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Paper Citation Record · LEDGER

Multi-LoRA Composition for Image Generation

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:2402.16843.

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

pith.paper-citation-record.v1
2402.16843 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 23 of 23 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:51:41.256703Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T01:37:30.937151Z

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Outbound references

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Pith citing papers

Observation 0de00f3b-b4ad-4704-a2f2-164ded11e2a4 · inbound

Modification Takes Courage: Seamless Image Stitching via Reference-Driven Inpainting cites this paper.

Modification Takes Courage: Seamless Image Stitching via Reference-Driven Inpainting Multi-LoRA Composition for Image Generation

Reference 48

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source=pdf_text observed=2026-08-12T19:50:01.812597Z digest=sha256:2e6df5012c5d242e63e8bf0bd6d701935c7cfd866eef602e4d9e0cc74a85817b

Observation fae18764-4937-4001-9cea-be086f72a098 · inbound

Multi LoRA Meets Vision: Merging multiple adapters to create a multi task model cites this paper.

Multi LoRA Meets Vision: Merging multiple adapters to create a multi task model Multi-LoRA Composition for Image Generation

Reference 13

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source=pdf_text observed=2026-08-12T15:37:00.421197Z digest=sha256:23b39ad66ed9d0dfc821c317e57a75435715b5d98a798235da287077aaee75aa

Observation 2553e3c8-6dfb-467c-93c7-efef82df77ac · inbound

IterIS: Iterative Inference-Solving Alignment for LoRA Merging cites this paper.

IterIS: Iterative Inference-Solving Alignment for LoRA Merging Multi-LoRA Composition for Image Generation

Reference 55

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source=pdf_text observed=2026-08-12T15:15:56.632930Z digest=sha256:2cc42d7e541ff6212b39ec0d8a659d3171fb6173a0ffb0e5ce8a0cd4309baf20

Observation f76943f8-674d-4c92-ab40-a18eec0817c7 · inbound

Safety Alignment Backfires: Preventing the Re-emergence of Suppressed Concepts in Fine-tuned Text-to-Image Diffusion Models cites this paper.

Safety Alignment Backfires: Preventing the Re-emergence of Suppressed Concepts in Fine-tuned Text-to-Image Diffusion Models Multi-LoRA Composition for Image Generation

Reference 91

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source=pdf_text observed=2026-08-12T05:33:18.477568Z digest=sha256:a577e3cb8f614b1c3c0813ea34d6c0d738d39b6ceb0b118827a9cc42f92dba64

Observation 6603938e-b3d5-4a3f-a08e-b6b5a2309493 · inbound

S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity cites this paper.

S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity Multi-LoRA Composition for Image Generation

Reference 83

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source=pdf_text observed=2026-08-11T19:55:12.217792Z digest=sha256:b92540ef12aa380a2df3791670c388bbb5ef1e6bf66721d1e258ac2e2eb0360e

Observation ea78b070-4909-420f-8120-e3794849d30a · inbound

AlignGuard: Scalable Safety Alignment for Text-to-Image Generation cites this paper.

AlignGuard: Scalable Safety Alignment for Text-to-Image Generation Multi-LoRA Composition for Image Generation

Reference 63

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source=pdf_text observed=2026-08-11T15:57:55.482042Z digest=sha256:a9ff011a4d83430292844d702d75a36ecf7c7325ddc3c32871b9c21480b3281b

Observation 38b99fee-15b0-499a-99bc-18db78878446 · inbound

Can video generation replace cinematographers? Research on the cinematic language of generated video cites this paper.

