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Paper Citation Record · LEDGER

MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2406.07209.

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

pith.paper-citation-record.v1
2406.07209 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 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 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:46:25.145387Z

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

0
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 f2f202ca-55c7-436d-ad5d-3d1d62dda530 · inbound

T2I-FactualBench: Benchmarking the Factuality of Text-to-Image Models with Knowledge-Intensive Concepts cites this paper.

T2I-FactualBench: Benchmarking the Factuality of Text-to-Image Models with Knowledge-Intensive Concepts MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 52

Resolution
metadata mismatch
arxiv_id, observed 2026-05-23T08:02:43.066441Z

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.

source=arxiv_source observed=2026-05-23T08:00:12.781392Z digest=sha256:de7a84877236f1b4413e178cc736300b480c11d2a8c061444a752f4e37c1e55c

Observation a2edb817-dc78-4de9-b11b-ba4f2366217b · inbound

FreeGraftor: Training-Free Cross-Image Feature Grafting for Subject-Driven Text-to-Image Generation cites this paper.

FreeGraftor: Training-Free Cross-Image Feature Grafting for Subject-Driven Text-to-Image Generation MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 24

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T18:11:54.549732Z

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.

source=pdf_text observed=2026-05-22T18:09:50.633826Z digest=sha256:5fb4513bfd6746cc0315084053a1e267f2be6a8d370816cc086c0dba198d30b8

Observation 471aa53f-5e5b-4900-9b34-b71aad0147e2 · inbound

Learning Zero-Shot Subject-Driven Video Generation Using 1% Compute cites this paper.

Learning Zero-Shot Subject-Driven Video Generation Using 1% Compute MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 48

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T17:51:54.324109Z

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.

source=pdf_text observed=2026-05-22T17:51:41.947939Z digest=sha256:3c33d2b2bd7a1d1d8a3b219003af28c029411a645a3c107ba60840e48894776c

Observation 01d4ffab-c112-4897-a612-a5bcaabc56c8 · 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 MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T20:46:25.145387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:46:25.145387Z digest=sha256:b991e586a14f3d843be3f9b1f764c7cf16c1fd037cb395d21479f0a58c758575

Observation 961c9dc6-24ff-43a8-8f69-930a481a52df · inbound

FreeCus: Free Lunch Subject-driven Customization in Diffusion Transformers cites this paper.

FreeCus: Free Lunch Subject-driven Customization in Diffusion Transformers MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T15:42:23.898097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:42:23.898097Z digest=sha256:52ba0e038bc2e561ccc0bbd4766dbe0605b559e036f382b2b4b886da4bcd0336

Observation 8ae67de0-cdcb-48a3-91c3-d219d47017c6 · inbound

FBI: Learning Dexterous In-hand Manipulation with Dynamic Visuotactile Shortcut Policy cites this paper.

FBI: Learning Dexterous In-hand Manipulation with Dynamic Visuotactile Shortcut Policy MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-05T18:37:22.326432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:37:22.326432Z digest=sha256:057fcdb7740839ce974d54e16b8faef490646d4d258ecdf9dd7b5053469c3fa1

Observation 1e93c7eb-55eb-448e-8970-9f027a610277 · inbound

OmniCache: A Trajectory-Oriented Global Perspective on Training-Free Cache Reuse for Diffusion Transformer Models cites this paper.

OmniCache: A Trajectory-Oriented Global Perspective on Training-Free Cache Reuse for Diffusion Transformer Models MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-05T17:42:59.002057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:42:59.002057Z digest=sha256:acc6ab91e7009dc9368a47f749f7e4c6a8edab102234bac3e4938fb706bf3117

Observation e1af5e4c-63e2-45e3-bca6-ec8d16b5a907 · inbound

UMO: Scaling Multi-Identity Consistency for Image Customization via Matching Reward cites this paper.

UMO: Scaling Multi-Identity Consistency for Image Customization via Matching Reward MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-04T23:06:09.104752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:06:09.104752Z digest=sha256:e3bd4d914073d5a0da9f5c154a00b1f54d84bbf85a5f79c98005da134dd57b65

Observation 3edebac2-ca7b-45fa-981c-ffb08a5d2651 · inbound

Animalbooth: multimodal feature enhancement for animal subject personalization cites this paper.

Animalbooth: multimodal feature enhancement for animal subject personalization MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T15:11:32.545104Z

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.

source=pdf_text observed=2026-05-18T15:08:36.365653Z digest=sha256:fac50c65fb8f98da1ee59a568d63bd12b274294f469cee3094d1f34c1258f8bd

Observation 3c035540-f3ff-47d4-b4c3-b9d9e80a53da · inbound

PSR: Scaling Multi-Subject Personalized Image Generation with Pairwise Subject-Consistency Rewards cites this paper.

PSR: Scaling Multi-Subject Personalized Image Generation with Pairwise Subject-Consistency Rewards MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-05-17T03:51:29.447762Z

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.

source=pdf_text observed=2026-05-17T03:49:05.489626Z digest=sha256:f268561f814e368dec4504bf4c610b3b4795c22ff855c4c7cef56a5bfcded92d

Observation 7cc84ab5-5e7a-46de-a1ce-a5763b1880bd · inbound

LooseRoPE: Content-aware Attention Manipulation for Semantic Harmonization cites this paper.

