Stable Diffusion Models are Secretly Good at Visual In-Context Learning | Paper Citation Record

Observation ea0e9fe5-1447-49a4-81bf-e1c267cba23c · outbound

This paper cites Cross-image attention for zero- shot appearance transfer.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Cross-image attention for zero- shot appearance transfer

Reference 1

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Observation 4ea1ad37-8362-43e2-b517-aca312ee46cb · outbound

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

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Sequential modeling enables scalable learn- ing for large vision models

Reference 2

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Observation 0c78c0da-cb8a-450d-9ceb-40e3db54a21e · outbound

This paper cites Visual prompting via image inpaint- ing.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Visual prompting via image inpaint- ing

Reference 3

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Observation 279f86f4-f708-4a88-972a-89722b9a1430 · outbound

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

Stable Diffusion Models are Secretly Good at Visual In-Context Learning In- structpix2pix: Learning to follow image editing instructions

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:18.714494Z

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Observation 1e441169-98af-43af-926c-38ff8468b4f1 · outbound

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

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Lan- guage models are few-shot learners

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:18.540437Z

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Observation ab96f64c-7e4f-47b6-bbcb-ef99c54e959f · outbound

This paper cites Masactrl: Tuning-free mu- tual self-attention control for consistent image synthesis and editing.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Masactrl: Tuning-free mu- tual self-attention control for consistent image synthesis and editing

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:18.392573Z

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Observation 20da4964-ea57-4fca-96e3-d14d20015449 · outbound

This paper cites Palm: Scaling language modeling with pathways.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Palm: Scaling language modeling with pathways

Reference 7

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Observation a6019d4b-ae55-475a-a205-e86bb6897692 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning The cityscapes dataset for semantic urban scene understanding

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:18.005280Z

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Observation a37b9586-9823-497a-b435-ef0d4c998b6f · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning An image is worth 16x16 words: Transformers for image recognition at scale

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:17.840449Z

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Observation fe7acafe-8409-4c76-a38a-6fefa71c9c5c · outbound

This paper cites Taming transformers for high-resolution image synthesis.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Taming transformers for high-resolution image synthesis

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:17.711926Z

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Observation 92968a93-2f4c-4d58-866e-094b743fbdac · outbound

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

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Explore in-context learning for 3d point cloud understanding

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:17.523814Z

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Observation bdb00826-7da4-4ba0-9f21-afa5a1913ce3 · outbound

This paper cites Openllama: An open reproduc- tion of llama, 2023.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Openllama: An open reproduc- tion of llama, 2023

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:17.333844Z

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Observation 0a76cdf3-950e-41c2-86d4-2c52527f4881 · outbound

This paper cites Language Models are General-Purpose Interfaces.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Language Models are General-Purpose Interfaces

Reference 13

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Observation 3f09f22a-d9ee-4c88-abfb-07858b1c03c5 · outbound

This paper cites Masked autoencoders are scalable vision learners.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Masked autoencoders are scalable vision learners

Reference 14

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Observation e22ed390-084b-44ea-91cb-b7913bfe02e1 · outbound

This paper cites Unsupervised keypoints from pretrained diffusion models.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Unsupervised keypoints from pretrained diffusion models

Reference 15

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Observation e14efd6c-fdb3-4f5a-881e-5ddbcbf6248d · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:16.797606Z

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Observation 21b0b5c6-4357-4d7c-87a8-2d63a06ef7dc · outbound

This paper cites Classifier-Free Diffusion Guidance.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Classifier-Free Diffusion Guidance

Reference 17

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Observation f1032768-867f-4539-a491-87c2d55c1be7 · outbound

This paper cites Arbitrary style transfer in real-time with adaptive instance normalization.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Arbitrary style transfer in real-time with adaptive instance normalization

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:16.700582Z

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Observation 097e27bf-7126-4538-8307-7a9c084f15fc · outbound

This paper cites An edit friendly ddpm noise space: Inversion and manipulations.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning An edit friendly ddpm noise space: Inversion and manipulations

