Paper Citation Record · LEDGER

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models

As of 21 August 2026, this Paper Citation Record lists 93 of 93 outbound references and 4 inbound Pith citation observations for arXiv:2412.01824.

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

pith.paper-citation-record.v1
2412.01824 v2

Coverage vector

measured 93 of 93 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:56:59.808319Z

measured 97 of 97 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:30:21.554689Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T15:19:51.779596Z

Reference resolution

93 of 93 outbound references displayed

verified exact0
verified fuzzy23
unresolved70
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5bfa5040-9f0b-4ece-bcaa-65e0cd1f737a · outbound

This paper cites PaLM 2 Technical Report.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models PaLM 2 Technical Report

Reference 1

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Observation 29acbec3-e92a-49f9-b0cc-fa34529d2034 · outbound

This paper cites OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.516791Z

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Observation c6312d3f-0ed7-427b-b6ab-345fe88efaa6 · outbound

This paper cites Es- timating and exploiting the aleatoric uncertainty in surface normal estimation.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Es- timating and exploiting the aleatoric uncertainty in surface normal estimation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.520501Z

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Observation 9911dee2-13bb-4aae-bc9c-2aa0d6548acf · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Sequential modeling enables scalable learn- ing for large vision models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.523819Z

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Observation b4546b04-90ea-46b6-9bb2-ef7a93e0f190 · outbound

This paper cites Visual prompting via image inpaint- ing.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Visual prompting via image inpaint- ing

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.527244Z

Source-reported events for the cited work

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Observation b7977445-e071-441d-9a4b-87c27b80b4d4 · outbound

This paper cites Improving image generation with better captions.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Improving image generation with better captions

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.530640Z

Source-reported events for the cited work

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Observation 255aa901-836c-4acc-a5bb-1f5093ac596b · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models In- structpix2pix: Learning to follow image editing instructions

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.533835Z

Source-reported events for the cited work

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Observation 554dec18-e5ac-483d-a105-35f235895d7e · outbound

This paper cites ByTheWay: Boost Your Text-to-Video Generation Model to Higher Quality in a Training-free Way.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models ByTheWay: Boost Your Text-to-Video Generation Model to Higher Quality in a Training-free Way

Reference 10

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Observation 8204d8d1-e1bd-460a-9f34-aeecde2685fd · outbound

This paper cites Learning photographic global tonal adjustment with a database of input / output image pairs.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Learning photographic global tonal adjustment with a database of input / output image pairs

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.546965Z

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Observation 9eaec335-1ec1-4f0c-8bd6-1c0d0a55ee68 · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Emerg- ing properties in self-supervised vision transformers

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.549903Z

Source-reported events for the cited work

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Observation 2138bdf9-57e4-4c73-a5cc-b739ccfd801a · outbound

This paper cites Masked-attention mask 9 transformer for universal image segmentation.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Masked-attention mask 9 transformer for universal image segmentation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.552932Z

Source-reported events for the cited work

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Observation 95668963-d6b0-426b-a6e4-f0e74ed8ca31 · outbound

This paper cites Shazeer, Vinodkumar Prab- hakaran, Emily Reif, Nan Du, Benton C.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Shazeer, Vinodkumar Prab- hakaran, Emily Reif, Nan Du, Benton C

Reference 14

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Source-reported events for the cited work

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Observation 4b10193d-ce38-4e8b-bc29-bc3a35456da4 · outbound

This paper cites Instruc- tir: High-quality image restoration following human instruc- tions.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Instruc- tir: High-quality image restoration following human instruc- tions

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.558459Z

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Observation af2b56f9-ff1f-4a6a-9cd2-5d273410e54b · outbound

This paper cites DreamLLM: Synergistic Multimodal Comprehension and Creation.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models DreamLLM: Synergistic Multimodal Comprehension and Creation

Reference 16

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Observation 047321ff-fb17-471c-b628-6501bf540668 · outbound

This paper cites Internlm-xcomposer2: Mastering free-form text- image composition and comprehension in vision-language large model, 2024.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Internlm-xcomposer2: Mastering free-form text- image composition and comprehension in vision-language large model, 2024

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.564386Z

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Observation fb85be1a-ee18-42be-b289-08f4d43408ad · outbound

