Paper Citation Record · LEDGER

Erasing Concepts from Diffusion Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2303.07345.

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

pith.paper-citation-record.v1
2303.07345 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:54:09.862951Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation ae406cd4-4100-405d-b7d7-614d873cec4d · inbound

DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory cites this paper.

DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory Erasing Concepts from Diffusion Models

Reference 246

Resolution: verified exact; arxiv_id, observed 2026-05-20T13:03:58.001330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 690cd40b-ba41-4801-8dd5-59c2c1bde898 · inbound

Learning Interactive Real-World Simulators cites this paper.

Learning Interactive Real-World Simulators Erasing Concepts from Diffusion Models

Reference 189

Resolution: verified exact; arxiv_id, observed 2026-05-16T02:15:18.683997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 913c9d04-4d30-4dce-849e-8529a399ef8c · inbound

SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation cites this paper.

SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation Erasing Concepts from Diffusion Models

Reference 229

Resolution: verified exact; arxiv_id, observed 2026-05-16T17:56:23.609790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d934e0f1-807b-4426-8075-e7682d8ad701 · inbound

TRACE: Trajectory-Constrained Concept Erasure in Diffusion Models cites this paper.

TRACE: Trajectory-Constrained Concept Erasure in Diffusion Models Erasing Concepts from Diffusion Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T12:54:09.862951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ce42170-8e93-4e40-a14b-daaa5cc4e906 · inbound

Invisible Watermarks, Visible Gains: Steering Machine Unlearning with Bi-Level Watermarking Design cites this paper.

Invisible Watermarks, Visible Gains: Steering Machine Unlearning with Bi-Level Watermarking Design Erasing Concepts from Diffusion Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T21:01:26.767048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13a4d278-e26b-4f1d-9e45-b96e0abc9abd · inbound

Few to Big: Prototype Expansion Network via Diffusion Learner for Point Cloud Few-shot Semantic Segmentation cites this paper.

Few to Big: Prototype Expansion Network via Diffusion Learner for Point Cloud Few-shot Semantic Segmentation Erasing Concepts from Diffusion Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T16:32:50.087392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6dadbab-1655-425a-9682-870bdeaa3002 · inbound

GUDA: Counterfactual Group-wise Training Data Attribution for Diffusion Models via Unlearning cites this paper.

GUDA: Counterfactual Group-wise Training Data Attribution for Diffusion Models via Unlearning Erasing Concepts from Diffusion Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T06:35:42.548378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation daf322b4-a067-4708-8b7c-d161fe35caf2 · inbound

FlowGuard: Towards Lightweight In-Generation Safety Detection for Diffusion Models via Linear Latent Decoding cites this paper.

FlowGuard: Towards Lightweight In-Generation Safety Detection for Diffusion Models via Linear Latent Decoding Erasing Concepts from Diffusion Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:41:00.450845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fc2192dd-72d7-4d95-bba2-6aaa3897a99d · inbound

The Illusion of High Utility in Safety Alignment of Text-to-Image Diffusion Models cites this paper.

The Illusion of High Utility in Safety Alignment of Text-to-Image Diffusion Models Erasing Concepts from Diffusion Models

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T14:57:03.740056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5015973b-38bf-4754-8f64-79fd1404d2a5 · inbound

One Modality to Forget Them All: Enhancing Cross-Modal Unlearning in Vision-Language Models cites this paper.

One Modality to Forget Them All: Enhancing Cross-Modal Unlearning in Vision-Language Models Erasing Concepts from Diffusion Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-01T21:01:04.687180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.