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Paper Citation Record · LEDGER

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement

As of 9 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 5 inbound Pith citation observations for arXiv:2509.01977.

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

pith.paper-citation-record.v1
2509.01977 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:04:29.002125Z

measured 41 of 41 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:01:44.036386Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:39:50.230089Z

Reference resolution

36 of 36 outbound references displayed

  • verified exact4
  • verified fuzzy15
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation daaa6aa8-03b0-490c-a024-ab481802f322 · outbound

This paper cites Surf: Speeded up robust features.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Surf: Speeded up robust features

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.448072Z

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.

source=pdf_text observed=2026-08-05T12:04:28.871585Z digest=sha256:7e60833d985f5e81f8e7dc6c399c3b5ac1d69941b399da47474801aecc123e9d

Observation 9fd33aeb-613c-48d9-b8e6-543cfa57ce5f · outbound

This paper cites XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-05T12:04:28.875711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.875711Z digest=sha256:3d842d25e965d2d0632ef85a879646faa4e3effa89cc222cee8e107aa9f247c8

Observation a84d353c-a019-4af3-9317-aecd1dc37562 · outbound

This paper cites Arcface: Additive angular margin loss for deep face recognition.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Arcface: Additive angular margin loss for deep face recognition

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.437538Z

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.

source=pdf_text observed=2026-08-05T12:04:28.879640Z digest=sha256:a9dfaa81df2dd2cfc43507f6599e52b0460696305b0e2a095c0626c4dd857a23

Observation 06a4d86f-c766-4db8-b418-a69bc61d9662 · outbound

This paper cites Aesthetic predictor v2.5: Siglip-based aesthetic score predictor.https://github.com/discus0434/ aesthetic-predictor-v2-5, 2024.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Aesthetic predictor v2.5: Siglip-based aesthetic score predictor.https://github.com/discus0434/ aesthetic-predictor-v2-5, 2024

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.427111Z

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.

source=pdf_text observed=2026-08-05T12:04:28.883283Z digest=sha256:adfe5b978a9f30419bad8d87d4463455769724f75f7502a5eeb7ce5728b15f0a

Observation d4870998-682f-400f-9de6-015e44e3e919 · outbound

This paper cites Scaling rectified flow transformers for high-resolution image synthesis.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Scaling rectified flow transformers for high-resolution image synthesis

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-05T12:04:28.886960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.886960Z digest=sha256:2c40bb0bacc4775284360c64dfaa9777fe5457a102c35d2080965758043c5576

Observation 212cf80d-2a4a-4cfd-9060-4d1089b769b3 · outbound

This paper cites Proposal flow: Semantic correspondences from object proposals.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Proposal flow: Semantic correspondences from object proposals

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.411183Z

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.

source=pdf_text observed=2026-08-05T12:04:28.891489Z digest=sha256:bf737a11731768cb5efbc2ae72c271e5867de00abec6499a590055f9770e0c25

Observation 4398c039-fb14-4b72-b334-27e9081a27a6 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Lora: Low-rank adaptation of large language models

Reference 7

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unresolved
no resolver link, observed 2026-08-05T12:04:28.895505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.895505Z digest=sha256:c2d1c227724e747d4fa330e2204f603d1e8836012a09334b707bb913269f0731

Observation e3649a87-bdab-4bbe-b64b-a37c6bae2479 · outbound

This paper cites ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment

Reference 8

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no resolver link, observed 2026-08-05T12:04:28.898718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.898718Z digest=sha256:4cccbe6b3308c239a203ed7335cbe3a1b0d128929ffcb0f026db40dadc4b2422

Observation 7234126f-f69d-41ad-bda2-9fb2ba0d7339 · outbound

This paper cites GPT-4o System Card.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement GPT-4o System Card

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T12:04:28.902170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.902170Z digest=sha256:5471643a7288d062fe9a3b51fba5ae6b14a763a26f7f3fd0a12577cad06192a1

Observation a3abfdb0-e0c8-4fab-bc2c-85d8310dc7b9 · outbound

This paper cites Adam: A method for stochastic optimization.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Adam: A method for stochastic optimization

Reference 10

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unresolved
no resolver link, observed 2026-08-05T12:04:28.905552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.905552Z digest=sha256:536782289bdc5a543b0ceed94e1fc3a19b295eaceeec0ff0511b73570e962f13

Observation 1e4813cc-bd4e-4274-8a3f-77d01d34ce32 · outbound

This paper cites Segment anything.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Segment anything

