Paper Citation Record · LEDGER

BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2307.10816.

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

pith.paper-citation-record.v1
2307.10816 v4

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 2026-08-20T06:33:59.587034+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:03:28.583234Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T21:48:57.854470Z

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 5a1387d4-dfc1-454c-b7a9-08eb179b69c8 · inbound

AnySynth: Harnessing the Power of Image Synthetic Data Generation for Generalized Vision-Language Tasks cites this paper.

AnySynth: Harnessing the Power of Image Synthetic Data Generation for Generalized Vision-Language Tasks BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T14:03:28.583234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17bfffb3-1719-4bdd-9515-fc307216109c · inbound

Imagine and Seek: Improving Composed Image Retrieval with an Imagined Proxy cites this paper.

Imagine and Seek: Improving Composed Image Retrieval with an Imagined Proxy BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-12T14:02:55.893044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e64c3edc-81c2-4a5d-999f-caa0beaaa2d4 · inbound

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model cites this paper.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-11T18:16:00.724016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5171a032-42ed-4bc0-9dbf-f7446b19b934 · inbound

SmartSpatial: Enhancing the 3D Spatial Arrangement Capabilities of Stable Diffusion Models and Introducing a Novel 3D Spatial Evaluation Framework cites this paper.

SmartSpatial: Enhancing the 3D Spatial Arrangement Capabilities of Stable Diffusion Models and Introducing a Novel 3D Spatial Evaluation Framework BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T22:48:04.420013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d63d2f5-54b2-4226-bed7-c60f7208a5cd · inbound

Why Settle for Mid: A Probabilistic Viewpoint to Spatial Relationship Alignment in Text-to-image Models cites this paper.

Why Settle for Mid: A Probabilistic Viewpoint to Spatial Relationship Alignment in Text-to-image Models BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion

Reference 73

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:48:57.931564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c59816ba-a2f3-492c-9554-ad302c81b323 · inbound

TILT: Improving Compositional Generation in Diffusion Models with a Model-Intrinsic Reward cites this paper.

TILT: Improving Compositional Generation in Diffusion Models with a Model-Intrinsic Reward BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-02T13:55:32.710981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.