Paper Citation Record · LEDGER

Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2504.14666.

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

pith.paper-citation-record.v1
2504.14666 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 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:02:15.374933Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T05:12:44.728311Z

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 309487b3-e06c-48ea-abca-18d367c5cd16 · inbound

KRIS-Bench: Benchmarking Next-Level Intelligent Image Editing Models cites this paper.

KRIS-Bench: Benchmarking Next-Level Intelligent Image Editing Models Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T15:02:15.374933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73ba1ad5-474b-4b33-91bd-c6f6d0e70bbd · inbound

FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities cites this paper.

FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-07T14:05:02.393418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 855a524b-5a6f-4049-9406-2c283f74792c · inbound

D-AR: Diffusion via Autoregressive Models cites this paper.

D-AR: Diffusion via Autoregressive Models Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T12:46:48.181078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba6c5649-32ce-4b33-8167-eb10939e377a · 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 Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T10:23:12.548885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ae4e593-e82f-407f-bafa-0a8250e4ea4f · inbound

What Limits Virtual Agent Application? OmniBench: A Scalable Multi-Dimensional Benchmark for Essential Virtual Agent Capabilities cites this paper.

What Limits Virtual Agent Application? OmniBench: A Scalable Multi-Dimensional Benchmark for Essential Virtual Agent Capabilities Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T05:02:29.249982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10121022-a5c4-4f85-b43f-81150524e195 · inbound

Towards Meta-Cognitive Knowledge Editing for Multimodal LLMs cites this paper.

Towards Meta-Cognitive Knowledge Editing for Multimodal LLMs Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:12:44.734629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.