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Paper Citation Record · LEDGER

IP-Prompter: Training-Free Theme-Specific Image Generation via Dynamic Visual Prompting

As of 17 August 2026, this Paper Citation Record lists 4 of 4 outbound references and 1 inbound Pith citation observation for arXiv:2501.15641.

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

pith.paper-citation-record.v1
2501.15641 v2

Coverage vector

measured 4 of 4 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:06:43.273640Z

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:46:25.173889Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T20:46:25.254453Z

Reference resolution

4 of 4 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 359ba780-79cd-454c-969f-3638ca1c1264 · outbound

This paper cites StyleShot: A Snapshot on Any Style.

IP-Prompter: Training-Free Theme-Specific Image Generation via Dynamic Visual Prompting StyleShot: A Snapshot on Any Style

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-10T14:06:43.265769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:06:43.265769Z digest=sha256:10d19a4e7b2824bd4e9e68fc33e24db03abfda27d93c3341111093c61e5ec9bb

Observation c6c0a21c-2802-4e83-bcf9-d33dca3e7196 · outbound

This paper cites Large-Scale Text-to-Image Model with Inpainting is a Zero-Shot Subject-Driven Image Generator.

IP-Prompter: Training-Free Theme-Specific Image Generation via Dynamic Visual Prompting Large-Scale Text-to-Image Model with Inpainting is a Zero-Shot Subject-Driven Image Generator

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-10T14:06:43.269945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:06:43.269945Z digest=sha256:6c46253d343ca51b4b0d521c576303cd66f4324d930417dfdeb6401df44a6cb6

Observation 80108da0-8765-4eb0-b1b7-8c8b86d0e313 · outbound

This paper cites Break-for-Make: Modular Low-Rank Adaptations for Composable Content-Style Customization.

IP-Prompter: Training-Free Theme-Specific Image Generation via Dynamic Visual Prompting Break-for-Make: Modular Low-Rank Adaptations for Composable Content-Style Customization

Reference 2023

Resolution
metadata mismatch
local_arxiv, observed 2026-08-10T14:06:43.308068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T14:06:43.273640Z digest=sha256:f706c53191d9da069265a3dc18c711ef4fa7166b4bf9aa4ed264334189c28747

Observation 2a79938f-e520-4cd9-909d-01e470b457f0 · outbound

This paper cites Animate-A-Story: Storytelling with Retrieval-Augmented Video Generation.

IP-Prompter: Training-Free Theme-Specific Image Generation via Dynamic Visual Prompting Animate-A-Story: Storytelling with Retrieval-Augmented Video Generation

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-10T14:06:43.261508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:06:43.261508Z digest=sha256:3213db8443b2c9890feea946e4d456b00ee65abdb4ac6a84079cff709620cb65

Pith citing papers

Observation 6c76c341-23da-4ae6-8b4a-634a321a2f69 · inbound

FreeLoRA: Enabling Training-Free LoRA Fusion for Autoregressive Multi-Subject Personalization cites this paper.

FreeLoRA: Enabling Training-Free LoRA Fusion for Autoregressive Multi-Subject Personalization IP-Prompter: Training-Free Theme-Specific Image Generation via Dynamic Visual Prompting

Reference 53

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:46:25.259185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T20:46:25.173889Z digest=sha256:f052eeb1f7f1d6226569cf1d7ccbe110574be98488fdbd3955df14d4f0abc386