 30

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:1cc05f65e30b89ffe1aec255876963c369c1977d91143271ec598decf83c8299

Observation 7fea6898-1e36-4fd8-9607-5c96b0cb4923 · outbound

This paper cites How far is video generation from world model: A physical law perspective.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios How far is video generation from world model: A physical law perspective

Reference 31

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:cf1e4b3451f6471900765b00e3bc1b77a4482bca5511ce637746edd6cb7ecb66

Observation 05aa365d-cd2d-4a2b-9462-d5e0a366c37d · outbound

This paper cites DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

Reference 32

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:79693d6046ecf56db89c61b78adf9fcd0399f72f96f4fc1c7bfbc4604277c50f

Observation 99c92f26-4afe-4495-9a74-dd4f30599f77 · outbound

This paper cites Kie.ai ai model api platform, 2026.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Kie.ai ai model api platform, 2026

Reference 33

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:26429fdeb3af149782a65edd1dd1f900b3735fb89e682f64168c7578da3362e8

Observation fb302278-bdc5-4002-9573-9452b2770e9c · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios OpenVLA: An Open-Source Vision-Language-Action Model

Reference 34

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local_arxiv, observed 2026-06-29T18:23:50.409119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:30b2f24d44c9584a04f772cb3ad41e52fc47770b22f4dc27c39e92b173bb1cbf

Observation 84de40a7-289b-4d2d-a6e3-308ea4873384 · outbound

This paper cites Causalvlbench: Benchmarking visual causal reasoning in large vision-language models.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Causalvlbench: Benchmarking visual causal reasoning in large vision-language models

Reference 35

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:4305a66a0930b05796e70b35b534e57e2aa5e8383320551c76929a187754df8c

Observation c95dfd25-f6ac-4c47-9198-e9458392e99a · outbound

This paper cites WorldModelBench: Judging Video Generation Models As World Models.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios WorldModelBench: Judging Video Generation Models As World Models

Reference 36

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arxiv_id, observed 2026-06-29T18:23:50.390311Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:50b16be0f39664110ab2afc7fbe7c0348a94d4680c73debc7071d5ad100139cb

Observation 21c1f094-bd9f-4ef8-9dcf-6764cd417f65 · outbound

This paper cites Multimodal Causal Reasoning Benchmark: Challenging Vision Large Language Models to Discern Causal Links Across Modalities.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Multimodal Causal Reasoning Benchmark: Challenging Vision Large Language Models to Discern Causal Links Across Modalities

Reference 37

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arxiv_id, observed 2026-06-29T18:23:50.361767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:76815f78717d539bdbd927a738441c3fd1ab8d5c691606d1baa2999286a9d960

Observation 80c2dc4c-7e88-4606-a8c5-1a03c995ee08 · outbound

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

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Physgen: Rigid-body physics-grounded image-to-video generation

Reference 38

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:e9bc4401d840ca35de94777b74a8142bc025aaa1e5f664091df816ece8927d5a

Observation ed1683d1-5acf-4be1-a8c4-91ac7b0806a6 · outbound

This paper cites G-eval: Nlg evaluation using gpt-4 with better human alignment.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios G-eval: Nlg evaluation using gpt-4 with better human alignment

Reference 39

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:cb037ab7d56a96d772fcdbeeb1d37ae96fd7d0690c0090ef9bfb374704a83bcc

Observation 6639408d-a99a-46e7-a02d-f4e8fd88a0f6 · outbound

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

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Evalcrafter: Benchmarking and evaluating large video generation models

Reference 40

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:bd508544f27ccaf7b242f4a1d5e4a07851118716b49bd18f60d25dd1fea92f38

Observation a45a101d-2b4d-4e0b-bc7c-ec70f494a13a · outbound

This paper cites Compositional Causal Reasoning Evaluation in Language Models.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Compositional Causal Reasoning Evaluation in Language Models

Reference 41

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:c0e95396662ea22d10e927840301c3466a1fec793b2e928c873ee7bc2d8fcea7

Observation 6b3c9c2e-891f-4cee-bac8-5e222da552d2 · outbound

This paper cites Towards world simulator: Crafting physical commonsense-based benchmark for video generation.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Towards world simulator: Crafting physical commonsense-based benchmark for video generation

Reference 42

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:389c4daa4725cb855a4ae8f9d29f73dab3911e4a71a5364f5e15f11cefcd4319

