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Paper Citation Record · LEDGER

Solving New Tasks by Adapting Internet Video Knowledge

As of 19 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 4 inbound Pith citation observations for arXiv:2504.15369.

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

pith.paper-citation-record.v1
2504.15369 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:33:00.971804Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:03:39.351300Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T23:36:22.398589Z

Reference resolution

44 of 44 outbound references displayed

  • verified exact0
  • verified fuzzy13
  • unresolved31
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3315c506-1bb2-4cca-8e00-4e076ea64c05 · outbound

This paper cites write newline.

Solving New Tasks by Adapting Internet Video Knowledge write newline

Reference 1

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no resolver link, observed 2026-08-16T11:33:00.753625Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:33:00.753625Z digest=sha256:5699d67380a5f805abb01040f18f6af1147af1a3219ad84a7dafdaa3c641f4d5

Observation 6fdff65e-773c-45b4-b790-af470334c6c9 · outbound

This paper cites Compositional foundation models for hierarchical planning.

Solving New Tasks by Adapting Internet Video Knowledge Compositional foundation models for hierarchical planning

Reference 2

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raw_fallback, observed 2026-08-16T11:33:01.607701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:33:00.759400Z digest=sha256:5899557c0283436074c493c4cfa11a2c82b4f4e2963a6ce6c302521bdd64b518

Observation 2d6fcbae-7521-4fc2-b74c-6ec93f029538 · outbound

This paper cites Frozen in time: A joint video and image encoder for end-to-end retrieval.

Solving New Tasks by Adapting Internet Video Knowledge Frozen in time: A joint video and image encoder for end-to-end retrieval

Reference 3

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raw_fallback, observed 2026-08-16T11:33:01.594587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:33:00.763492Z digest=sha256:3f790b272fc96b446b1e56b55de0d260b4d676c0c227efc2cd6fd11abb807454

Observation 30a171b4-8dc6-4ea3-a920-989c6f90fa94 · outbound

This paper cites Learning universal policies via text-guided video generation.

Solving New Tasks by Adapting Internet Video Knowledge Learning universal policies via text-guided video generation

Reference 4

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raw_fallback, observed 2026-08-16T11:33:01.579463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:33:00.768615Z digest=sha256:b94dd37428cf05a861706ea7c2de1726a34ccb44ce60b01a42a08cb7dc40b4f4

Observation 7e717fa4-6b4f-4ea2-ab44-6d7aca923067 · outbound

This paper cites Tenenbaum, Leslie Pack Kaelbling, Andy Zeng, and Jonathan Tompson.

Solving New Tasks by Adapting Internet Video Knowledge Tenenbaum, Leslie Pack Kaelbling, Andy Zeng, and Jonathan Tompson

Reference 5

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raw_fallback, observed 2026-08-16T11:33:01.565686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:33:00.773609Z digest=sha256:f373fd9afcc3db5cce8a95407311f733bce8cf74d4508d508815736cf2ce2aee

Observation 52791cb4-2960-4c46-a48e-6ca3d44af7f6 · outbound

This paper cites AI2-THOR: An Interactive 3D Environment for Visual AI.

Solving New Tasks by Adapting Internet Video Knowledge AI2-THOR: An Interactive 3D Environment for Visual AI

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:33:00.779254Z digest=sha256:a0cbda36c0ef06398d77b69970bc60496c943290cd851e3dddbea7ec78e3d68c

Observation 284bee85-ad9e-4a0e-9e68-de352100848f · outbound

This paper cites Video prediction models as rewards for reinforcement learning.

Solving New Tasks by Adapting Internet Video Knowledge Video prediction models as rewards for reinforcement learning

Reference 7

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raw_fallback, observed 2026-08-16T11:33:01.549379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:33:00.783474Z digest=sha256:128e84288f1085df170081d326f999ab78654d0463d6109f2fd6896e554f1a20

Observation 24ad2658-78f1-4378-b7d1-d635a808f660 · outbound

This paper cites Video prediction models as rewards for reinforcement learning.

Solving New Tasks by Adapting Internet Video Knowledge Video prediction models as rewards for reinforcement learning

Reference 8

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raw_fallback, observed 2026-08-16T11:33:01.534066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:33:00.787297Z digest=sha256:182c8fb7f564f17af1d94fc51011e7a18f1d451a7664f67ef998673f8a999dcb

Observation a36cfdc5-af8a-488c-a1a2-5e6d11e09535 · outbound

This paper cites An image is worth one word: Personalizing text-to-image generation using textual inversion.

