Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation | Paper Citation Record

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This paper cites Qwen Technical Report.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Qwen Technical Report

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This paper cites Sequential modeling enables scalable learn- ing for large vision models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Sequential modeling enables scalable learn- ing for large vision models

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This paper cites eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers

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This paper cites Towards in-context scene understanding.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Towards in-context scene understanding

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This paper cites Visual prompting via image inpaint- ing.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Visual prompting via image inpaint- ing

Reference 5

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This paper cites Ledits++: Limitless image editing using text-to-image models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Ledits++: Limitless image editing using text-to-image models

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This paper cites In- structpix2pix: Learning to follow image editing instructions.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation In- structpix2pix: Learning to follow image editing instructions

Reference 7

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This paper cites Lan- guage models are few-shot learners.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Lan- guage models are few-shot learners

Reference 8

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This paper cites Enhancing diffu- sion models with text-encoder reinforcement learning.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Enhancing diffu- sion models with text-encoder reinforcement learning

Reference 9

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This paper cites Gentron: Diffusion trans- formers for image and video generation.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Gentron: Diffusion trans- formers for image and video generation

Reference 10

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This paper cites Scaling instruction- finetuned language models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Scaling instruction- finetuned language models

Reference 11

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This paper cites Diffedit: Diffusion-based semantic image editing with mask guidance.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Diffedit: Diffusion-based semantic image editing with mask guidance

Reference 12

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This paper cites Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack

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This paper cites Dreamllm: Synergistic multimodal com- prehension and creation.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Dreamllm: Synergistic multimodal com- prehension and creation

Reference 14

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This paper cites Diffusion self-guidance for control- lable image generation.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Diffusion self-guidance for control- lable image generation

Reference 15

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This paper cites Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens

Reference 16

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This paper cites PUMA: Empowering Unified MLLM with Multi-granular Visual Generation.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation PUMA: Empowering Unified MLLM with Multi-granular Visual Generation

Reference 17

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This paper cites Explore in-context learning for 3d point cloud understanding.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Explore in-context learning for 3d point cloud understanding

Reference 18

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This paper cites Making llama see and draw with seed tokenizer.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Making llama see and draw with seed tokenizer

Reference 19

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This paper cites SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 20

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This paper cites Analogist: Out-of-the-box visual in-context learning with image diffusion model.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Analogist: Out-of-the-box visual in-context learning with image diffusion model

Reference 21

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Observation 2b57f07d-d7d7-415b-80c9-3d7dcee161b4 · outbound

This paper cites Generative Visual Instruction Tuning.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Generative Visual Instruction Tuning

Reference 22

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This paper cites Prompt-to-prompt image editing with cross-attention control.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Prompt-to-prompt image editing with cross-attention control

Reference 23

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

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Lora: Low- rank adaptation of large language models

Reference 24

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This paper cites Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning

Reference 25

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This paper cites Customizing Text-to-Image Models with a Single Image Pair.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Customizing Text-to-Image Models with a Single Image Pair

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This paper cites Chameleon: A data-efficient gener- alist for dense visual prediction in the wild.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Chameleon: A data-efficient gener- alist for dense visual prediction in the wild

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This paper cites Gen- erating images with multimodal language models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Gen- erating images with multimodal language models

Reference 28

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This paper cites Lego: Learning egocentric action frame generation via visual instruction tuning.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Lego: Learning egocentric action frame generation via visual instruction tuning

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

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Blip-diffusion: pre-trained subject representation for controllable text-to- image generation and editing

Reference 30

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This paper cites Visual in-context prompting.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Visual in-context prompting

Reference 31

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Observation 6de807b2-8fa7-47a7-ab82-3ec1cfa9b05a · outbound

This paper cites Autoregressive image generation without vector quantization.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Autoregressive image generation without vector quantization

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Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Visual atribute transfer through deep image analogy

Reference 33

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This paper cites Text-driven image editing via learn- able regions.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Text-driven image editing via learn- able regions

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This paper cites Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining

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This paper cites Glid: Pre-training a generalist encoder-decoder vision model.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Glid: Pre-training a generalist encoder-decoder vision model

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Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Decoupled weight de- cay regularization

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This paper cites Unified-io 2: Scaling autoregressive multimodal models with vision language audio and action.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Unified-io 2: Scaling autoregressive multimodal models with vision language audio and action

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This paper cites STAR: Scale-wise Text-conditioned AutoRegressive image generation.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation STAR: Scale-wise Text-conditioned AutoRegressive image generation

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Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Sdedit: Guided image synthesis and editing with stochastic differential equa- tions

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This paper cites Watch your steps: Local image and scene editing by text instructions.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Watch your steps: Local image and scene editing by text instructions

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This paper cites Null-text inversion for editing real im- ages using guided diffusion models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Null-text inversion for editing real im- ages using guided diffusion models

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Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Visual instruction inversion: image editing via visual prompting