Observation f7fc9a5d-dec4-4ff6-b463-4303b3154eb5 · outbound

This paper cites Do gener- ative video models understand physical principles? InProceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pages 948–958, 2026.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Do gener- ative video models understand physical principles? InProceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pages 948–958, 2026

Reference 43

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:e1ca4670210d80498b97226560d4d31e888cc0eb1cf1c5edac9db8986fecf4b1

Observation 811846ca-6884-4de8-a148-cd0805913723 · outbound

This paper cites Counterfactual vqa: A cause-effect look at language bias.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Counterfactual vqa: A cause-effect look at language bias

Reference 44

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:b903caedd7beba449bc64a3d790ff6cff7de9e51cdf1de3939e6549b1854a0b4

Observation 748d0ae3-bed2-4e53-88da-35f9d93547b3 · outbound

This paper cites Video generation models as world simulators.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Video generation models as world simulators

Reference 45

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:fe9d14f39d8d6c17ff74874f820342d95871284240e176fc19b59da05f01f936

Observation 2828a563-fde3-41dd-8e4a-8caa2234857d · outbound

This paper cites Open x- embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collaboration 0.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Open x- embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collaboration 0

Reference 46

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:4a3a0910733da7265bb07294d2e569463644ec01f768ab3211d834cbcbbf88e2

Observation 4fd0ee5a-5488-43f6-afb2-33dede048484 · outbound

This paper cites an unresolved cited work.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Unresolved cited work

Reference 47

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:6e6039cec3ae5e6bfe89408e62020931b5946ef6e002ad25efc1dfdc3ab51b91

Observation 00d18cf0-d906-4304-82af-8ce383394ba2 · outbound

This paper cites Cripp-vqa: Counterfactual reasoning about implicit physical properties via video question answering.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Cripp-vqa: Counterfactual reasoning about implicit physical properties via video question answering

Reference 48

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:cfe26e6bb146fc39aa00473a92688623ffbdd8dafcae3eff2279f8be790ee52f

Observation 4746c20f-93ba-45d0-8f59-4bb2c4411309 · outbound

This paper cites Cambridge university press, 2009.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Cambridge university press, 2009

Reference 49

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:cf30c66763d7934d4c887e6a5c661ea2ad608dcadca1d8b0d8c0e17f9fc3cd15

Observation e7fc84b7-fcc1-4d79-b2ce-08f08665d270 · outbound

This paper cites WorldSimBench: Towards Video Generation Models as World Simulators.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios WorldSimBench: Towards Video Generation Models as World Simulators

Reference 50

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:e86219c8d166a63ef91ef6b7d444e81f4d409b004ea29b80715e37c31a56832e

Observation 96d1a665-1de3-4f34-88c1-97d690c24b7d · outbound

This paper cites Toward causal representation learning.Proceedings of the IEEE, 109(5):612–634, 2021.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Toward causal representation learning.Proceedings of the IEEE, 109(5):612–634, 2021

Reference 51

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:7ca4fc8d1e8e4c16e70e0b6b20af8972489b7a12d53d8e5efcac3dcbd78474e5

Observation f8a645cc-70f2-4ce5-9cf5-c13afee3d265 · outbound

This paper cites Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model

Reference 52

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:1344cd2867193bbcfea484e7388cb83d771072980f18050ff11332a527d30470

Observation 1e34c705-1103-45cc-9cbc-bf50363e3408 · outbound

This paper cites Seedance 2.0: Advancing Video Generation for World Complexity.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Seedance 2.0: Advancing Video Generation for World Complexity

Reference 53

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local_arxiv, observed 2026-06-29T18:23:50.392770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:08ff79bc55eb8cda3a6b6aad7a9adaadf138a804161cd9b9ac021e861bd06b20

Observation c5020912-8b41-4953-a293-15d2da57521f · outbound

This paper cites Worldarena: A unified benchmark for evaluating perception and functional utility of embodied world models.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Worldarena: A unified benchmark for evaluating perception and functional utility of embodied world models

Reference 54

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:efb5972c147dec3966a09a020d30ccc289f85d5467dd5eb257af28e904b1dd22

Observation 23897052-9e9c-4964-b660-826ca03b00f2 · outbound

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

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios T2v- compbench: A comprehensive benchmark for compositional text-to-video generation

Reference 55

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:a34d070fcd5a335dc2f161340061d395cb877016be8320c2a91d58bac81825e5

Observation bdd7aa5c-58cb-4ac9-a7f7-48fddab4f1ad · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Gemini: A Family of Highly Capable Multimodal Models