Solving New Tasks by Adapting Internet Video Knowledge An image is worth one word: Personalizing text-to-image generation using textual inversion

Reference 9

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raw_fallback, observed 2026-08-16T11:33:01.517357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:33:00.792678Z digest=sha256:58172c4f7c8a9b7db5c98ed4d49fade534076767184fb1814827aa528b8a3b37

Observation cc6e9dc7-2d9b-404a-9ab1-553ba5c83bbd · outbound

This paper cites AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning.

Solving New Tasks by Adapting Internet Video Knowledge AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

Reference 10

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source=arxiv_source observed=2026-08-16T11:33:00.797162Z digest=sha256:d1b05253343360d851060112041ca0ff99865724872fc60244e5170cae519bf9

Observation e3fdffe2-a310-42f9-8649-3d6d1e16d6ce · outbound

This paper cites Temporal Difference Learning for Model Predictive Control.

Solving New Tasks by Adapting Internet Video Knowledge Temporal Difference Learning for Model Predictive Control

Reference 11

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source=arxiv_source observed=2026-08-16T11:33:00.802808Z digest=sha256:8d18ba1a3a1acd04f5cb1528d6f638d21cd9c490d3732653c4a938441e1cf0bf

Observation 95952ffe-95e1-4bc3-a635-9bddc6b43b40 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

Solving New Tasks by Adapting Internet Video Knowledge Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 12

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source=arxiv_source observed=2026-08-16T11:33:00.807441Z digest=sha256:3c2b3c90f5bcaa2e235443f3bb954eea3d55639f132dedc5e0e7e13b0321e739

Observation abf2696e-ccce-42f1-8de7-e9265a57e62f · outbound

This paper cites Classifier-Free Diffusion Guidance.

Solving New Tasks by Adapting Internet Video Knowledge Classifier-Free Diffusion Guidance

Reference 13

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:33:00.812937Z digest=sha256:9287055294d5942abebe1a23c367973cb722c4ef2164d7fc251821c5ce28f13a

Observation 112bd6b5-2709-4b0f-9f47-e2e50e132e25 · outbound

This paper cites Denoising diffusion probabilistic models.

Solving New Tasks by Adapting Internet Video Knowledge Denoising diffusion probabilistic models

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-16T11:33:01.494556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:33:00.817411Z digest=sha256:515f3a10e9a2bb2555dbad851a8955eb1270ab45b947a2beb3bd913ce3129825

Observation e9ebd7fc-7c70-417a-80a7-3d71441fd33c · outbound

This paper cites Video diffusion models.

Solving New Tasks by Adapting Internet Video Knowledge Video diffusion models

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:33:00.821875Z digest=sha256:632044bcf9f934d277667d50a8f4be92c3acaa6de1977b1dcd82a77b0a433f53

Observation a95b08a4-e519-4ec7-a18a-6dec4c54d84b · outbound

This paper cites LoRA: low-rank adaptation of large language models.

Solving New Tasks by Adapting Internet Video Knowledge LoRA: low-rank adaptation of large language models

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-16T11:33:01.470379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:33:00.826221Z digest=sha256:ebb4220e5523995ab4474cee9786f00f685a7c4f2543b652061b5c0e608cb3f8

Observation 8d03c7f9-b68b-4431-8a31-c56d7d0f8f1e · outbound

This paper cites Diffusion Reward: Learning Rewards via Conditional Video Diffusion.

Solving New Tasks by Adapting Internet Video Knowledge Diffusion Reward: Learning Rewards via Conditional Video Diffusion

Reference 17

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no resolver link, observed 2026-08-16T11:33:00.830272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:33:00.830272Z digest=sha256:275a4c5d79609296b484726a2800e8dcc632d868b51a04904f5185e45124b593

Observation 230cad55-a8fb-4570-a11d-c5a807641156 · outbound

This paper cites Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators.

Solving New Tasks by Adapting Internet Video Knowledge Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators

Reference 18

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source=arxiv_source observed=2026-08-16T11:33:00.836456Z digest=sha256:3392d5e6b12e6e86733023390cf70fc8adfb226eed06da2e4e05527ef55af90c

Observation ef72ae16-99d9-4d0f-88c9-72d877fa04a7 · outbound

This paper cites Tenenbaum.

Solving New Tasks by Adapting Internet Video Knowledge Tenenbaum

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-16T11:33:01.455941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:33:00.840722Z digest=sha256:2944c8e8c301066f97c0d71537ed1d946e00d8311cb4630e71f50e60e3bb0ddb

Observation 51c8893f-8572-4192-a5b0-6a67f6f4ca40 · outbound

This paper cites Dreamitate: Real-World Visuomotor Policy Learning via Video Generation.

