Paper Citation Record · LEDGER

Reasoning Physical Video Generation with Diffusion Timestep Tokens via Reinforcement Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2504.15932.

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

pith.paper-citation-record.v1
2504.15932 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:23:12.530267Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:20:05.869783Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b0172b25-e168-43c2-a262-98253bd749ec · inbound

FocusDiff: Advancing Fine-Grained Text-Image Alignment for Autoregressive Visual Generation through RL cites this paper.

FocusDiff: Advancing Fine-Grained Text-Image Alignment for Autoregressive Visual Generation through RL Reasoning Physical Video Generation with Diffusion Timestep Tokens via Reinforcement Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T10:23:12.530267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2eed39a-bfcb-4826-95f0-8d4f609e6074 · inbound

Enhancing Physical Plausibility in Video Generation by Reasoning the Implausibility cites this paper.

Enhancing Physical Plausibility in Video Generation by Reasoning the Implausibility Reasoning Physical Video Generation with Diffusion Timestep Tokens via Reinforcement Learning

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-18T12:56:24.323090Z

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.

Observation 9aafc059-0a6c-4170-b957-83c1ae242674 · inbound

PhySe-RPO: Physics and Semantics Guided Relative Policy Optimization for Diffusion-Based Surgical Smoke Removal cites this paper.

PhySe-RPO: Physics and Semantics Guided Relative Policy Optimization for Diffusion-Based Surgical Smoke Removal Reasoning Physical Video Generation with Diffusion Timestep Tokens via Reinforcement Learning

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-15T01:23:26.847561Z

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.

Observation af5d0a1e-a5c8-4d99-b1a6-b342b7faaf8b · inbound

Incantation: Natural Language as the Action Interface for Multi-Entity Video World Models cites this paper.

Incantation: Natural Language as the Action Interface for Multi-Entity Video World Models Reasoning Physical Video Generation with Diffusion Timestep Tokens via Reinforcement Learning

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-20T10:58:13.632288Z

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.

Observation 036c5be8-c10d-4eff-b649-c3eb5c2545cd · inbound

Incantation: Natural Language as the Action Interface for Multi-Entity Video World Models cites this paper.

Incantation: Natural Language as the Action Interface for Multi-Entity Video World Models Reasoning Physical Video Generation with Diffusion Timestep Tokens via Reinforcement Learning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-14T18:52:51.601629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41d131f3-d2a3-4f71-b360-6958ece7b68f · inbound

Physics Question Scene Graph: Fine-grained Evaluation of Physical Plausibility in Text-to-Video Generation cites this paper.

Physics Question Scene Graph: Fine-grained Evaluation of Physical Plausibility in Text-to-Video Generation Reasoning Physical Video Generation with Diffusion Timestep Tokens via Reinforcement Learning

Reference 29

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T19:20:05.872870Z

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.