Reference 56

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:8f7e6af064e3ccea2c20b0f1aaabb2b7db9cb18682ba8cef989dc43ea035d156

Observation ee9f6de7-f860-4d0c-8c85-b069dd08ac54 · outbound

This paper cites Kling-Omni Technical Report.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Kling-Omni Technical Report

Reference 57

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:2cabf8688c46c91d5fd24110e3322bc27df42638d09f037e30e250d4e09a6092

Observation 64ae3862-2a3f-435f-a749-0f0684852523 · outbound

This paper cites Winoground: Probing vision and language models for visio-linguistic compositionality.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Winoground: Probing vision and language models for visio-linguistic compositionality

Reference 58

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:a593679e3f1174e9222ff3cac67192f5889721a8e407d021068de060fa11a7b0

Observation 1d868501-14df-46fd-ba99-96a22601e8e2 · outbound

This paper cites an unresolved cited work.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Unresolved cited work

Reference 59

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:b55064c5e63c111e8b53bc9c685e46e8a857ddb4857ca69334e44d04cf636669

Observation d0b7ad6b-b23b-4243-b012-d86f03c1d864 · outbound

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

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Wan: Open and Advanced Large-Scale Video Generative Models

Reference 60

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local_arxiv, observed 2026-06-29T18:23:50.437754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:e17f7945c86f3291f19b017361592145c16c010d3820083de29beeaa0546d2ac

Observation 01b56f1f-cef5-4c33-b99d-f034051f4bfe · outbound

This paper cites GenSim: Generating Robotic Simulation Tasks via Large Language Models.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios GenSim: Generating Robotic Simulation Tasks via Large Language Models

Reference 61

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arxiv_id, observed 2026-06-29T18:23:50.426578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:ba9e674b147300a002fc061f3229b7e2ff7a798b7c517564c35ecf7785f42f78

Observation 849fa882-b67a-4c3d-9470-37825e937304 · outbound

This paper cites Large language models are not fair evaluators.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Large language models are not fair evaluators

Reference 62

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:80a911962e32edb70222191b1a9d2b3966b242803a02d3b87f41598a19f8d9ce

Observation ccc1480c-ff55-4f80-96ce-0059d1fada48 · outbound

This paper cites Omnidrive: A holistic vision-language dataset for autonomous driving with counterfactual reasoning.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Omnidrive: A holistic vision-language dataset for autonomous driving with counterfactual reasoning

Reference 63

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:681b2827458ba1a2756c61d300af97531beafb88a987229b47b48f101cf6ad45

Observation 3859a7cf-1f9f-40a8-bdc7-44fe4e28fd05 · outbound

This paper cites Drive- dreamer: Towards real-world-drive world models for autonomous driving.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Drive- dreamer: Towards real-world-drive world models for autonomous driving

Reference 64

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:b5ac125a31c7c6e22f29f7e6efecdc7f28399523add7168dfd516d44193a9a60

Observation b6f9ff10-1ac0-4d90-8520-dcf54c305edf · outbound

This paper cites Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail

Reference 65

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local_arxiv, observed 2026-06-29T18:23:50.367490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:cf7d335c3eeb0343d1119af9801540eec600a1165f08a2f6cba4cc8094e9c377

Observation 3a454eaf-2584-4e77-8d5c-74bd66c6e61b · outbound

This paper cites Causalbench: A comprehensive benchmark for evaluating causal reasoning capabilities of large language models.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Causalbench: A comprehensive benchmark for evaluating causal reasoning capabilities of large language models

Reference 66

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:468649c2d19c00745f815cdc4ed47ae5de592be58c8d211f40225903f495b42f

Observation 02e07769-2bae-43ab-9b93-72549519475a · outbound

This paper cites HunyuanVideo 1.5 Technical Report.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios HunyuanVideo 1.5 Technical Report

Reference 67

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local_arxiv, observed 2026-06-29T18:23:50.370134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:a9b4e8c92b3bcafe26c280da30410869bfd1297b231d4d36d06176519bd7603b

Observation 0e77163e-16be-4107-86bd-f14845461c73 · outbound

This paper cites STAR: A Benchmark for Situated Reasoning in Real-World Videos.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios STAR: A Benchmark for Situated Reasoning in Real-World Videos

Reference 68

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arxiv_id, observed 2026-06-29T18:23:50.384160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:45198bceaecbf35ed0bfd86097ec8486d2d61d3cc796901bb4967070c4373cdc

