Paper Citation Record · LEDGER

Diffuse, Attend, and Segment: Unsupervised Zero-Shot Segmentation using Stable Diffusion

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2308.12469.

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

pith.paper-citation-record.v1
2308.12469 v3

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 2026-08-07T14:42:43.673904Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:29:30.107818Z

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 015164fc-2247-44b1-b426-123853792d9e · inbound

Segment Anyword: Mask Prompt Inversion for Open-Set Grounded Segmentation cites this paper.

Segment Anyword: Mask Prompt Inversion for Open-Set Grounded Segmentation Diffuse, Attend, and Segment: Unsupervised Zero-Shot Segmentation using Stable Diffusion

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T14:42:43.673904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8016f4b6-768a-4783-8bf1-ef9b35c6f405 · inbound

Diffusion Counterfactual Generation with Semantic Abduction cites this paper.

Diffusion Counterfactual Generation with Semantic Abduction Diffuse, Attend, and Segment: Unsupervised Zero-Shot Segmentation using Stable Diffusion

Reference 121

Resolution: unresolved; no resolver link, observed 2026-08-07T05:30:33.151687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44523044-c91c-4f82-b234-3f09335abca7 · inbound

Harnessing Text-to-Image Diffusion Models for Point Cloud Self-Supervised Learning cites this paper.

Harnessing Text-to-Image Diffusion Models for Point Cloud Self-Supervised Learning Diffuse, Attend, and Segment: Unsupervised Zero-Shot Segmentation using Stable Diffusion

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T18:10:15.259656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5ac9e28-2269-4448-ba96-b0d9c96edf05 · inbound

UniVidX: A Unified Multimodal Framework for Versatile Video Generation via Diffusion Priors cites this paper.

UniVidX: A Unified Multimodal Framework for Versatile Video Generation via Diffusion Priors Diffuse, Attend, and Segment: Unsupervised Zero-Shot Segmentation using Stable Diffusion

Reference 99

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:26:08.003736Z

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.

Observation 2fbc3aa5-60a4-44c4-9c8c-97bc80df8f23 · inbound

Functionalization via Structure Completion and Motion Rectification cites this paper.

Functionalization via Structure Completion and Motion Rectification Diffuse, Attend, and Segment: Unsupervised Zero-Shot Segmentation using Stable Diffusion

Reference 207

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:28:16.875540Z

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.

Observation 6abfa110-90b5-4591-ae06-76876c58523f · inbound

StreamKL: Fast and Memory-Efficient KL Divergence for Boosting Attention Distillation cites this paper.

StreamKL: Fast and Memory-Efficient KL Divergence for Boosting Attention Distillation Diffuse, Attend, and Segment: Unsupervised Zero-Shot Segmentation using Stable Diffusion

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:29:30.110222Z

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.