This paper cites The Llama 3 Herd of Models.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models The Llama 3 Herd of Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.567054Z

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Observation 55972e13-63d9-49c8-8a72-2fc5aebd8ef9 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Taming transformers for high-resolution image synthesis

Reference 19

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Source-reported events for the cited work

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Observation 3c4beb1c-4411-43cb-82ef-13fa678862bb · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.572607Z

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Observation 9ccd74bd-8563-46fa-abff-8de2b8706926 · outbound

This paper cites Removing rain from single images via a deep detail network.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Removing rain from single images via a deep detail network

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.556021Z

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Observation f241de02-5408-4dac-8cb2-69f89fa3e553 · outbound

This paper cites InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists

Reference 22

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Observation 2a352133-5948-4b17-8b7c-4bd3dd3493a4 · outbound

This paper cites Making LLaMA SEE and Draw with SEED Tokenizer.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Making LLaMA SEE and Draw with SEED Tokenizer

Reference 23

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Source-reported events for the cited work

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Observation e58e58aa-8a1c-4340-80b9-ebb31f09af18 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 24

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Observation b37ea80f-5399-499b-af47-4730d32667f6 · outbound

This paper cites Instructdiffusion: A generalist modeling inter- face for vision tasks.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Instructdiffusion: A generalist modeling inter- face for vision tasks

Reference 25

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Observation 1a13b393-9199-4a9e-9339-b6194817a20d · outbound

This paper cites Geneval: An object-focused framework for evaluating text- to-image alignment.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Geneval: An object-focused framework for evaluating text- to-image alignment

Reference 26

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Observation 15daa145-782f-4ccc-912b-ce5b9d7e1597 · outbound

This paper cites FreeEdit: Mask-free Reference-based Image Editing with Multi-modal Instruction.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models FreeEdit: Mask-free Reference-based Image Editing with Multi-modal Instruction

Reference 27

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Observation c23aa687-ef92-47a1-a152-162285a5093a · outbound

This paper cites Denoising dif- fusion probabilistic models.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Denoising dif- fusion probabilistic models

Reference 28

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Source-reported events for the cited work

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Observation bedcf773-588e-41fa-9e76-dad461967606 · outbound

This paper cites Training Compute-Optimal Large Language Models.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Training Compute-Optimal Large Language Models

Reference 29

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Observation 874e5f9d-2eff-4ffd-9b1c-7bc2eaa1a9ea · outbound

This paper cites Deciphering Cross-Modal Alignment in Large Vision-Language Models with Modality Integration Rate.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Deciphering Cross-Modal Alignment in Large Vision-Language Models with Modality Integration Rate

Reference 30

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Observation 199e7cce-eab5-458b-8b02-b0795708f5bb · outbound

This paper cites Smartedit: Exploring complex instruction-based image editing with multimodal large lan- guage models.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Smartedit: Exploring complex instruction-based image editing with multimodal large lan- guage models

Reference 31

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Observation f26e6c39-a4f8-450d-bcb3-123e9c2a254c · outbound

This paper cites Repurpos- 10 ing diffusion-based image generators for monocular depth estimation.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Repurpos- 10 ing diffusion-based image generators for monocular depth estimation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.512163Z

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Observation c22d2bdd-3c91-45be-94e4-0ff28e766f5b · outbound

This paper cites Auto-Encoding Variational Bayes.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Auto-Encoding Variational Bayes

Reference 33

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This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Retrieval-augmented generation for knowledge-intensive nlp tasks

Reference 34

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Observation 0aa70367-b215-4d66-907c-a89e72fe9042 · outbound

This paper cites All-in-one image restoration for unknown corruption.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models All-in-one image restoration for unknown corruption

Reference 35

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Observation 85f473ed-78fd-4ebd-89e7-ef3849560b0b · outbound

This paper cites Mask dino: Towards a unified transformer-based framework for object detection and segmentation.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Mask dino: Towards a unified transformer-based framework for object detection and segmentation

Reference 36

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Observation 9e2cacb5-52b9-4fd8-8c1e-3c07c138f222 · outbound

This paper cites BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

Reference 37

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Observation 832c8996-a5a4-4d51-954e-2590435a78e5 · outbound

This paper cites ImageFolder: Autoregressive Image Generation with Folded Tokens.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models ImageFolder: Autoregressive Image Generation with Folded Tokens