Reference 11

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no resolver link, observed 2026-08-05T12:04:28.908455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.908455Z digest=sha256:4dbf95a5bbd38f059e9feb0f492859c20f75a2dc13de24fe69a0eb9d5f6d0f1c

Observation 09eb9a9c-1812-468e-bfc2-06a733d6137b · outbound

This paper cites Flux-dev-1.0.https://github.com/black-forest-labs/flux, 2024.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Flux-dev-1.0.https://github.com/black-forest-labs/flux, 2024

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.381988Z

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.

source=pdf_text observed=2026-08-05T12:04:28.911742Z digest=sha256:1f81f804dc609c61afa76ea0a348980d3c0dd24b69b135468081ba47e6e4a63e

Observation 2768d2da-b35a-45f0-8684-542a8025b8a0 · outbound

This paper cites FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T12:04:28.914683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.914683Z digest=sha256:9703f68be1fd4dba6f67a371f4e8d307502483003b46d9aed8087902e7b77fc3

Observation a03a3e9e-964a-4058-8969-0b292543463c · outbound

This paper cites SFNet: Learning Object-aware Semantic Correspondence.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement SFNet: Learning Object-aware Semantic Correspondence

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-05T12:04:29.216206Z

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.

source=pdf_text observed=2026-08-05T12:04:28.918736Z digest=sha256:e062e3978df59e60515670eb732993d64f3c2709513f98d44551f7aa11f4e1fc

Observation 22c743fb-8e2b-4aaf-b248-b7a74bad7374 · outbound

This paper cites Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-05T12:04:29.201821Z

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.

source=pdf_text observed=2026-08-05T12:04:28.921892Z digest=sha256:684fab12b342542ca53b74da8be3c5a3e582b2f91d5c6d4f82482552aa35ec96

Observation 85f4c5d4-215e-4754-a5c8-ea1a9b689111 · outbound

This paper cites Blip-diffusion: Pre-trained subject representation for controllable text-to-image generation and editing.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Blip-diffusion: Pre-trained subject representation for controllable text-to-image generation and editing

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.372198Z

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.

source=pdf_text observed=2026-08-05T12:04:28.925107Z digest=sha256:89f01e28f4c534e91b1b3038a7e9c567009d995b7f6c5ffa71b994479f3464e2

Observation 3153d103-8670-4e22-b076-f12e87a1ce30 · outbound

This paper cites Distinctive image features from scale-invariant keypoints.IJCV, 60:91–110, 2004.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Distinctive image features from scale-invariant keypoints.IJCV, 60:91–110, 2004

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.361728Z

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.

source=pdf_text observed=2026-08-05T12:04:28.928096Z digest=sha256:95e87a34d0c9fa0598685e93878fa2155b4a01f4f5c833d72bb4f178a53ff7a9

Observation 2f932e42-047e-4b49-a9b5-2ea0e947ba73 · outbound

This paper cites RegionDrag: Fast Region-Based Image Editing with Diffusion Models.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement RegionDrag: Fast Region-Based Image Editing with Diffusion Models

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-05T12:04:29.186985Z

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.

source=pdf_text observed=2026-08-05T12:04:28.931583Z digest=sha256:e1e0cf294b2cffb4bb38e00d0fbe6b6a6de433a2cb43de173c436f62be3d6209

Observation 41c6200f-e38b-4ce0-9bcf-938bb0a9b3c9 · outbound

This paper cites Hyperpixel flow: Semantic correspondence with multi- layer neural features.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Hyperpixel flow: Semantic correspondence with multi- layer neural features

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.351316Z

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.

source=pdf_text observed=2026-08-05T12:04:28.935002Z digest=sha256:14f43236c12e3a4cf9226d116f3e95d41cf08ec93831c416060afd110e47e9f9

Observation 3724f14d-8124-4701-92a2-9b4780eff1c5 · outbound

This paper cites Dreamo: A unified framework for image customization.arXiv preprint arXiv:2504.16915, 2025.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Dreamo: A unified framework for image customization.arXiv preprint arXiv:2504.16915, 2025

Reference 21

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no resolver link, observed 2026-08-05T12:04:28.943160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.943160Z digest=sha256:9a345ded4502914c651a1e9709d3efc627bb7092b81db798d29d1e870de340a1

Observation 25d5673c-7f3d-4043-ba2c-172b469bf35f · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement DINOv2: Learning Robust Visual Features without Supervision

