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Paper Citation Record · LEDGER

Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 40 inbound Pith citation observations for arXiv:2504.02160.

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

pith.paper-citation-record.v1
2504.02160 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 40 of 40 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:53:29.227782Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T19:08:50.368542Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e0af591f-9c6b-49b2-9505-4516f554c4b5 · 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 Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 11

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verified exact
arxiv_id, observed 2026-05-22T18:11:54.569021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T18:09:50.633826Z digest=sha256:04cf47e976f9b3a7687a7758da15950a57fb3c87411868530bedc917584d552b

Observation 885d3daf-870b-416e-85b9-470b63d58f7c · inbound

In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer cites this paper.

In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 28

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verified exact
arxiv_id, observed 2026-05-16T16:07:53.089204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T16:07:53.054355Z digest=sha256:d9e2f532580c679aa6efd26d8229c110155d4e42e462e38e98199f82f21b1c96

Observation 320137bf-3f49-434a-a5a4-e127f3e0da13 · inbound

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis cites this paper.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 50

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no resolver link, observed 2026-08-07T12:53:29.227782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:53:29.227782Z digest=sha256:efd32e422cf61fdee715af47e0426f1601d62a4a82c49b9b99fa9f4d2132cb30

Observation cc34760f-04e2-40e4-8373-2730428d775e · inbound

LoRAShop: Training-Free Multi-Concept Image Generation and Editing with Rectified Flow Transformers cites this paper.

LoRAShop: Training-Free Multi-Concept Image Generation and Editing with Rectified Flow Transformers Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 43

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no resolver link, observed 2026-08-07T12:41:24.209707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:41:24.209707Z digest=sha256:4746d8a5bfdcd39bccd7f4c157b4363b483562a8a62cd68b873d342332cec752

Observation 9566bd98-1cac-4de7-afb5-0f23f089cbc9 · inbound

Image Editing As Programs with Diffusion Models cites this paper.

Image Editing As Programs with Diffusion Models Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 64

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no resolver link, observed 2026-08-07T10:51:38.555957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:51:38.555957Z digest=sha256:cef64483192f76ebc0f8dbc2a23d250076e602c3a37713a16fc12c5dd618da61

Observation f8ed8aab-b6c4-4014-ac81-e2676973098e · inbound

FullDiT2: Efficient In-Context Conditioning for Video Diffusion Transformers cites this paper.

FullDiT2: Efficient In-Context Conditioning for Video Diffusion Transformers Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 19

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unresolved
no resolver link, observed 2026-08-07T10:51:45.926726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:51:45.926726Z digest=sha256:21930e6ac17c1bd680ea357e28153bd0ae8269d0ef83c2d191fb372afc39aa0f

Observation bc18696b-d073-4b85-92ea-4cabc108bb91 · inbound

PairEdit: Learning Semantic Variations for Exemplar-based Image Editing cites this paper.

PairEdit: Learning Semantic Variations for Exemplar-based Image Editing Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 63

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no resolver link, observed 2026-08-07T05:29:14.863460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:29:14.863460Z digest=sha256:eca863178952aadf2777b99043ea3fbb3eda83e775881ef600c10ec06e0d3aa8

Observation ef199316-fc17-48f4-94e0-96ea07d976d4 · inbound

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

OmniGen2: Towards Instruction-Aligned Multimodal Generation Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 79

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arxiv_id, observed 2026-05-19T07:52:10.924837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T07:47:34.464711Z digest=sha256:e0b7341bbada2bbc0d23570bc178c96abb4ed58708d0d5835deebbcce1dac5fb

Observation f96b9a0a-e68f-47f6-ae2c-98ae8c6a048d · inbound

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

XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 13

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no resolver link, observed 2026-08-06T22:31:37.542461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:31:37.542461Z digest=sha256:2ade0e3198f21528aa535f860414b8a5727894b02560239ed8cfeaaa01658d81

Observation 94b5e726-2eaa-4714-abaa-c5571e8cbdde · inbound

Imagine for Me: Creative Conceptual Blending of Real Images and Text via Blended Attention cites this paper.