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:16.517854Z

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Observation e65fa974-f178-4267-b48a-ee822bf7af11 · outbound

This paper cites Fss-1000: A 1000-class dataset for few- shot segmentation.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Fss-1000: A 1000-class dataset for few- shot segmentation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:16.356034Z

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Observation ff2ed0fe-3963-4cfa-acfc-fb9a47cfdbb5 · outbound

This paper cites Microsoft coco: Common objects in context.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Microsoft coco: Common objects in context

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:16.187764Z

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Observation 2d64a71a-81f3-4847-83dd-4cf2f1126cd6 · outbound

This paper cites Explicit visual prompting for low-level structure segmenta- tions.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Explicit visual prompting for low-level structure segmenta- tions

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:16.037748Z

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Observation 616c6738-5689-4846-bde1-91441c31a463 · outbound

This paper cites Instaflow: One step is enough for high-quality diffusion- based text-to-image generation.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Instaflow: One step is enough for high-quality diffusion- based text-to-image generation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:15.817633Z

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Observation 49ae3865-0d90-47ca-8dd0-929f6ed843fa · outbound

This paper cites Deepfashion: Powering robust clothes recognition and retrieval with rich annotations.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Deepfashion: Powering robust clothes recognition and retrieval with rich annotations

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:15.617910Z

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Observation a7669b71-d91c-4ddb-b930-23a48fd25abb · outbound

This paper cites Localizing object-level shape variations with text-to-image diffusion models.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Localizing object-level shape variations with text-to-image diffusion models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:15.473594Z

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Observation 26bb486c-c1c8-4cf1-870b-acb41d9279cc · outbound

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

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Learning transferable visual models from natural language supervi- sion

Reference 26

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Observation 971880ba-b9bd-4a29-8caf-3a2ec646574e · outbound

This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-05T20:45:09.443522Z

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Observation 241695fd-c785-4c00-8cc9-d96f30560e88 · outbound

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

Stable Diffusion Models are Secretly Good at Visual In-Context Learning High-resolution image synthesis with latent diffusion models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:15.284617Z

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Observation d3ca2731-a12e-4c2d-8967-8821137393a8 · outbound

This paper cites Imagenet large scale visual recognition challenge.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Imagenet large scale visual recognition challenge

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:15.132089Z

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Observation fdc02c7e-29c3-4394-8e00-7d38d771fc7d · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:14.965749Z

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Observation beb072df-3064-489d-a413-a39b42bd99bb · outbound

This paper cites One-Shot Learning for Semantic Segmentation.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning One-Shot Learning for Semantic Segmentation

Reference 31

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Observation c8f21ec4-1925-4b96-8948-9823c16e68d0 · outbound

This paper cites Indoor segmentation and support inference from rgbd images.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Indoor segmentation and support inference from rgbd images

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:14.831772Z

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Observation 2347fc21-f0c2-432f-aaba-ee081af82a43 · outbound

This paper cites LaMDA: Language Models for Dialog Applications.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning LaMDA: Language Models for Dialog Applications

Reference 33

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Observation 23bf833b-62e0-4108-a269-a7dd2ae6e9c3 · outbound

This paper cites Diffuse attend and segment: Un- supervised zero-shot segmentation using stable diffusion.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Diffuse attend and segment: Un- supervised zero-shot segmentation using stable diffusion

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:14.658644Z

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Observation 923b9bb1-eafc-4abe-b358-85ada635f178 · outbound

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

Stable Diffusion Models are Secretly Good at Visual In-Context Learning LLaMA: Open and Efficient Foundation Language Models

Reference 35

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Observation cb9f60f3-d965-4aa2-bb28-8fcc1c32aabf · outbound

This paper cites Plug-and-play diffusion features for text-driven image-to-image translation.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Plug-and-play diffusion features for text-driven image-to-image translation

Reference 36

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Observation a0d20d56-4c9f-4965-a019-5c9ec8260765 · outbound

This paper cites Attention is all you need.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Attention is all you need