Reference 38

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Observation 68ace587-682e-44a5-a454-747b1d399901 · outbound

This paper cites MotionClone: Training-Free Motion Cloning for Controllable Video Generation.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models MotionClone: Training-Free Motion Cloning for Controllable Video Generation

Reference 39

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Observation 142d523d-929d-47ef-826e-9084208b1384 · outbound

This paper cites Playground v3: Improving Text-to-Image Alignment with Deep-Fusion Large Language Models.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Playground v3: Improving Text-to-Image Alignment with Deep-Fusion Large Language Models

Reference 40

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Observation 31cde6aa-6ae1-4f83-842c-bddaf0fc6804 · outbound

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X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining

Reference 41

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Observation 27cab28d-099d-4893-b962-9a205a7dd291 · outbound

This paper cites MIA-DPO: Multi-Image Augmented Direct Preference Optimization For Large Vision-Language Models.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models MIA-DPO: Multi-Image Augmented Direct Preference Optimization For Large Vision-Language Models

Reference 42

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Observation 9cae051f-4df6-42f4-9088-051fc050bfbc · outbound

This paper cites Unified-io: A unified model for vision, language, and multi-modal tasks.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Unified-io: A unified model for vision, language, and multi-modal tasks

Reference 43

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Observation 74a0d82e-affe-4917-bb1d-b664d0bb0b0d · outbound

This paper cites Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation

Reference 44

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Observation 72ccaa16-a94b-40fc-bba6-6c2f5feba1b0 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models STAR: Scale-wise Text-conditioned AutoRegressive image generation

Reference 45

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Observation 9a93f306-e501-44c1-b6e1-5fa294a51bc7 · outbound

This paper cites Language Models are Few-Shot Learners.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Language Models are Few-Shot Learners

Reference 46

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Source-reported events for the cited work

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Observation 0e111547-fa6e-4197-9f10-66514e4e1ca3 · outbound

This paper cites Deep multi-scale convolutional neural network for dynamic scene deblurring.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Deep multi-scale convolutional neural network for dynamic scene deblurring

Reference 47

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Observation 863c6666-5de0-4b5f-877f-0322900e14f9 · outbound

This paper cites Gpt-4v(ision) system card.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Gpt-4v(ision) system card

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.462746Z

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Observation bb949fb4-704a-4199-8623-9cc2676b8c11 · outbound

This paper cites Gpt-4 technical report.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Gpt-4 technical report

Reference 49

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Observation 84848d12-4ae2-42a0-a72b-bee436e31a94 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 50

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This paper cites GPT4Point: A Unified Framework for Point-Language Understanding and Generation.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models GPT4Point: A Unified Framework for Point-Language Understanding and Generation

Reference 51

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Source-reported events for the cited work

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Observation e900c64a-1e02-4a64-bb5f-e2161ff8546b · outbound

This paper cites Gpt4point: A unified framework for point-language understanding and generation.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Gpt4point: A unified framework for point-language understanding and generation

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.444084Z

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Observation 825ef939-0a58-405d-a155-b340ced7a3f6 · outbound

This paper cites Tailor3D: Customized 3D Assets Editing and Generation with Dual-Side Images.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Tailor3D: Customized 3D Assets Editing and Generation with Dual-Side Images

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.678101Z

Source-reported events for the cited work

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Observation b7085699-5954-413c-8325-55e90c03c51a · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Learning transferable visual models from natural language supervi- sion

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.434621Z

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Observation ed437bf1-73e5-430a-8284-32d7eb7f78fd · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Zero-shot text-to-image generation

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.684841Z

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Observation ec5a1d25-08c5-48fb-983e-22c7894a4cf3 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.688002Z

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Observation c68f39c7-933f-4d12-9f9b-769b79b13b48 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models High-resolution image synthesis with latent diffusion models

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.419092Z

Source-reported events for the cited work

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Observation 439ee319-2672-4f02-b6b5-4b13a4cc4248 · outbound

This paper cites RB-Modulation: Training-Free Personalization of Diffusion Models using Stochastic Optimal Control.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models RB-Modulation: Training-Free Personalization of Diffusion Models using Stochastic Optimal Control