Observation 52cfe877-7da2-4a7f-9825-16c53dc2f7f2 · outbound

This paper cites Video World Models with Long-term Spatial Memory.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Video World Models with Long-term Spatial Memory

Reference 69

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arxiv_id, observed 2026-06-29T18:23:50.422893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:a352cf7d2474d219530784f78e2892e2836fa3457ef2cc54920f545f11454d06

Observation b92568bb-c81a-411e-8341-c5a1aa543c37 · outbound

This paper cites Grok imagine: Multimodal image and video generation model, 2025.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Grok imagine: Multimodal image and video generation model, 2025

Reference 70

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:17add9fab237646ee0d1c86f2d28ad631c17af90bb20d8b130b9247f80b244dc

Observation 71909a19-4e14-4a2d-89fc-7428a5bbcc85 · outbound

This paper cites Next-qa: Next phase of question- answering to explaining temporal actions.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Next-qa: Next phase of question- answering to explaining temporal actions

Reference 71

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:29b04e1fffa11e0a7213cb8f34ee6e8f71ef48a6fe9ec6d05b02e9d36785b625

Observation 42b1f6a7-10fa-4aae-b144-9add24c930a7 · outbound

This paper cites Unisim: A neural closed-loop sensor simulator.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Unisim: A neural closed-loop sensor simulator

Reference 72

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:f65edf828009b4d1a4b55b84f5d3bd530adb89acc1b1c6358392b9e69365a87a

Observation 39a1d28c-5111-4589-a2b1-1d18d4d3ccec · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 73

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local_arxiv, observed 2026-06-29T18:23:50.446357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:fcb3a5e568e5195bee17c798441cbafbd29428e8c24520d70094ee143e098c9a

Observation 51c52bc1-dd3e-4674-a0fe-25c1540fdc1a · outbound

This paper cites Tenenbaum.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Tenenbaum

Reference 74

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:c8d512ae481a4e887f73cf606d1e90576cf974fd8ba93f157142cc1a8d798b4b

Observation fe3173a2-4724-4ca7-aaed-e942764f59a5 · outbound

This paper cites Chronomagic-bench: A benchmark for metamorphic evaluation of text-to-time-lapse video generation.Advances in Neural Information Processing Systems, 37:21236–21270, 2024.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Chronomagic-bench: A benchmark for metamorphic evaluation of text-to-time-lapse video generation.Advances in Neural Information Processing Systems, 37:21236–21270, 2024

Reference 75

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:98641b956e814b5d084ef2ae9cedfa8ecf097ae39064c47985e3b7570e04ef6b

Observation c2a4d166-a776-4cf3-a84c-013c05566a01 · outbound

This paper cites Magicbrush: A manually annotated dataset for instruction-guided image editing.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Magicbrush: A manually annotated dataset for instruction-guided image editing

Reference 76

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:9f36f0f8c24f7af3055f0e3ff1caa46ba24c862e4dd70a0715e739f7c160a183

Observation 94fa7883-bdb0-4bd1-a817-7a5bdcaf72ca · outbound

This paper cites TesserAct: Learning 4D Embodied World Models.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios TesserAct: Learning 4D Embodied World Models

Reference 77

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arxiv_id, observed 2026-06-29T18:23:50.417573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:8855252cbffe881961af147d9c5118568d1d56c19ce83005bfe926525f37d47a

Observation aaddc02a-7f16-4cdc-bf6f-94455700735c · outbound

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

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness

Reference 78

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local_arxiv, observed 2026-06-29T18:23:50.420197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:c430814a362e0d0b516ba5e6a9f01ed6928e1204898a5b5b2284f24292ec0a32

Observation 074d939f-06d0-4a1e-af2a-f9bbfe7bae00 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.Advances in neural information processing systems, 36:46595–46623, 2023.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Judging llm-as-a-judge with mt-bench and chatbot arena.Advances in neural information processing systems, 36:46595–46623, 2023

Reference 79

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:27d24f825beecf1fb6fbe45ee2fa0200f01366ff81e9d0bdca0e54bd1289a2b3

Observation 8b69a24a-8e10-4c6e-abd5-7d4fd5927f73 · outbound

This paper cites ContPhy: Continuum Physical Concept Learning and Reasoning from Videos.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios ContPhy: Continuum Physical Concept Learning and Reasoning from Videos

