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Paper Citation Record · LEDGER

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning

As of 19 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2502.07600.

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

pith.paper-citation-record.v1
2502.07600 v2

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:16:28.684771Z

measured 15 of 15 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 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

15 of 15 outbound references displayed

  • verified exact2
  • verified fuzzy5
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7b44e9c7-4e26-46b0-b1fa-80597824ccb5 · outbound

This paper cites On the Binding Problem in Artificial Neural Networks.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning On the Binding Problem in Artificial Neural Networks

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-08T12:16:28.641413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:16:28.641413Z digest=sha256:3cea807a24d56a18e8967f80f64200d5557e887e158b416abba8b42e4df460b2

Observation 984186ed-4b82-48f4-b188-674a96d8a253 · outbound

This paper cites Object-Centric World Model for Language-Guided Manipulation.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning Object-Centric World Model for Language-Guided Manipulation

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-08T12:16:28.649242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:16:28.649242Z digest=sha256:7f3471f4607985a5ec3f70889c259a63a9c4782d3d39c17ec9e85dfba380ed82

Observation 656512f2-2fc5-4198-aac2-35d0f7a95c06 · outbound

This paper cites Illiterate DALL-E Learns to Compose.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning Illiterate DALL-E Learns to Compose

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-08T12:16:28.656515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:16:28.656515Z digest=sha256:d1d4efea4a2e7f1cef15737102f6f01a16ffe77fa2d518c973951beac6fced23

Observation 70b2e5c4-c54f-431f-8136-521161624b51 · outbound

This paper cites Object- centric image to video generation with language guid- ance.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning Object- centric image to video generation with language guid- ance

Reference 8

Resolution
verified exact
raw_fallback, observed 2026-08-08T12:16:28.807670Z

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=2026-08-08T12:16:28.660008Z digest=sha256:512df294f1faf7ac8b0aac020decda2c66d11e51e9a2edafe233f7443ec002b9

Observation 4a91b847-d8c6-4ca2-b218-8b55656cb775 · outbound

This paper cites an unresolved cited work.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-08T12:16:28.958725Z

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=2026-08-08T12:16:28.663332Z digest=sha256:62318dd05917e541d574120164a5e902a107c1283772d47f0092eb5e6c50ac8b

Observation ad78d104-536a-4b40-b41a-392e5a61bba7 · outbound

This paper cites The projected object slots are then conditioned by adding them with the projected action prototype and variability embedding from the corresponding time step.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning The projected object slots are then conditioned by adding them with the projected action prototype and variability embedding from the corresponding time step

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T12:16:28.923241Z

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=2026-08-08T12:16:28.673620Z digest=sha256:55067d8678a1ff80d9c335e9dfdce8238403656f786bb8cbe48f6a15c978e6be

Observation baa0748c-10bf-4a9a-a0e1-ad411c49ed95 · outbound

This paper cites CADDY infers latent actions that encode the agent’s actions between consecutive pairs of frames.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning CADDY infers latent actions that encode the agent’s actions between consecutive pairs of frames

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T12:16:28.899689Z

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=2026-08-08T12:16:28.680624Z digest=sha256:283959e2e0a5165b035a85e62ce0c2d9ba47eba1347e22a7fbe41006de983ee7

Observation 9d62bee2-d508-4f0a-9088-123b7f14f78e · outbound

This paper cites In contrast to the object-centric representations employed by PlaySlot, LAPO relies on feature maps output by a convolutional encoder.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning In contrast to the object-centric representations employed by PlaySlot, LAPO relies on feature maps output by a convolutional encoder

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T12:16:28.887168Z

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=2026-08-08T12:16:28.684771Z digest=sha256:708bcd37546eb925b625bce76e1eb6752e72bdf498ba46c7e0dbc9b8572ff7d1

Observation e7da0824-59ce-461d-b4e4-8bc513a30a91 · outbound

This paper cites an unresolved cited work.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning Unresolved cited work

Reference 1024

Resolution
unresolved
raw_fallback, observed 2026-08-08T12:16:28.934007Z

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=2026-08-08T12:16:28.669415Z digest=sha256:6dd1a9918e76121da554adab874ada17487d30dc5dd1c823f0c4ffad02ddbe01

Observation d603d2b6-a823-4d89-b427-ab58c66474ef · outbound

This paper cites an unresolved cited work.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning Unresolved cited work

Reference 2017

Resolution
unresolved
raw_fallback, observed 2026-08-08T12:16:28.947336Z

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=2026-08-08T12:16:28.666587Z digest=sha256:c8178cf030fdb14f54c49fc2b6c3a10653d9f2f70fdf6c114a8e845284f77633

Observation 742c2e18-3d08-4497-bfd6-817ffea8ffd5 · outbound

This paper cites To ensure a fair comparison, we balance the number of learnable parameters and compute requirements for all methods.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning To ensure a fair comparison, we balance the number of learnable parameters and compute requirements for all methods

Reference 2018

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T12:16:28.912014Z

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=2026-08-08T12:16:28.677218Z digest=sha256:229b6ac5e7df9d6178e58c839e9bc95fdd30d4ce4c85bd4b8cb838aa9715b41a

Observation dc964014-a2ed-4d95-a77d-143be5e09eef · outbound

This paper cites Mastering Diverse Domains through World Models.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning Mastering Diverse Domains through World Models

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-08T12:16:28.645327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:16:28.645327Z digest=sha256:1ab274e265f0d9d67373193180e871fc16e0abbeaa12d790b3672493aac4934d

Observation f5a1d540-7453-4665-9db3-8d9c7fa8d85c · outbound

This paper cites Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases

Reference 2022

Resolution
verified exact
local_arxiv, observed 2026-08-08T12:16:28.833509Z

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=2026-08-08T12:16:28.653218Z digest=sha256:17437b5fdbcf0432c3d4ca8520f87bbdfad2a05f7d9b52b8c7dbdf2ae6c042df

Observation cb183922-46a5-4f39-aa20-cdb3260bba8b · outbound

This paper cites Object discovery from motion-guided to- kens.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning Object discovery from motion-guided to- kens

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T12:16:28.969199Z

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=2026-08-08T12:16:28.633179Z digest=sha256:92ac86484dc64d9bb1fa130a7caa47ba03c570621dce4a4ea07d2675eee238f5

Observation 03d8ee3a-3cb0-499b-bea0-906cc4c27912 · outbound

This paper cites MONet: Unsupervised Scene Decomposition and Representation.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning MONet: Unsupervised Scene Decomposition and Representation

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-08T12:16:28.637393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:16:28.637393Z digest=sha256:514fb13fe2f4ea5cabae723868b7837e7405bd64cd5e7802000524159d863c29

Pith citing papers

No inbound Pith citation observations are available.