Pith. sign in

Paper Citation Record · LEDGER

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

As of 9 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 2026-08-09T06:31:02.800959+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=sha256:7b679826249e497f69b708083409d0bbf2cbc39aceaf2548d072ab002739a142

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=sha256:44c9c335d568f3fd9ac3f425982a17e2196426c40d956e1d8098eb62d48ba5c6

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:e5efede2a223fea0792ef64084fa478306f393add874358e6a86152277d7ca29

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T12:16:28.660008Z digest=sha256:7c9d5a9a09400aac2ba1a534e99750d7250e5f46a674f13090e1f51fc8e9b994

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T12:16:28.663332Z digest=sha256:5158f2d220aaf620e9e906d509ce74681d24bda1d2983cd46716746ac70c1471

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T12:16:28.673620Z digest=sha256:f974712487361d8e02a1e6378f0eabd6795fd111626d5a8e0606170faaaaa95f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T12:16:28.680624Z digest=sha256:67126c3a85819d527370bbd59b4eaec669daea9c70bd263ea3e69def5055c416

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T12:16:28.684771Z digest=sha256:df6616795e3a6981cb5d4e6fbd768378a5d8eb7ad8bb8f87d792ad14790584c4

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T12:16:28.669415Z digest=sha256:e0aa63b2b3906e69e9aeb71450422d580892b0d25024cbadc9dc967635204aee

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T12:16:28.666587Z digest=sha256:f60c08f5459582668539b7ecca28113c323c67290d7312655032ff3946633eb0

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T12:16:28.677218Z digest=sha256:af6548291f3d8c06000d07ecb84cee53294eeeea771fa8298451927af019fa73

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:b77eeb52b3be544ed85f5ab9b7658fd19a7a4d05338bcda2828e6bea132e8d46

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T12:16:28.653218Z digest=sha256:348c20654d2df8701e9ffbd2d6b0f95ba7cbcf64d85d312e2185ced2630f31c3

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T12:16:28.633179Z digest=sha256:b4e5200665f8d32b81ee2d46b06b20077aac83b15392f9f2e51fc25191e39728

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:aaf5e5239a6e963d7d081a93aec5137e140be1647775d8955bf76b6911733b80

Pith citing papers

No inbound Pith citation observations are available.