Imagine for Me: Creative Conceptual Blending of Real Images and Text via Blended Attention Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 21

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no resolver link, observed 2026-08-06T21:45:16.749206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:45:16.749206Z digest=sha256:181fd12f87f6cc391772c4cf3e1ebf3c01e6334ccb0eade3565998bbf37294e9

Observation b6c24b32-0c70-4d77-9ea5-2b4950a3001b · 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 Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 46

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no resolver link, observed 2026-08-06T20:46:25.155847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:46:25.155847Z digest=sha256:e5e85076c5400601b9cda60772ac6401ff800f9018840e7b2ac8e1c3bd631e60

Observation 77515524-4a0b-4c95-91a5-f8085a14a04d · inbound

DreamPainter: Image Background Inpainting for E-commerce Scenarios cites this paper.

DreamPainter: Image Background Inpainting for E-commerce Scenarios Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 28

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no resolver link, observed 2026-08-06T05:11:38.326855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:11:38.326855Z digest=sha256:13c13c900dec658554e68aa3011b4fe2f1b8f4d31beca7cb0b8f47fa1548acad

Observation 6770393b-c88b-4663-8b23-dc95edadc091 · inbound

Echo-4o: Harnessing the Power of GPT-4o Synthetic Images for Improved Image Generation cites this paper.

Echo-4o: Harnessing the Power of GPT-4o Synthetic Images for Improved Image Generation Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 68

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no resolver link, observed 2026-08-05T20:44:16.671224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:44:16.671224Z digest=sha256:4133119d75d24be82c04a30d0a3971a62338987c7a5d4c837ba981cd57f7851a

Observation e6420c93-3141-4cb9-bc5a-1443315e3a4b · inbound

USO: Unified Style and Subject-Driven Generation via Disentangled and Reward Learning cites this paper.

USO: Unified Style and Subject-Driven Generation via Disentangled and Reward Learning Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 34

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no resolver link, observed 2026-08-05T16:07:24.715507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T16:07:24.715507Z digest=sha256:d196b80b14d1cc19eb58d33b444ea3ef600bde2ebbb60c89220f9f0f9e368cc4

Observation ffc348a3-a6be-45e0-9a27-9ec261c14643 · inbound

FocusDPO: Dynamic Preference Optimization for Multi-Subject Personalized Image Generation via Adaptive Focus cites this paper.

FocusDPO: Dynamic Preference Optimization for Multi-Subject Personalized Image Generation via Adaptive Focus Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 37

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no resolver link, observed 2026-08-05T12:53:42.038331Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:53:42.038331Z digest=sha256:c0efe11e960703bfbd444b98d59bfcecc05c9e209b2f313c5ef1f5e965f00287

Observation 299a3d50-ab0c-4d08-9f21-970dc41eb57f · inbound

EditIDv2: Editable ID Customization with Data-Lubricated ID Feature Integration for Text-to-Image Generation cites this paper.

EditIDv2: Editable ID Customization with Data-Lubricated ID Feature Integration for Text-to-Image Generation Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 24

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no resolver link, observed 2026-08-05T05:20:00.975597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:20:00.975597Z digest=sha256:b95694160dba14775ade5a46066457474d94a52471114689844221b2745c4733

Observation e7b1079e-987c-4055-8827-e5e0b9820761 · 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 Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 32

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no resolver link, observed 2026-08-04T23:06:09.112747Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:06:09.112747Z digest=sha256:8df4ccd084da443a87adfa0e4d0ba030a594e8f959b473fc02d8518774acd89d

Observation 09e1d13a-23f6-4a4d-ad06-9f9249e653a2 · inbound

Adversarial Concept Distillation for One-Step Diffusion Personalization cites this paper.

Adversarial Concept Distillation for One-Step Diffusion Personalization Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 98

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verified exact
arxiv_id, observed 2026-05-18T04:50:53.716606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T04:50:01.364000Z digest=sha256:bb27ebda05ff1306e3b0aa98c58f6136d8fc57a4500250db0327b7fd8224de62

Observation 3cda477b-2e74-45b3-b8ba-0f001350c7df · inbound

Emu3.5: Native Multimodal Models are World Learners cites this paper.

Emu3.5: Native Multimodal Models are World Learners Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 109

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arxiv_id, observed 2026-05-18T01:12:13.604462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T01:12:13.426640Z digest=sha256:562a2c49468f0cf0979de6fb8a6de2e7328dd8ff76cf7bc2c32ba3ec9673bcdd

Observation 9ec24dd0-c196-4990-81ed-38cfda623f4c · inbound

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation cites this paper.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 57

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no resolver link, observed 2026-08-04T06:47:09.770582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:47:09.770582Z digest=sha256:070d57af298bbeb5f1675251d65f941829c5ba65c0a0faaec26f4364195a8215

Observation 89f132e9-1361-4b30-ab54-33d6438d371b · 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 Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 40

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arxiv_id, observed 2026-05-17T03:51:29.452509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-17T03:49:05.489626Z digest=sha256:2a9201e2d59b1451232f71b9dafc6a03105574c110329dec5de274caa942021a

Observation 9b242daf-048c-4226-a46c-cff78e317caf · inbound

Scone: Bridging Composition and Distinction in Subject-Driven Image Generation via Unified Understanding-Generation Modeling cites this paper.