Reference 22

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no resolver link, observed 2026-08-05T12:04:28.946533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.946533Z digest=sha256:b4f5121af9f608ee6ee184df81dd9d5ef490a7e26dbeafd156f0f65a84cd0444

Observation b0bf3da2-fa1a-412e-8de8-386d19c5ecea · outbound

This paper cites Learning transferable visual models from natural language supervision.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Learning transferable visual models from natural language supervision

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T12:04:28.950021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.950021Z digest=sha256:e2d8de7391cd787fe9e4217c9229825086ace22b560714b10e4e3e00f3bb055d

Observation 7daa8a1a-8d23-4216-b790-79ffb4352d1f · outbound

This paper cites Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Reference 24

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no resolver link, observed 2026-08-05T12:04:28.953456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.953456Z digest=sha256:0561c7800137faff3442fff0965f950fd1f8c177973a74b1c50d95c7ad90ca4f

Observation 344aec03-832b-4951-9652-2b6d44ab9985 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.334138Z

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.

source=pdf_text observed=2026-08-05T12:04:28.956872Z digest=sha256:6af307ea2d39cf1c5324730f3030fd86afbefd2c36d02c78be93a16b4b88c87d

Observation 16e0a129-4c1b-4ab0-b54e-b82b2d547bc0 · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024

Reference 26

Resolution
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no resolver link, observed 2026-08-05T12:04:28.960111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.960111Z digest=sha256:8e44e3080ec19cb99f517aa13b0a4613f302db0e1e9a6e18e1c9bbf6e50fae4b

Observation 108dddce-fc05-47e7-a328-7d5eac5598e0 · outbound

This paper cites Ominicontrol: Minimal and universal control for diffusion transformer.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Ominicontrol: Minimal and universal control for diffusion transformer

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.317514Z

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.

source=pdf_text observed=2026-08-05T12:04:28.963620Z digest=sha256:ee5bedcff7175404f36e6cbdea32790c3ca79d345541dfc4e29103110330bcd5

Observation 17473e51-6646-4202-a9be-59ec41fa3644 · outbound

This paper cites Emergent Correspondence from Image Diffusion.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Emergent Correspondence from Image Diffusion

Reference 28

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unresolved
no resolver link, observed 2026-08-05T12:04:28.966971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.966971Z digest=sha256:1efbebca4974e27b213c1c70afd6aef8a742ededb9e40b97fb3b29c814b83eae

Observation e40fd7d3-636b-49e6-b623-6f39653355f9 · outbound

This paper cites Ms-diffusion: Multi-subject zero-shot image personalization with layout guidance.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Ms-diffusion: Multi-subject zero-shot image personalization with layout guidance

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.306738Z

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.

source=pdf_text observed=2026-08-05T12:04:28.970340Z digest=sha256:20668b49d7669c566f53171dfc5d40c754c2b0fa0357e8b2f1ad6ed626fc6a01

Observation 0cd68c83-9b9a-4dc1-8953-e73c63c7c53e · outbound

This paper cites OmniGen2: Towards Instruction-Aligned Multimodal Generation.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement OmniGen2: Towards Instruction-Aligned Multimodal Generation

Reference 30

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unresolved
no resolver link, observed 2026-08-05T12:04:28.975261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.975261Z digest=sha256:c2e831d7081a4245fdc31252e2a183da6fd91cc2e5bf34c84a3d5461817327ff

Observation cf65f635-0651-44bb-b879-1c0684abc53a · outbound

This paper cites Less-to-more generalization: Unlocking more controllability by in-context generation.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Less-to-more generalization: Unlocking more controllability by in-context generation

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.296772Z

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.

source=pdf_text observed=2026-08-05T12:04:28.981271Z digest=sha256:3153659446f50f1e1b5c356777eb2ae062b8d25aeb760a359f8ad1064db39ec3

Observation f5b3eed3-6c6c-4296-9aba-b4cd0fa55133 · outbound

This paper cites AP-10K: A Benchmark for Animal Pose Estimation in the Wild.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement AP-10K: A Benchmark for Animal Pose Estimation in the Wild

Reference 32

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unresolved
no resolver link, observed 2026-08-05T12:04:28.984470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.984470Z digest=sha256:348f0e40bd007d6b6a37cb4b35073f69d4914c44cd3e8c6b62b586ed35faaf2d

Observation 5744d108-d99c-4434-812f-9d20f08ac9e1 · outbound

This paper cites A tale of two features: Stable diffusion complements dino for zero-shot semantic correspondence,.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement A tale of two features: Stable diffusion complements dino for zero-shot semantic correspondence,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.286652Z