Solving New Tasks by Adapting Internet Video Knowledge Dreamitate: Real-World Visuomotor Policy Learning via Video Generation

Reference 20

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source=arxiv_source observed=2026-08-16T11:33:00.845679Z digest=sha256:c70b68e56ba692f521632d903b0e5eb1eda62777e355f879f32bc88ffbe85ef0

Observation 59248e84-3725-468f-9ba4-52076e746308 · outbound

This paper cites Text-aware diffusion for policy learning.

Solving New Tasks by Adapting Internet Video Knowledge Text-aware diffusion for policy learning

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-16T11:33:01.440442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:33:00.850935Z digest=sha256:013c63a0c9688665feae24b2c931fd3746d31cc514b336af9b795023adb025c7

Observation dddeb86c-e92b-4fa2-ab42-3de5df9721f0 · outbound

This paper cites VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training.

Solving New Tasks by Adapting Internet Video Knowledge VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training

Reference 22

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source=arxiv_source observed=2026-08-16T11:33:00.857214Z digest=sha256:61e251a8cbc9bbe74283cdde120a3ce94c20fca5627091d156f73af6abc40a3b

Observation 12a60017-f1ab-4123-aff9-14bb6dafd246 · outbound

This paper cites Where are we in the search for an artificial visual cortex for embodied intelligence? In Conference on Neural Information Processing Systems (NeurIPS), 2023.

Solving New Tasks by Adapting Internet Video Knowledge Where are we in the search for an artificial visual cortex for embodied intelligence? In Conference on Neural Information Processing Systems (NeurIPS), 2023

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:33:00.863476Z digest=sha256:afb720c1e3d64b4f8a71336f4f9a3decef9bb97887d76a43e3eecdab2336dfef

Observation 3617c4f9-e53b-4f1b-8d81-6e8abeb788ad · outbound

This paper cites Towards Generalist Robot Learning from Internet Video: A Survey.

Solving New Tasks by Adapting Internet Video Knowledge Towards Generalist Robot Learning from Internet Video: A Survey

Reference 24

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:33:00.868257Z digest=sha256:ef6c11f72339e650bb4ba8c51abc3b674f6c4b13d108bdefab5d3e08d6dab202

Observation ac2f9a6d-9140-446c-b2c1-8b960e672306 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Solving New Tasks by Adapting Internet Video Knowledge Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 25

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source=arxiv_source observed=2026-08-16T11:33:00.873944Z digest=sha256:2702b9c024ede965f9a5b3a901f43b004f120cbed560dd5b59a4eef185c5239d

Observation afa58192-e473-44eb-a104-cc2605f37884 · outbound

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

Solving New Tasks by Adapting Internet Video Knowledge High-resolution image synthesis with latent diffusion models

Reference 26

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no resolver link, observed 2026-08-16T11:33:00.879093Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:33:00.879093Z digest=sha256:435378506e03f1d0960e9e64af96990aa9ed10a32712a584f5d7db614b7a46a5

Observation a63a197e-769c-47dc-a787-4bf1fd411d11 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation.

Solving New Tasks by Adapting Internet Video Knowledge Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 27

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source=arxiv_source observed=2026-08-16T11:33:00.883727Z digest=sha256:a00364c4549713afa331382a694a56e4cdb251024742632ec89d31d3ae5b598d

Observation 4edc3f50-b190-4fb1-9c1d-f4e543d9576b · outbound

This paper cites Unsupervised Perceptual Rewards for Imitation Learning.

Solving New Tasks by Adapting Internet Video Knowledge Unsupervised Perceptual Rewards for Imitation Learning

Reference 28

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source=arxiv_source observed=2026-08-16T11:33:00.887676Z digest=sha256:cba0d5618aedc34aac627e765beda6e0d2948c5dc8acf2bef79b38f7fce2d8ef

Observation 996a5f49-0ce6-4611-81f6-08dab81f48e1 · outbound

This paper cites Make-A-Video: Text-to-Video Generation without Text-Video Data.

Solving New Tasks by Adapting Internet Video Knowledge Make-A-Video: Text-to-Video Generation without Text-Video Data

Reference 29

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:33:00.892069Z digest=sha256:0da178d6e47147c540e04b0c18f7942ea6d178b0cd7a09f649ecad34c36c55e7

Observation 262e6d34-98eb-4122-83ae-00643579c824 · outbound

This paper cites Denoising diffusion implicit models.