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.694280Z

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Observation 23fd0597-9589-4072-b0e0-1ef186d965e6 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.408917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 64de6525-48f6-41dc-9372-75aad7c53018 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Emu edit: Precise image editing via recognition and gen- eration tasks

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.398101Z

Source-reported events for the cited work

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Observation 41b9e1fd-bb7d-4783-9013-699820ed19c1 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Indoor segmentation and support inference from rgbd images

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.389297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e5966f0a-97fd-4a77-8b17-6ce0b66c6bf6 · outbound

This paper cites Denoising Diffusion Implicit Models.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Denoising Diffusion Implicit Models

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.705352Z

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Observation 679f3e18-3360-425a-9b0a-40f73e19dc24 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.708401Z

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Observation a4ffc111-bdf7-48c4-a07d-c2be88e849c3 · outbound

This paper cites Emu: Generative pretraining in multimodality.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Emu: Generative pretraining in multimodality

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.711162Z

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Observation 2b766934-8a3b-40db-89c4-4453644f1d31 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Generative multimodal mod- els are in-context learners

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.713917Z

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Observation 6133a99f-cd74-409a-b854-bfeed499aab6 · outbound

This paper cites Alpha- clip: A clip model focusing on wherever you want, 2023.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Alpha- clip: A clip model focusing on wherever you want, 2023

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.370352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation af1355ad-b7f9-47f8-87dd-2d990dd38077 · outbound

This paper cites HART: Efficient Visual Generation with Hybrid Autoregressive Transformer.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models HART: Efficient Visual Generation with Hybrid Autoregressive Transformer

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.719288Z

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Observation 46b6ba75-12ef-4c79-820a-e2486ba25db7 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.722132Z

Source-reported events for the cited work

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Observation fb423553-6403-4e51-b4e3-d974705d62cf · outbound

This paper cites Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.725425Z

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Observation c6bd74ac-59e0-45c6-8a01-ff96dcad33fb · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models LLaMA: Open and Efficient Foundation Language Models

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.728864Z

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Observation e233f119-89dc-4dd4-a4f2-78ee6f39916a · outbound

This paper cites Neural discrete representation learning.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Neural discrete representation learning

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.732778Z

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Observation bcedd024-df6f-4a0c-aa2b-fa7f9767d2e6 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.736081Z

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Observation c4b1cc3b-203c-4213-8471-e3764113e26d · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Images speak in images: A generalist painter for in-context visual learning

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.356301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3b5255e3-d242-4e42-ac82-a20abc71799d · outbound

This paper cites SegGPT: Segmenting Everything In Context.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models SegGPT: Segmenting Everything In Context

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.742838Z

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Observation 9558197c-75cd-41c3-a606-b08d4cdbee71 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Emu3: Next-Token Prediction is All You Need

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.746232Z

Source-reported events for the cited work

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Observation 75b4d6ec-fd1c-442b-95de-ce81cc6197ba · outbound

This paper cites Deep Retinex Decomposition for Low-Light Enhancement.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Deep Retinex Decomposition for Low-Light Enhancement

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.750151Z

Source-reported events for the cited work

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Observation 34c5a393-e22f-4037-ac96-b40136512a9a · outbound

This paper cites Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.753498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70807277-4dcf-418b-af70-11f113fbdd21 · outbound

This paper cites NExT-GPT: Any-to-Any Multimodal LLM.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models NExT-GPT: Any-to-Any Multimodal LLM

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.756955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52c3278d-7f0a-419e-8630-568d51058738 · outbound

This paper cites VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.760360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f71053a-6c9e-4994-bd71-8f1cd7587618 · outbound

This paper cites OmniGen: Unified Image Generation.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models OmniGen: Unified Image Generation

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.763167Z

Source-reported events for the cited work

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Observation 1fb8cc4e-b2e6-4657-bb56-9a2b6144c798 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.766390Z

Source-reported events for the cited work

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Observation f0f3ddc0-aaab-4290-9511-f751322438fa · outbound

This paper cites PyramidDrop: Accelerating Your Large Vision-Language Models via Pyramid Visual Redundancy Reduction.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models PyramidDrop: Accelerating Your Large Vision-Language Models via Pyramid Visual Redundancy Reduction