Reference 37

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Observation 9de3235e-7d0e-4f19-8c58-7bede78fabf1 · outbound

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

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Images speak in images: A generalist painter for in-context visual learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:14.460737Z

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Observation d6743e03-b4d1-4a9f-ad12-21eb31c0a679 · outbound

This paper cites SegGPT: Segmenting Everything In Context.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning SegGPT: Segmenting Everything In Context

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-05T20:45:10.267368Z

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Observation ea9b798f-32c4-4a78-b75e-c0e1fd9b19cb · outbound

This paper cites Skeleton-in-context: Unified skeleton sequence modeling with in-context learning.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Skeleton-in-context: Unified skeleton sequence modeling with in-context learning

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:14.185823Z

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Observation e35bfc9e-0305-4407-a16f-21226894854e · outbound

This paper cites In- context learning unlocked for diffusion models.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning In- context learning unlocked for diffusion models

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:13.929754Z

Source-reported events for the cited work

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Observation 01c703b2-bea8-4173-874e-c1ffd15056a0 · outbound

This paper cites Emergent abilities of large language models.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Emergent abilities of large language models

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:13.481069Z

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Observation baa751ca-64cb-49a5-bd05-07d8de37512f · outbound

This paper cites Holistically-nested edge de- tection.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Holistically-nested edge de- tection

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:13.288223Z

Source-reported events for the cited work

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Observation f585997b-c4f4-4bff-a58f-7d6ab1a7d75f · outbound

This paper cites IMProv: Inpainting-based Multimodal Prompting for Computer Vision Tasks.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning IMProv: Inpainting-based Multimodal Prompting for Computer Vision Tasks

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-05T20:45:10.874525Z

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Observation d8c56f9a-ba14-4fde-8add-e172b04bc932 · outbound

This paper cites Improved Distribution Matching Distillation for Fast Image Synthesis.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Improved Distribution Matching Distillation for Fast Image Synthesis

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-05T20:45:11.013444Z

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Observation 46c9168b-3274-4100-ab56-7067f4fc9e32 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning The unreasonable effectiveness of deep features as a perceptual metric

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:13.143015Z

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Observation 8a303289-20e1-4d0a-b51c-1dc3719dbed8 · outbound

This paper cites What makes good examples for visual in-context learning? Advances in Neural Information Processing Systems, 36:17773–17794,.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning What makes good examples for visual in-context learning? Advances in Neural Information Processing Systems, 36:17773–17794,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:12.966932Z

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Observation bf780141-304e-4389-9986-410db0428342 · outbound

This paper cites Semantic under- standing of scenes through the ade20k dataset.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Semantic under- standing of scenes through the ade20k dataset

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:12.841015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1a9829e6-0b1f-4825-9430-44fad156dbf2 · outbound

This paper cites To accommo- date the different spatial scales, we apply Gaussians with smaller variance for facial keypoints, which are relatively finer, and larger variance for body keypoints.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning To accommo- date the different spatial scales, we apply Gaussians with smaller variance for facial keypoints, which are relatively finer, and larger variance for body keypoints

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:12.718357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d4e52e8c-3d23-41ad-9ca7-58450e1771b1 · outbound

This paper cites We compute the LPIPS loss and the FID score [16] between the original colored image and the colorized prediction to evaluate the perceptual simi- larity.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning We compute the LPIPS loss and the FID score [16] between the original colored image and the colorized prediction to evaluate the perceptual simi- larity

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:12.512074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 405de464-d3f0-4a4b-aa9b-a4de4ef4bbe3 · outbound

This paper cites LAION5B [30]) that span annotated, unannotated, and sequence images.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning LAION5B [30]) that span annotated, unannotated, and sequence images

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:45:12.222950Z

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Observation baf02844-f133-45ce-9239-b9f829f1ea4e · outbound

This paper cites an unresolved cited work.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning Unresolved cited work

Reference 2023

Resolution: parse uncertain; raw_fallback, observed 2026-08-05T20:45:13.707769Z

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