Solving New Tasks by Adapting Internet Video Knowledge Denoising diffusion implicit models

Reference 30

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:33:00.897290Z digest=sha256:42759da18586af11282cafcf31a983b04efcd27a5d2d00e78b3ceafde960b24f

Observation 676a07e8-6f2f-4f10-a3f3-d893aae50b66 · outbound

This paper cites DeepMind Control Suite.

Solving New Tasks by Adapting Internet Video Knowledge DeepMind Control Suite

Reference 31

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source=arxiv_source observed=2026-08-16T11:33:00.901351Z digest=sha256:7e13912c317b3e816557e947c0ebc3568f54ac21d63afa991b774909d18f0748

Observation 28f1ed69-6a63-4185-9e1b-a02272a7ab14 · outbound

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

Solving New Tasks by Adapting Internet Video Knowledge Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 32

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source=arxiv_source observed=2026-08-16T11:33:00.905970Z digest=sha256:aad170adbe910a0cd969cdb7eb7b2c64edc2f32ee02ac37001522267ec80f971

Observation c6c288cf-4ae1-4dff-8eb2-b9c2c486d902 · outbound

This paper cites Phenaki: Variable Length Video Generation From Open Domain Textual Description.

Solving New Tasks by Adapting Internet Video Knowledge Phenaki: Variable Length Video Generation From Open Domain Textual Description

Reference 33

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:33:00.910696Z digest=sha256:295c4315d7ca130d64037f7ab489b297666a56d59ba17f2b50502d57caee424d

Observation cf7a7e42-7241-4c09-ae1c-152ef4b3a6c1 · outbound

This paper cites This&That: Language-Gesture Controlled Video Generation for Robot Planning.

Solving New Tasks by Adapting Internet Video Knowledge This&That: Language-Gesture Controlled Video Generation for Robot Planning

Reference 34

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no resolver link, observed 2026-08-16T11:33:00.915658Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:33:00.915658Z digest=sha256:c65777ca69d57315eb3f7a7b13116fa328826a6a4e7c492c2602196eb4486411

Observation c15169f9-13d2-4de9-ae36-bd1577798ce1 · outbound

This paper cites AnimateLCM: Computation-Efficient Personalized Style Video Generation without Personalized Video Data.

Solving New Tasks by Adapting Internet Video Knowledge AnimateLCM: Computation-Efficient Personalized Style Video Generation without Personalized Video Data

Reference 35

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source=arxiv_source observed=2026-08-16T11:33:00.920948Z digest=sha256:e87d03e878ec518227ba3131084a5a87ac6dd50ec32828a41f0657472488293a

Observation c042fa16-75a4-488a-a82c-c0fb72ea8c53 · outbound

This paper cites Dreamvideo: Composing your dream videos with customized subject and motion.

Solving New Tasks by Adapting Internet Video Knowledge Dreamvideo: Composing your dream videos with customized subject and motion

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-16T11:33:01.384900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:33:00.927060Z digest=sha256:28498266e32f290e9ca9fcdedd57d77d16ec8753b35172dc3d54b44c80f42a2e

Observation 0759a97c-f5b9-487f-9774-718e8a7061f4 · outbound

This paper cites Any-point Trajectory Modeling for Policy Learning.

Solving New Tasks by Adapting Internet Video Knowledge Any-point Trajectory Modeling for Policy Learning

Reference 37

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source=arxiv_source observed=2026-08-16T11:33:00.933889Z digest=sha256:b436e5a657313bd3b3879d510def7a41dfb0331f4c1d216637a1610eb275bf4e

Observation 9e50c0d5-6362-42f1-9834-1a10bb1fe5e5 · outbound

This paper cites DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors.

Solving New Tasks by Adapting Internet Video Knowledge DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors

Reference 38

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source=arxiv_source observed=2026-08-16T11:33:00.940194Z digest=sha256:4bd69cfb8259dc502cdfe3a1afcd0933f8e1537dbc5e51952ed4b1fbcbf1f267

Observation c0bd381e-9c98-4f61-8408-eb65ae4566c4 · outbound

This paper cites Probabilistic Adaptation of Text-to-Video Models.

Solving New Tasks by Adapting Internet Video Knowledge Probabilistic Adaptation of Text-to-Video Models

Reference 39

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source=arxiv_source observed=2026-08-16T11:33:00.946510Z digest=sha256:31350eb10dace923b0c2e550c378fac25a28fe766e0f9f6b45d48a74d1b73718

Observation e443fcea-f44c-4f53-9538-9d888042d62f · outbound

This paper cites Learning Interactive Real-World Simulators.