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This paper cites Swiftbrush: One-step text-to-image diffusion model with variational score distilla- tion.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Swiftbrush: One-step text-to-image diffusion model with variational score distilla- tion

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Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation In-context Learning and Induction Heads

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This paper cites Editing implicit assumptions in text-to-image diffusion models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Editing implicit assumptions in text-to-image diffusion models

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Observation c1c4d7f9-2ec4-40e2-b938-2aa0045c72af · outbound

This paper cites Effective real image editing with accelerated iter- ative diffusion inversion.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Effective real image editing with accelerated iter- ative diffusion inversion

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This paper cites Precisecontrol: En- hancing text-to-image diffusion models with fine-grained at- tribute control.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Precisecontrol: En- hancing text-to-image diffusion models with fine-grained at- tribute control

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This paper cites True few- shot learning with language models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation True few- shot learning with language models

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Observation d09ed24f-437c-4b2a-bb06-4cbe5fa00ce2 · outbound

This paper cites Sdxl: Improving latent diffusion models for high-resolution image synthesis.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Sdxl: Improving latent diffusion models for high-resolution image synthesis

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This paper cites Learning transferable visual models from natural language supervi- sion.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Learning transferable visual models from natural language supervi- sion

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This paper cites Zero-shot text-to-image generation.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Zero-shot text-to-image generation

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This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Hierarchical Text-Conditional Image Generation with CLIP Latents

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Observation 1d16b7d2-e0b5-42c5-9c07-e62aec1fb9c7 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation High-resolution image synthesis with latent diffusion models

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Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.234585Z

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Observation ed47628d-45e0-4c27-9934-2039ed92315f · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Photorealistic text-to-image diffusion models with deep language understanding

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.239163Z

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Observation b029c63b-4561-4006-9a52-1c8300393e3b · outbound

This paper cites Towards more unified in-context visual un- derstanding.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Towards more unified in-context visual un- derstanding

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:50.141887Z

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Observation bed095a8-98d4-401c-a9ea-37c7e6087eeb · outbound

This paper cites Emu edit: Precise image editing via recognition and gen- eration tasks.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Emu edit: Precise image editing via recognition and gen- eration tasks

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:50.126573Z

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Observation c5eba021-39b3-46fa-a73a-2238c59c071e · outbound

This paper cites Diffusion image analo- gies.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Diffusion image analo- gies

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:50.111422Z

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Observation cc3b2b50-102f-47c8-8c2d-aebe6a17deb0 · outbound

This paper cites Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.257448Z

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Observation 5aef0648-b7cb-447d-b6b1-6cae5e0746f9 · outbound

This paper cites Emu: Generative pretraining in multimodality.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Emu: Generative pretraining in multimodality

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:50.096723Z

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Observation dc8e0ac2-4975-4b76-8973-798f14f1054c · outbound

This paper cites Generative multimodal mod- els are in-context learners.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Generative multimodal mod- els are in-context learners

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:50.080487Z

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Observation f09ff6ce-4aba-4aa8-b7c7-a14a61329b2d · outbound

This paper cites Imagebrush: learning visual in-context instructions for exemplar-based image manipulation.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Imagebrush: learning visual in-context instructions for exemplar-based image manipulation

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:50.065599Z

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Observation 2cd2823c-4bb5-486f-8f16-e4e0ba6f4c13 · outbound

This paper cites Rethinking and improving visual prompt selection for in-context learning segmentation.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Rethinking and improving visual prompt selection for in-context learning segmentation

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:50.050054Z

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Observation 9d92ecdb-2ea9-4f87-ae6d-f81c3459b945 · outbound

This paper cites Cognitive load during problem solving: Ef- fects on learning.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Cognitive load during problem solving: Ef- fects on learning

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:50.033456Z

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Observation 1f9602eb-e4d2-4d8a-b9d5-c1c61eaac87b · outbound

This paper cites Codi-2: In-context inter- leaved and interactive any-to-any generation.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Codi-2: In-context inter- leaved and interactive any-to-any generation

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:50.017976Z

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Observation 1957869c-cf8d-4da1-b66c-63aa5d54a2cb · outbound

This paper cites Chameleon: Mixed-Modal Early-Fusion Foundation Models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.289474Z

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Observation b9d81c44-c1b1-422c-ac07-1ce507fa7d5d · outbound

This paper cites How to grow a mind: Statistics, structure, and abstraction.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation How to grow a mind: Statistics, structure, and abstraction

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:50.001965Z

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Observation 2e155071-68fc-4fc6-9c3c-0fb851ccc12d · outbound

This paper cites Visual autoregressive modeling: Scalable image gen- eration via next-scale prediction.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Visual autoregressive modeling: Scalable image gen- eration via next-scale prediction

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:49.985962Z

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Observation 7c8a8970-2b8f-4d8b-8592-aa571bb076a8 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation LLaMA: Open and Efficient Foundation Language Models