Scone: Bridging Composition and Distinction in Subject-Driven Image Generation via Unified Understanding-Generation Modeling Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 39

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arxiv_id, observed 2026-05-16T22:41:19.273475Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T22:39:32.955779Z digest=sha256:a0ad07048832c0aca643e1d0742dee3401ce7c738cf43ef9567fb7a1311da75a

Observation 15a56cba-fde1-406b-9f63-cdcf368c9d73 · inbound

Scone: Bridging Composition and Distinction in Subject-Driven Image Generation via Unified Understanding-Generation Modeling cites this paper.

Scone: Bridging Composition and Distinction in Subject-Driven Image Generation via Unified Understanding-Generation Modeling Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 39

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source=pdf_text observed=2026-08-03T16:37:07.025646Z digest=sha256:10959afca89227bd7a8bb7281ba769361e4173ae0d53abc7cbf3a36cd3bfcf5c

Observation 6ab24eaa-faef-49e4-9662-4c8c07a8f291 · inbound

InstructMoLE: Instruction-Guided Mixture of Low-rank Experts for Multi-Conditional Image Generation cites this paper.

InstructMoLE: Instruction-Guided Mixture of Low-rank Experts for Multi-Conditional Image Generation Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 34

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arxiv_id, observed 2026-05-16T19:11:11.439190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T19:10:47.425041Z digest=sha256:1a6850f692c7fc70295703add81dc03c57054f9acc2ac6a0c10766c44ed036ed

Observation 1a151d56-3f35-429f-8e46-63e055cc6fa7 · inbound

Muses: Designing, Composing, Generating Nonexistent Fantasy 3D Creatures without Training cites this paper.

Muses: Designing, Composing, Generating Nonexistent Fantasy 3D Creatures without Training Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 56

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T12:23:34.499794Z digest=sha256:7e6af12477394aef5da88c3b8a55d40d14e6e9de774431e9b0de6bd15512cdb5

Observation a56049df-3c24-4d30-8fd4-57b3a0aad5db · inbound

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

Hierarchical Concept-to-Appearance Guidance for Multi-Subject Image Generation Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 34

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no resolver link, observed 2026-08-03T05:01:44.798189Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T05:01:44.798189Z digest=sha256:d63f419d412b30354506fd7265eb61b707a45c845ab7f78331c860c1602c0127

Observation 545ce45c-36c2-42d1-8df5-888c46cb507f · inbound

PureCC: Pure Learning for Text-to-Image Concept Customization cites this paper.

PureCC: Pure Learning for Text-to-Image Concept Customization Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 46

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verified exact
arxiv_id, observed 2026-05-21T11:10:02.191673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-21T11:09:15.512162Z digest=sha256:fa476d34e23449daae6f454c5baae1e6b07cfdd1fef1433785abee9173383d4b

Observation f93df6df-f217-41c1-8d9d-5ee14c5c2dc6 · 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 Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 67

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arxiv_id, observed 2026-05-15T15:20:09.038403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T15:16:59.801347Z digest=sha256:9848d830c2ee6a7c1ed4ad8f59db7491fa7f9106a9cf72fd7604ee266d08a807

Observation 32f50ad0-35a9-4a69-929e-03e5d090a695 · 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 Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 67

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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=sha256:13fd62855a1edec96caf7e47cdc73fb87301c4e95fd26b5a77a2c5c8de7feeb7

Observation 0863cc3f-de39-460c-89d6-602100cf9eb1 · 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 Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 31

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verified exact
arxiv_id, observed 2026-05-10T21:55:49.159415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T20:33:25.422350Z digest=sha256:ff76beb2c0ad2a8199c2d5f6cc28c6edf5233b91f39bfdfa451887921a83ebb6

Observation bc31739b-5222-401d-8185-0078b8cbf692 · inbound

ID-Sim: An Identity-Focused Similarity Metric cites this paper.