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.769394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79a5fc81-a78f-4cd0-919a-e74d5ae98d2c · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Depth anything: Unleashing the power of large-scale unlabeled data

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.772416Z

Source-reported events for the cited work

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Observation c03bbacd-17d7-4f0b-a5a7-023eb186eb85 · outbound

This paper cites LayerPano3D: Layered 3D Panorama for Hyper-Immersive Scene Generation.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models LayerPano3D: Layered 3D Panorama for Hyper-Immersive Scene Generation

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.774838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b5763c5-0701-45f2-b971-f0d2af69017a · outbound

This paper cites Deep joint rain detection and removal from a single image.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Deep joint rain detection and removal from a single image

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.341899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 46906c86-bcfd-4deb-b086-409d8db8df58 · outbound

This paper cites Inverted pyramid multi-task trans- former for dense scene understanding.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Inverted pyramid multi-task trans- former for dense scene understanding

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.332943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0d4f2d3c-152a-4334-83b2-7a10cbbabb39 · outbound

This paper cites IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.783126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbc6f3a2-9a93-4714-9cd9-11aeb2765524 · outbound

This paper cites Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.785833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d50d04c-4829-421e-a1f5-fbfcd7359f6d · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Magicbrush: A manually annotated dataset for instruction- guided image editing

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.323390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4052ce3d-8bad-4811-9379-49d31fa50f94 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Adding conditional control to text-to-image diffusion models

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.792082Z

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Observation d91d5ab1-9ccd-4d7d-9f55-7832c2d40ba3 · outbound

This paper cites Internlm-xcomposer: A vision-language large model for ad- vanced text-image comprehension and composition, 2023.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Internlm-xcomposer: A vision-language large model for ad- vanced text-image comprehension and composition, 2023

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:57:00.307195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 032a2303-6d34-4de3-9c41-6cd1f5d933b1 · outbound

This paper cites VAR-CLIP: Text-to-Image Generator with Visual Auto-Regressive Modeling.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models VAR-CLIP: Text-to-Image Generator with Visual Auto-Regressive Modeling

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.798606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d3d874a-6126-4c04-859a-4692e5ef9177 · outbound

This paper cites UltraEdit: Instruction-based Fine-Grained Image Editing at Scale.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models UltraEdit: Instruction-based Fine-Grained Image Editing at Scale

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.801968Z

Source-reported events for the cited work

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Observation 8b51fed7-f510-4b7d-afc0-9beec1bd5c25 · outbound

This paper cites Scene parsing through ade20k dataset.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Scene parsing through ade20k dataset

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.805205Z

Source-reported events for the cited work

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Observation 11cc75af-ed41-433b-b5bb-1077f47aa075 · outbound

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

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.808319Z

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Pith citing papers

Observation 03e39ec1-c5dc-4dcb-a655-5aad110f1693 · inbound

ScaleCap: Inference-Time Scalable Image Captioning via Dual-Modality Debiasing cites this paper.

ScaleCap: Inference-Time Scalable Image Captioning via Dual-Modality Debiasing X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T18:30:21.554689Z

Source-reported events for the cited work

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Observation 84696db2-b6ed-48cf-9186-844744fabb5a · inbound

CODA: Coordinating the Cerebrum and Cerebellum for a Dual-Brain Computer Use Agent with Decoupled Reinforcement Learning cites this paper.

CODA: Coordinating the Cerebrum and Cerebellum for a Dual-Brain Computer Use Agent with Decoupled Reinforcement Learning X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-05T15:19:51.797076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bf4091d7-c1f8-4a74-b56b-357c74f87fa0 · inbound

T2T-VICL: Cross-Task Visual In-Context Learning via Implicit Text-Driven VLMs cites this paper.

T2T-VICL: Cross-Task Visual In-Context Learning via Implicit Text-Driven VLMs X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T21:15:46.208071Z

Source-reported events for the cited work

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Observation 1dbba8e2-49a4-4769-8392-bf3f0ab74947 · inbound

UniGen-AR: Unifying Visual Generation with Auto-Regressive Modeling cites this paper.

UniGen-AR: Unifying Visual Generation with Auto-Regressive Modeling X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models

Reference 65

Resolution: unresolved; no resolver link, observed 2026-07-31T22:25:12.450878Z

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Unavailable: canonical work link unavailable.