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.303712Z

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Observation b9840747-8159-45c9-b350-76927afe851f · outbound

This paper cites Edict: Exact diffusion inversion via coupled transformations.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Edict: Exact diffusion inversion via coupled transformations

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:49.970856Z

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Observation 7fb96bbf-4a92-49ee-a45e-24395db5a77a · outbound

This paper cites Explore In-Context Segmentation via Latent Diffusion Models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Explore In-Context Segmentation via Latent Diffusion Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.312831Z

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Observation c3e57cf5-eebc-4bb1-a4c6-e553d7fa561f · outbound

This paper cites Images speak in images: A generalist painter for in-context visual learning.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Images speak in images: A generalist painter for in-context visual learning

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.317769Z

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Observation 33a61fbc-7a86-473b-a7ac-a61bddb8f924 · outbound

This paper cites Seggpt: Segmenting ev- erything in context.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Seggpt: Segmenting ev- erything in context

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:49.945690Z

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Observation 2c0cfb8f-7b2a-4747-ad94-f0d3891f471d · outbound

This paper cites Emu3: Next-Token Prediction is All You Need.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Emu3: Next-Token Prediction is All You Need

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.327105Z

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Observation 3999a648-31b7-4ea8-8165-4f370addb7fd · outbound

This paper cites In-context learning unlocked for diffu- sion models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation In-context learning unlocked for diffu- sion models

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:49.929550Z

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Observation 8dd952f5-0926-4001-a046-19c665053bf9 · outbound

This paper cites The learn- ability of in-context learning.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation The learn- ability of in-context learning

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:49.912859Z

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Observation 5566c6a6-e839-49b2-853b-3f927c3c0fa1 · outbound

This paper cites OmniGen: Unified Image Generation.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation OmniGen: Unified Image Generation

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.341022Z

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Observation d7961126-1edb-46f5-88ce-2ef177b4b95b · outbound

This paper cites Show-o: One Single Transformer to Unify Multimodal Understanding and Generation.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

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Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.345818Z

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Observation 1e10c7fc-137b-467a-aea1-660224a9b7f0 · outbound

This paper cites To- wards global optimal visual in-context learning prompt se- lection.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation To- wards global optimal visual in-context learning prompt se- lection

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:49.897644Z

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Observation a35469e6-92ec-4cb9-9e69-aa868b5fec94 · outbound

This paper cites Improv: Inpainting-based multimodal prompting for computer vision tasks.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Improv: Inpainting-based multimodal prompting for computer vision tasks

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:49.882072Z

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Observation 34e43b7a-a490-4f44-87bb-17f9d9b94885 · outbound

This paper cites Prompt-free diffusion: Taking” text” out of text-to-image diffusion models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Prompt-free diffusion: Taking” text” out of text-to-image diffusion models

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:49.866525Z

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Observation d883f07f-3acf-4ee2-83ae-83f1320fcc67 · outbound

This paper cites AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling

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Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.364318Z

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Observation 409eb0b5-e82f-4c9b-91aa-d84bfe430e23 · outbound

This paper cites Magicbrush: a manually annotated dataset for instruction- guided image editing.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Magicbrush: a manually annotated dataset for instruction- guided image editing

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:49.851446Z

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Observation 9b9caa51-1566-411b-a6cb-ca3cfa8ee9af · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Adding conditional control to text-to-image diffusion models

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Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.374025Z

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Observation 338b89d5-f98c-44bf-8b3f-3f69f603271a · outbound

This paper cites What makes good examples for visual in-context learning? In Proceed- ings of the 37th International Conference on Neural Infor- mation Processing Systems, pages 17773–17794, 2023.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation What makes good examples for visual in-context learning? In Proceed- ings of the 37th International Conference on Neural Infor- mation Processing Systems, pages 17773–17794, 2023

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:49.825502Z

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Observation cc003e2c-a4eb-4b79-81de-68521e201cc2 · outbound

This paper cites InstructBrush: Learning Attention-based Instruction Optimization for Image Editing.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation InstructBrush: Learning Attention-based Instruction Optimization for Image Editing

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Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.383104Z

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Observation 6e70062c-9bd1-4171-859c-82d4f202e702 · outbound

This paper cites Calibrate before use: Improving few-shot perfor- mance of language models.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Calibrate before use: Improving few-shot perfor- mance of language models

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:49.809961Z

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Observation af8c770f-4c1f-4ab4-9229-7a16fef69820 · outbound

This paper cites Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-12T04:50:49.392554Z

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Observation 63076f3f-b888-4aae-8263-6352e5166f4c · outbound

This paper cites As a baseline of text-guided image editing model, InstructPix2Pix is trained only with textual instructions.

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation As a baseline of text-guided image editing model, InstructPix2Pix is trained only with textual instructions

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:50:49.793577Z

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