LooseRoPE: Content-aware Attention Manipulation for Semantic Harmonization MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 42

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T16:08:04.470931Z

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.

source=pdf_text observed=2026-05-16T16:06:20.797660Z digest=sha256:e32942d1d78f61ea61e8588b5dfb3c70f12fd74ab8a59d31dfd405b728e3f20f

Observation d32c443f-6bb8-4682-9186-922de763ece1 · inbound

DSH-Bench: A Difficulty- and Scenario-Aware Benchmark with Hierarchical Subject Taxonomy for Subject-Driven Text-to-Image Generation cites this paper.

DSH-Bench: A Difficulty- and Scenario-Aware Benchmark with Hierarchical Subject Taxonomy for Subject-Driven Text-to-Image Generation MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 63

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T15:20:09.088674Z

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.

source=pdf_text observed=2026-05-15T15:16:59.801347Z digest=sha256:6e51639d155b50ec17b2fa8b5952d7aabcdfdc192dea7b127e24b20151f4cc55

Observation 3b4d2939-9722-491b-a16d-372f81f77ff0 · inbound

DSH-Bench: A Difficulty- and Scenario-Aware Benchmark with Hierarchical Subject Taxonomy for Subject-Driven Text-to-Image Generation cites this paper.

DSH-Bench: A Difficulty- and Scenario-Aware Benchmark with Hierarchical Subject Taxonomy for Subject-Driven Text-to-Image Generation MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 63

Resolution
unresolved
no resolver link, observed 2026-07-15T12:51:20.969593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T12:51:20.969593Z digest=sha256:83986e36afc093f8b0ae469aa0c7cbbc6047103f8cd30b5aee52d495b1555b78

Observation a33e9608-d78b-4d90-85ee-624103db4a0c · inbound

ASTRA: Enhancing Multi-Subject Generation with Retrieval-Augmented Pose Guidance and Disentangled Position Embedding cites this paper.

ASTRA: Enhancing Multi-Subject Generation with Retrieval-Augmented Pose Guidance and Disentangled Position Embedding MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 40

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T14:10:29.263978Z

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.

source=pdf_text observed=2026-05-10T13:49:59.632467Z digest=sha256:d8c243a5cd4b909d2945db369e862d41ba5827f44688d322eb067f3a0d1766d0

Observation 524961f5-bf00-4db4-8037-e997ead0bfa9 · inbound

EM-Vid: Training-Free Entity-Centric Memory for Efficient and Consistent Multi-Shot Video Generation cites this paper.

EM-Vid: Training-Free Entity-Centric Memory for Efficient and Consistent Multi-Shot Video Generation MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:00:22.391492Z

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.

source=pdf_text observed=2026-05-25T04:57:13.479165Z digest=sha256:78b8d2964214bc5c727a7f8fdfb66626c7f5e102f5bb6287d22578232dab919d

Observation c267c162-97ff-4d12-87a4-a4796848549b · inbound

MRT: Masked Region Transformer for Layered Image Generation and Editing at Scale cites this paper.

MRT: Masked Region Transformer for Layered Image Generation and Editing at Scale MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 52

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T18:33:50.277158Z

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.

source=pdf_text observed=2026-06-29T18:32:37.613906Z digest=sha256:5ff5453b8bac1a6039609cb1b2aae10b6794241d35f86ad258fe7cf81d403430

Observation e303529f-b4e6-4b23-83fe-9d02c1583eb9 · inbound

UniVerse: A Unified Modulation Framework for Segmentation-Free,Disentangled Multi-Concept Personalization cites this paper.

UniVerse: A Unified Modulation Framework for Segmentation-Free,Disentangled Multi-Concept Personalization MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 31

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T19:26:00.744974Z

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.

source=pdf_text observed=2026-06-28T22:34:05.043186Z digest=sha256:49c2d89d3d67ed68049de947ab8911e17e5c0a38ca3ef265bfbc988be3b46055

Observation 6ceb7e35-cca1-47b8-88cc-3309a06cbfd9 · inbound

A Comprehensive Ecosystem for Open-Domain Customized Video Generation cites this paper.

A Comprehensive Ecosystem for Open-Domain Customized Video Generation MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T10:17:57.913110Z

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.

source=pdf_text observed=2026-06-27T10:06:33.572182Z digest=sha256:dea360327a94b0b53743f8fd55424d067bd063e23db54acd284c3d54e82e498c

Observation c14420b5-2fe6-4c09-8906-9aabacf9cc11 · inbound

Atomistic Language Models Understand and Generate Materials cites this paper.

Atomistic Language Models Understand and Generate Materials MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 72

Resolution
verified exact
arxiv_id, observed 2026-07-04T06:09:36.519416Z

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.

source=pdf_text observed=2026-06-26T14:54:28.608607Z digest=sha256:c6f49a958ba76534abf855da83aa87de3d4f073a1d5ccc352203cd7b8923fcb3

Observation f1390630-648d-4d6c-b17d-f6e3e1daf51c · inbound

MIBE: Multi-subject Interaction Benchmark and Evaluator for Personalized Image Generation cites this paper.

MIBE: Multi-subject Interaction Benchmark and Evaluator for Personalized Image Generation MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T21:08:57.526105Z

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.

source=pdf_text observed=2026-07-03T21:05:29.882088Z digest=sha256:3ec4e590b4220bbdf05a116a2205fbf5ecde5978ad197fa03624d0ed2e49027a