Can video generation replace cinematographers? Research on the cinematic language of generated video Multi-LoRA Composition for Image Generation

Reference 45

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source=pdf_text observed=2026-08-11T14:52:04.452484Z digest=sha256:c49945a200dc6d8174088410a0b5fbc6a87fd52187b5391179328e639d5c9175

Observation d651653a-364d-4c2a-a185-7ec55bec5e08 · inbound

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation cites this paper.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Multi-LoRA Composition for Image Generation

Reference 66

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source=pdf_text observed=2026-08-10T14:25:39.383666Z digest=sha256:b0cc9feea230d42d4b95ed36729cdd5c1543b401ed9cb7f549446e439495a44f

Observation 612959a0-704f-423c-9923-f9bc51e5fe71 · inbound

Cached Multi-Lora Composition for Multi-Concept Image Generation cites this paper.

Cached Multi-Lora Composition for Multi-Concept Image Generation Multi-LoRA Composition for Image Generation

Reference 37

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source=arxiv_source observed=2026-08-08T21:03:24.064992Z digest=sha256:9a45286c6cddab7231382e36f41acd497998762a024624e27ea80f7ed4344b95

Observation ea8eef2f-1577-4dfc-a3d2-f917ed0d8973 · inbound

Skill Expansion and Composition in Parameter Space cites this paper.

Skill Expansion and Composition in Parameter Space Multi-LoRA Composition for Image Generation

Reference 2025

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source=pdf_text observed=2026-08-08T17:26:09.368041Z digest=sha256:328d9f66d201af3a1bd4760212e114d34eaa8381d5d94d0cbdb4a7facf8904a4

Observation 2b554452-5eaf-4420-b348-5ac66849495c · inbound

Distribution-Conditional Generation: From Class Distribution to Creative Generation cites this paper.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Multi-LoRA Composition for Image Generation

Reference 45

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source=pdf_text observed=2026-08-15T23:51:41.256703Z digest=sha256:aec6695105ead5ac041860403a2539c07e910724eda93203ec9858579d376453

Observation c4334150-4bf1-440d-bd6c-dc0fb0f6a2c4 · inbound

MultLFG: Training-free Multi-LoRA composition using Frequency-domain Guidance cites this paper.

MultLFG: Training-free Multi-LoRA composition using Frequency-domain Guidance Multi-LoRA Composition for Image Generation

Reference 17

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source=pdf_text observed=2026-08-07T13:58:13.537847Z digest=sha256:a84b71ec45365cff5b2a0acad1a4702207621035c74347494805fb9e1112d96f

Observation e858c169-9f28-4f67-bf7f-92c83b2fc23f · 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 Multi-LoRA Composition for Image Generation

Reference 55

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source=pdf_text observed=2026-08-06T20:46:25.179142Z digest=sha256:f70e8d43371b0077ed1515f286fd5c94f9c06ef033dc2344f2c5c526b0c929fa

Observation 8c54b8e3-2952-4ea2-9b56-d0499a1fe1b7 · inbound

QR-LoRA: Efficient and Disentangled Fine-tuning via QR Decomposition for Customized Generation cites this paper.

QR-LoRA: Efficient and Disentangled Fine-tuning via QR Decomposition for Customized Generation Multi-LoRA Composition for Image Generation

Reference 74

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source=pdf_text observed=2026-08-06T19:53:04.379364Z digest=sha256:1ae3089a047b8486824ffec3e99e24d1b57fc54ac85c1cf22f5260d5a2115631

Observation 9b140797-8531-48f6-9c87-6507995805a0 · inbound

LiON-LoRA: Rethinking LoRA Fusion to Unify Controllable Spatial and Temporal Generation for Video Diffusion cites this paper.

LiON-LoRA: Rethinking LoRA Fusion to Unify Controllable Spatial and Temporal Generation for Video Diffusion Multi-LoRA Composition for Image Generation

Reference 122

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source=pdf_text observed=2026-08-06T19:25:28.788549Z digest=sha256:deffc5d55460d674323bb5979a23414ba3e177b8dee09d925f8e7e4311447403

Observation 968617f0-e3ff-48d2-b6d0-c71411d3dc42 · inbound

LobRA: Multi-tenant Fine-tuning over Heterogeneous Data cites this paper.