Reference 80

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arxiv_id, observed 2026-06-29T18:23:50.378133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:09b0494cf640e83d70f23c7edaf76bf170b8cd148e61a11e6371845883d08d22

Observation cf347445-125c-4eb9-803a-b4dbe4dadd3f · outbound

This paper cites Drivinggen: A comprehensive benchmark for generative video world models in autonomous driving.arXiv preprint arXiv:2601.01528.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Drivinggen: A comprehensive benchmark for generative video world models in autonomous driving.arXiv preprint arXiv:2601.01528

Reference 81

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arxiv_id, observed 2026-06-29T18:23:50.364767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:1ccc00ff59a3018144c3e96799cf21686347fca746ce3a2d8602fd09471bdd64

Observation 5b1f372b-2e01-4a1c-a441-2392f4315b05 · outbound

This paper cites icy surface.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios icy surface

Reference 82

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:4670232d751893747a5d02065c577ba73c72dcf4aacba134554e1587884149b1

Observation 81f7950d-d953-4fb8-b690-3376ce91050a · outbound

This paper cites an unresolved cited work.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Unresolved cited work

Reference 83

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:ab1715114e31d4951a01ce211278a509f631787f3e0a78b8e92a23e9b0eb1f8a

Observation 76dcdd03-15f0-4915-aaea-5b071e1a4a3f · outbound

This paper cites Video B, and (d)causal constraintsdictating which entities may and may not change.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Video B, and (d)causal constraintsdictating which entities may and may not change

Reference 84

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:63e43319a58aaedcf0f589bc8fadd3d5cb4bbc0685eef0c614d82b06c1ff11bd

Observation ed8f2436-848e-4f89-8d21-32970d8d222d · outbound

This paper cites an unresolved cited work.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Unresolved cited work

Reference 85

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:25d5de0dfe99aa651480a6a2d5028595979fd214929cb62686caa0c7a1110f4e

Observation bb17f0ee-b5c6-43b7-9593-0a84eb7015c0 · outbound

This paper cites an unresolved cited work.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios Unresolved cited work

Reference 86

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:1e9aee4ab3ea8b37ef840ebd22d1575135753e622b17323874fe254348e8fd30

Observation 19ab91b7-922a-4d27-a71c-f6e0d97e11ec · outbound

This paper cites A_Adherence_Single.

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios A_Adherence_Single

Reference 87

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source=pdf_text observed=2026-06-29T18:23:22.987086Z digest=sha256:9818cffe380e1f86f4018f41daceaeb18539e88b269361699774ac06d00a3017

Pith citing papers

Observation 1f520f89-7eaa-4ecb-8227-ad1780631dc8 · inbound

Why Does the Future Branch? Identifiable Closure Tests for Stochastic Physical World Models cites this paper.

Why Does the Future Branch? Identifiable Closure Tests for Stochastic Physical World Models What-If World: A Causal Benchmark for General World Models in Embodied Scenarios

Reference 27

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local_arxiv, observed 2026-08-05T00:42:28.649422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-05T00:42:28.416916Z digest=sha256:ec084039b0050fd7b35001d9f6ee5c804bed7a7222230419d40f4ac312a3b94f

Observation 178f7739-2537-4975-b7bf-4b84f80cc2f0 · inbound

Twin Rollouts: Noise-Coupled Counterfactual Branching in Interactive Video World Models cites this paper.

Twin Rollouts: Noise-Coupled Counterfactual Branching in Interactive Video World Models What-If World: A Causal Benchmark for General World Models in Embodied Scenarios

Reference 2

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source=pdf_text observed=2026-08-14T04:23:57.855823Z digest=sha256:a8d7b16bc7caca0c53323db90a24873cfdf78a8aba40f3f3194b1d93830821c9

Observation 94cdc256-45ce-4789-bb49-1612e101b291 · inbound

WorldSimProbe: Diagnosing Simulator Faithfulness in Action-Conditioned World Models for Embodied Manipulation cites this paper.

WorldSimProbe: Diagnosing Simulator Faithfulness in Action-Conditioned World Models for Embodied Manipulation What-If World: A Causal Benchmark for General World Models in Embodied Scenarios

Reference 36

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no resolver link, observed 2026-08-11T19:59:33.585056Z

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source=arxiv_source observed=2026-08-11T19:59:33.585056Z digest=sha256:f18c46091f727dcdb4fe1c10d9ac82af32d7473d32512fb7d2234e4ba59e0b5a