ID-Sim: An Identity-Focused Similarity Metric Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 93

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verified exact
arxiv_id, observed 2026-05-10T21:55:50.711747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T20:28:41.596362Z digest=sha256:ed76278eba744c034043e3debec2fbf69b2dee2d0c0d56958934240e90dfd1a9

Observation 7be5e315-df86-4dcf-b933-1fbb0bb5cc56 · 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 Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 43

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verified exact
arxiv_id, observed 2026-05-10T14:10:29.292556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T13:49:59.632467Z digest=sha256:6efd7a22d2d68a86f2f82645543992ef5089fb98a7ede32d14ab9789481dcff7

Observation 112a85e2-383c-40ac-a64b-e27168ced281 · inbound

Towards In-Context Tone Style Transfer with A Large-Scale Triplet Dataset cites this paper.

Towards In-Context Tone Style Transfer with A Large-Scale Triplet Dataset Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 44

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metadata mismatch
arxiv_id, observed 2026-05-10T09:08:26.585621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T08:23:04.555337Z digest=sha256:1a1899facae3c98b3b231ab1230358075f96c561384608b3913f9e0c3b04c534

Observation 3d7f9a77-74be-48b5-ba6c-75b2b3313907 · inbound

Fashion130K: An E-commerce Fashion Dataset for Outfit Generation with Unified Multi-modal Condition cites this paper.

Fashion130K: An E-commerce Fashion Dataset for Outfit Generation with Unified Multi-modal Condition Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:51:27.752417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T03:56:43.640874Z digest=sha256:8e99f658e3b4f196b744b81d5a3b3cc943376671853ef98325841484842c1cb9

Observation 782ebfba-ac51-4bef-8a25-91509d0b5ad7 · inbound

Fashion130K: An E-commerce Fashion Dataset for Outfit Generation with Unified Multi-modal Condition cites this paper.

Fashion130K: An E-commerce Fashion Dataset for Outfit Generation with Unified Multi-modal Condition Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-14T21:58:03.316628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T21:56:10.499014Z digest=sha256:a9483b0db4e8187660a9755c69253be8f98782f2ebc1ed6d6f15f0f25682919d

Observation d1885c3e-102a-4db1-9745-c660d2eb4bcd · inbound

Lance: Unified Multimodal Modeling by Multi-Task Synergy cites this paper.

Lance: Unified Multimodal Modeling by Multi-Task Synergy Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 128

Resolution
verified exact
arxiv_id, observed 2026-05-20T11:48:14.799855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T11:46:52.658984Z digest=sha256:cee700ec1238c497cfa4f8b13f68382b9140b6dcb6cbbc20d6d7a08d585c2a80

Observation e9a2707d-6317-42e9-b7a5-b8f0c5c9e179 · inbound

Lance: Unified Multimodal Modeling by Multi-Task Synergy cites this paper.

Lance: Unified Multimodal Modeling by Multi-Task Synergy Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 129

Resolution
verified exact
arxiv_id, observed 2026-05-21T07:59:50.555217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-21T07:56:34.034047Z digest=sha256:0e2a2e2fcad96d3126aaff4d91a55285adb54b9cc635847c637d08c6be9dbfdb

Observation 7a0e91a7-66b2-42db-a4e2-81591b233fbb · 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 Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-07-01T19:26:00.761725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T22:34:05.043186Z digest=sha256:53570d9d747a17c8b51ac1810a2e85ec67f48c99a53c0740e94d8b3cdffdc670

Observation 2c9b636d-2cf4-4acb-a1f7-b203ac2d12c4 · inbound

RAVA: Retrieval-Augmented Viewpoint Alignment for Subject-Driven Image Generation cites this paper.

RAVA: Retrieval-Augmented Viewpoint Alignment for Subject-Driven Image Generation Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-07-03T19:08:50.370514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T02:02:32.008630Z digest=sha256:d7a70a6ef414620f41339026da5632d663a23a05993828744b740c62df1117f9

Observation fba856a1-923d-4f63-a43d-c12404ffca11 · inbound

ICDepth: Taming Video Diffusion Models for Video Depth Estimation via In-Context Conditioning cites this paper.

ICDepth: Taming Video Diffusion Models for Video Depth Estimation via In-Context Conditioning Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T17:08:42.886922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-03T16:59:40.925535Z digest=sha256:f341135bea2181dbf1d0c1399beed62f5e31e51429bafe525c8b7a69814b3af2