LobRA: Multi-tenant Fine-tuning over Heterogeneous Data Multi-LoRA Composition for Image Generation

Reference 77

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source=pdf_text observed=2026-08-05T12:56:45.821454Z digest=sha256:3d1e5d774bc91fc5a9564d3c90ac8f5acba2e72efe7861cadf14c7b82cc18c96

Observation 532727e3-fc14-42dd-b45b-baee8ae1076b · inbound

Human Preference-Aligned Concept Customization Benchmark via Decomposed Evaluation cites this paper.

Human Preference-Aligned Concept Customization Benchmark via Decomposed Evaluation Multi-LoRA Composition for Image Generation

Reference 62

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source=pdf_text observed=2026-08-05T10:59:25.492941Z digest=sha256:fd34a3af459e73506d6dd795b71cf97005ad18c77b6c084357ddf18d4468a4fa

Observation 1740a800-b6a7-4651-add0-b4df0fac4d56 · inbound

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

PureCC: Pure Learning for Text-to-Image Concept Customization Multi-LoRA Composition for Image Generation

Reference 53

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arxiv_id, observed 2026-05-21T11:10:02.178218Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-21T11:09:15.512162Z digest=sha256:f5bbf63536dbdbdd56b084118fdb8cbce85b803dbd829aa792ea061ea489aebb

Observation 2eabcd49-9763-44d6-a9c7-1f9f12a827ac · inbound

FREE-Switch: Frequency-based Dynamic LoRA Switch for Style Transfer cites this paper.

FREE-Switch: Frequency-based Dynamic LoRA Switch for Style Transfer Multi-LoRA Composition for Image Generation

Reference 43

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arxiv_id, observed 2026-05-11T09:36:06.045685Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T15:55:16.158145Z digest=sha256:e4be9d7ebb2d948ba4c313722d6c49f98056115dafc38afeddefc7c73289ce76

Observation 67266e1b-bcda-45ae-8377-6a7230a58305 · inbound

Efficient Adversarial Training via Criticality-Aware Fine-Tuning cites this paper.

Efficient Adversarial Training via Criticality-Aware Fine-Tuning Multi-LoRA Composition for Image Generation

Reference 43

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arxiv_id, observed 2026-05-11T11:31:01.947525Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T14:49:47.131427Z digest=sha256:7bb57a477b988c75108926d95e6d1aaca5705c176a225d4e3c175d6ddb1c8693

Observation e0bcc578-1990-443d-a49f-40478c361c9f · inbound

Customization under Fire: Plugin Poisoning in Text-to-Image Ecosystem cites this paper.

Customization under Fire: Plugin Poisoning in Text-to-Image Ecosystem Multi-LoRA Composition for Image Generation

Reference 93

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arxiv_id, observed 2026-07-03T01:37:30.938785Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-27T16:25:37.031986Z digest=sha256:ec160db35e4e6c6e6c0d3e8bca51e633267491e55ef2682ce7aa14d48ff8a6f1

Observation 07a4b75e-83c5-49f5-beae-8cdf1e6f5aa3 · inbound

EmoStyle: Affective Conditioning of Style-Specialist Experts for Emotional Image Generation cites this paper.

EmoStyle: Affective Conditioning of Style-Specialist Experts for Emotional Image Generation Multi-LoRA Composition for Image Generation

Reference 93

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source=pdf_text observed=2026-07-14T13:48:36.708969Z digest=sha256:d8b4bafe0e7c92acb63a045c1e33c41cd3a0c2be035c6a33f1cb65e38626c832

Observation d091b8f9-9606-4f25-a9a3-61805ec6f31d · inbound

Staying True to the Origin: Continuous Image Stylization with Smooth Transitions cites this paper.

Staying True to the Origin: Continuous Image Stylization with Smooth Transitions Multi-LoRA Composition for Image Generation

Reference 18

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source=pdf_text observed=2026-08-12T00:26:55.129557Z digest=sha256:0c73171113483935f923a4a106ccc812710cbf07b9cbbb4be21b81230693b887