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.

source=pdf_text observed=2026-08-05T12:04:28.987975Z digest=sha256:7e764171491e9fa13218352d9a4c5b763c5ec923b053b6850425c4f793523490

Observation 478fb03f-7919-4278-9f12-c684d5b7e6a5 · outbound

This paper cites Telling Left from Right: Identifying Geometry-Aware Semantic Correspondence.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Telling Left from Right: Identifying Geometry-Aware Semantic Correspondence

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-08-05T12:04:29.037396Z

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.

source=pdf_text observed=2026-08-05T12:04:28.995742Z digest=sha256:e22102b11a11f2b90dae9ca0d918afbbdac77833d56d382b78523bd058fe36d5

Observation 7d7ef960-f152-4913-85d1-017841cc8aa6 · outbound

This paper cites Ssr-encoder: Encoding selective subject representation for subject-driven generation.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Ssr-encoder: Encoding selective subject representation for subject-driven generation

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.276438Z

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.

source=pdf_text observed=2026-08-05T12:04:28.999165Z digest=sha256:9b3b8ef5152bd1b764cd8b46e4d813a4995365776f7525f1167381e04f4cea0b

Observation e4560bd5-1fb8-46d5-95cf-b16bc72f3066 · outbound

This paper cites Ssr-encoder: Encoding selective subject representation for subject-driven generation.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement Ssr-encoder: Encoding selective subject representation for subject-driven generation

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:04:29.266259Z

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.

source=pdf_text observed=2026-08-05T12:04:29.002125Z digest=sha256:0b2135fb624aba1eb351a97fcead420e0b8c952bfa479432163d8c74adadca28

Observation 221c2033-7d97-4719-9121-72ccb69954ff · outbound

This paper cites A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence.

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-05T12:04:28.992387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:28.992387Z digest=sha256:327b85200d25b815dcf0eacecb41ebca8fb25cbe502dd0269c52b1cfc5414efa

Pith citing papers

Observation cb8459a4-affe-40f4-bd89-82c25d4e7f7c · inbound

Hierarchical Concept-to-Appearance Guidance for Multi-Subject Image Generation cites this paper.

Hierarchical Concept-to-Appearance Guidance for Multi-Subject Image Generation MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-03T05:01:44.036386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T05:01:44.036386Z digest=sha256:50f8d02e66b209082e1bde4b7bf193673ca320955ebb17773019fe6209173793

Observation 7a069496-f67f-4e37-a17e-98b77a18a06a · inbound

Training-Free Image Editing with Visual Context Integration and Concept Alignment cites this paper.

Training-Free Image Editing with Visual Context Integration and Concept Alignment MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:05:47.773724Z

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.

source=pdf_text observed=2026-05-10T20:17:34.383852Z digest=sha256:568ef20b44c9648c00ab98f7713fa3739eb38883a2e7ee4707c96cb6d23d5545

Observation 8a877661-85a4-48b3-95ac-ed1300b863fb · inbound

Vanast: Virtual Try-On with Human Image Animation via Synthetic Triplet Supervision cites this paper.

Vanast: Virtual Try-On with Human Image Animation via Synthetic Triplet Supervision MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-10T21:55:49.167329Z

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.

source=pdf_text observed=2026-05-10T20:33:25.422350Z digest=sha256:f603da7e7c17467410f95411d14b5b6e874218056ce7a699924e4be18b5b0f54

Observation 44f66d05-17c4-48fa-a85d-bca8989511a7 · inbound

DreamShot: Personalized Storyboard Synthesis with Video Diffusion Prior cites this paper.

DreamShot: Personalized Storyboard Synthesis with Video Diffusion Prior MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-10T07:21:54.987881Z

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.

source=pdf_text observed=2026-05-10T07:21:45.633310Z digest=sha256:6f2dd9ea1b938d5edd40bb16c09e1638cc5a5acfe95ce1257c55d62693111f13

Observation 1d743213-786c-4366-905c-5d5e85aab1a9 · inbound

Scaling Multi-Reference Image Generation with Dynamic Reward Optimization cites this paper.

Scaling Multi-Reference Image Generation with Dynamic Reward Optimization MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:39:50.231683Z

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.

source=pdf_text observed=2026-06-26T05:06:12.721122Z digest=sha256:c8d4b8ff8fd650b87db6d070dda00bcbbfe77d846d1bd90e6fb9e819446fe2c6