Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Magnet: We Never Know How Text-to-Image Diffusion Models Work, Until We Learn How Vision-Language Models Function
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.19967.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T17:18:42.960273Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T05:15:54.318059Z
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 a656a0b0-e6e6-4f57-abce-c1c705dc8443 · inbound
DECOR:Decomposition and Projection of Text Embeddings for Text-to-Image Customization cites this paper.
DECOR:Decomposition and Projection of Text Embeddings for Text-to-Image Customization Magnet: We Never Know How Text-to-Image Diffusion Models Work, Until We Learn How Vision-Language Models Function
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T17:18:42.960273Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fcc4e5d7-f047-4403-85fa-5ea420373245 · inbound
RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling cites this paper.
RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling Magnet: We Never Know How Text-to-Image Diffusion Models Work, Until We Learn How Vision-Language Models Function
Reference 52
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T05:15:54.320879Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.