Solving New Tasks by Adapting Internet Video Knowledge Learning Interactive Real-World Simulators

Reference 40

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source=arxiv_source observed=2026-08-16T11:33:00.952100Z digest=sha256:b80db8a67e802fd4078e1f8ce4f32115faae9dbd162adf739114a901d286e8af

Observation cb130f2f-0356-44c7-9d0f-3ae20fa53072 · outbound

This paper cites Video as the New Language for Real-World Decision Making.

Solving New Tasks by Adapting Internet Video Knowledge Video as the New Language for Real-World Decision Making

Reference 41

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no resolver link, observed 2026-08-16T11:33:00.956992Z

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source=arxiv_source observed=2026-08-16T11:33:00.956992Z digest=sha256:c80314158c9ce4e19a374f525d9f0766e0fd32735358de018c4b840611fbfa03

Observation ff9ba1c5-5fa5-4bcc-b39a-681aff068c72 · outbound

This paper cites Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning.

Solving New Tasks by Adapting Internet Video Knowledge Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning

Reference 42

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source=arxiv_source observed=2026-08-16T11:33:00.961338Z digest=sha256:32f6adc9f555b10c1876cd4ba045617dcaecb314c2e35e1d54ff27270ceb8ad0

Observation 3c8167e6-8e1f-47d1-a756-b3e7f8d8bb19 · outbound

This paper cites MineDreamer: Learning to Follow Instructions via Chain-of-Imagination for Simulated-World Control.

Solving New Tasks by Adapting Internet Video Knowledge MineDreamer: Learning to Follow Instructions via Chain-of-Imagination for Simulated-World Control

Reference 43

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source=arxiv_source observed=2026-08-16T11:33:00.966215Z digest=sha256:d68cf52a45b495d114530601eb962a751aace2f64d3486539e5801056159a8a1

Observation ca6fc24f-46a7-47f6-9b80-1cd269d24aca · outbound

This paper cites RoboDreamer: Learning Compositional World Models for Robot Imagination.

Solving New Tasks by Adapting Internet Video Knowledge RoboDreamer: Learning Compositional World Models for Robot Imagination

Reference 44

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source=arxiv_source observed=2026-08-16T11:33:00.971804Z digest=sha256:3c4b1683921204602ea9bfe1e4268a8cb3f7a955a5065b576b1d33761a87d9dc

Pith citing papers

Observation f51cdcfd-4231-4f1c-a9df-49631214729d · inbound

$I^2G$: Generating Instructional Illustrations via Text-Conditioned Diffusion cites this paper.

$I^2G$: Generating Instructional Illustrations via Text-Conditioned Diffusion Solving New Tasks by Adapting Internet Video Knowledge

Reference 31

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no resolver link, observed 2026-08-07T15:03:39.351300Z

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source=arxiv_source observed=2026-08-07T15:03:39.351300Z digest=sha256:73e0cfafff4af00ef07f40b21f93f6ae25f4b2512af8f7b8d4921c071577910f

Observation a35f9480-b2f8-4a97-9f63-d0f3ec6f6b20 · inbound

Large Video Planner Enables Generalizable Robot Control cites this paper.

Large Video Planner Enables Generalizable Robot Control Solving New Tasks by Adapting Internet Video Knowledge

Reference 56

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verified exact
arxiv_id, observed 2026-05-16T21:28:34.005109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-16T21:26:32.048309Z digest=sha256:f3639f7801a33802c55386c00fa052352961d36e81b552b84c43b3c1d4d88c2a

Observation 6d5e8f1d-9076-41cc-877d-80e8f8271a3f · inbound

WALL-WM: Carving World Action Modeling at the Event Joints cites this paper.

WALL-WM: Carving World Action Modeling at the Event Joints Solving New Tasks by Adapting Internet Video Knowledge

Reference 51

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verified exact
arxiv_id, observed 2026-07-01T23:36:22.400470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-28T14:15:14.454649Z digest=sha256:8f828d5c6e6a28d784a7881b708b924ff7aadde569cda513ef2af30af7bb4965

Observation e3b50482-1bef-4a71-803d-a2c08d5259fc · inbound

Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling cites this paper.

Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling Solving New Tasks by Adapting Internet Video Knowledge

Reference 40

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source=arxiv_source observed=2026-07-11T19:24:48.899301Z digest=sha256:0a8c7f8cd929cdc6114b21184ac8c7e37e8acaf8562c8695e09e4a0cd0418fd6