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Paper Citation Record · LEDGER

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget

As of 22 August 2026, this Paper Citation Record lists 100 of 153 outbound references and 0 inbound Pith citation observations for arXiv:2607.13125.

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

pith.paper-citation-record.v1
2607.13125 v2

Coverage vector

measured 100 of 153 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T06:14:01.543829Z

measured 100 of 100 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

100 of 153 outbound references displayed

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Outbound references

Observation f75c1e18-ec9d-4f06-ab7e-dc6961f8df88 · outbound

This paper cites an unresolved cited work.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Unresolved cited work

Reference 1

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Observation 065d2d06-4f77-4ec1-8a6a-fe423e7d5973 · outbound

This paper cites Ideogram 4.https://ideogram.ai/blog/ideogram-4.0/, 2026.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Ideogram 4.https://ideogram.ai/blog/ideogram-4.0/, 2026

Reference 2

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Observation f66f1c88-641b-4614-804a-da07dbc6fbbd · outbound

This paper cites Qwen3-VL Technical Report.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Qwen3-VL Technical Report

Reference 3

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Observation d6279725-3635-44cd-b614-f2ffb0af2c73 · outbound

This paper cites Qwen2.5-VL Technical Report.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Qwen2.5-VL Technical Report

Reference 4

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source=pdf_text observed=2026-08-02T06:13:49.323044Z digest=sha256:3eb3caf13c8a46a30a605cd3498f984015a49efee45398d82b8dbb1d3f295d56

Observation ddd8f2fc-b920-4a3b-841b-74fe98cb43bc · outbound

This paper cites Beyond the imitation game: Quantifying and extrapolating the capabilities of language models.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Beyond the imitation game: Quantifying and extrapolating the capabilities of language models

Reference 5

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source=pdf_text observed=2026-08-02T06:13:49.431087Z digest=sha256:7d35ddb6eba20320144e470489b7f055c7e9dfadb3e025f29e73380c2d780ac7

Observation 3c57dcef-d81b-4db0-a15b-9dde2a0865c7 · outbound

This paper cites Improving image generation with better captions.Computer Science.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Improving image generation with better captions.Computer Science

Reference 6

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Observation 9611a8b6-6332-4c86-beb7-2acd03074d41 · outbound

This paper cites Announcing Black Forest Labs: Black forest labs’ inaugural model suite, FLUX.1, 2024.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Announcing Black Forest Labs: Black forest labs’ inaugural model suite, FLUX.1, 2024

Reference 7

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source=pdf_text observed=2026-08-02T06:13:49.618977Z digest=sha256:663629c6cd0d7bd2277ead8108b2823073b3d311f45a043d3ee4477abf2aade5

Observation 61d5e663-1719-497a-814f-f647ae23e963 · outbound

This paper cites FLUX.2: Analyzing and enhancing the latent space of FLUX – representation comparison, 11.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget FLUX.2: Analyzing and enhancing the latent space of FLUX – representation comparison, 11

Reference 8

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Observation 03749cc6-d98c-453d-9b5a-f950fe6a3ed2 · outbound

This paper cites Flux.2: Production-grade ai image generation and editing model with 4mp photorealistic output and multi-reference control.https://bfl.ai/models/flux-2, 2025.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Flux.2: Production-grade ai image generation and editing model with 4mp photorealistic output and multi-reference control.https://bfl.ai/models/flux-2, 2025

Reference 9

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source=pdf_text observed=2026-08-02T06:13:49.859041Z digest=sha256:6e682904e6750d0d9256d7c19ea82d3cf82a8f2d8ae7b8ca2b71bfb511d98121

Observation c12ec047-d7e2-400a-91c8-460d904a884a · outbound

This paper cites Large scale GAN training for high fidelity natural image synthesis.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Large scale GAN training for high fidelity natural image synthesis

Reference 10

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Observation 259a7151-5308-4b2f-a9b8-a1119afb0c65 · outbound

This paper cites Instructpix2pix: Learning to follow image editing instructions.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Instructpix2pix: Learning to follow image editing instructions

Reference 11

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Observation e0a0416a-cfc7-4528-9f55-5356a84cde8e · outbound

This paper cites Video generation models as world simulators.OpenAI Blog, 1(8):1, 2024.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Video generation models as world simulators.OpenAI Blog, 1(8):1, 2024

Reference 12

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Observation 99c4ee04-a9e4-4be9-8fb1-85f47340b849 · outbound

This paper cites Coyo-700m: Image-text pair dataset.https://github.com/kakaobrain/coyo-dataset, 2022.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Coyo-700m: Image-text pair dataset.https://github.com/kakaobrain/coyo-dataset, 2022

Reference 13

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Observation 6f85faa0-662d-440b-a022-9a3e63747382 · outbound

This paper cites Seedream 4.5.https://seed.bytedance.com/en/seedream4_5, 2026.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Seedream 4.5.https://seed.bytedance.com/en/seedream4_5, 2026

Reference 14

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Observation ed3d5552-d504-4b08-a4da-8bbc71c5212c · outbound

This paper cites Seedream 5.0 lite.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Seedream 5.0 lite

Reference 15

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Observation cefddff5-b290-4d9e-8837-d75c549dc05b · outbound

This paper cites MM-IQ: Benchmarking Human-Like Abstraction and Reasoning in Multimodal Models.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget MM-IQ: Benchmarking Human-Like Abstraction and Reasoning in Multimodal Models

Reference 16

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Observation 7c448b51-6336-4511-b2b3-f0c670e2ca42 · outbound

This paper cites HiDream-O1-Image: A Natively Unified Image Generative Foundation Model with Pixel-level Unified Transformer.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget HiDream-O1-Image: A Natively Unified Image Generative Foundation Model with Pixel-level Unified Transformer

Reference 17

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Observation a42ccb62-a100-4276-961d-6d0d03c56213 · outbound

This paper cites Rwku: Benchmarking real-world knowledge unlearning for large language models.Advances in Neural Information Processing Systems, 37:98213–98263, 2024.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Rwku: Benchmarking real-world knowledge unlearning for large language models.Advances in Neural Information Processing Systems, 37:98213–98263, 2024

Reference 18

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Observation 5aee7ec5-5670-4a14-b0a5-a9fcb9744b44 · outbound

This paper cites HunyuanImage 3.0 Technical Report.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget HunyuanImage 3.0 Technical Report

Reference 19

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Observation a2a6725d-6fd7-401e-916e-f6262fe876d3 · outbound

This paper cites Extracting training data from diffusion models.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Extracting training data from diffusion models

Reference 20

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Observation 3bf47c79-a902-40c7-92ea-b1dd3384aabc · outbound

This paper cites OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 21

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Observation d4191802-51cd-4ca5-ac6c-34fa639ee628 · outbound

This paper cites Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models

Reference 22

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Observation 4b36701e-60ab-408f-a654-6e94ec38b917 · outbound

This paper cites Blip3o-next: Next frontier of native image generation, 2025.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Blip3o-next: Next frontier of native image generation, 2025

Reference 23

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Observation d49977c3-4e02-4670-b68d-364df23ed756 · outbound

This paper cites Pixart-α: Fast training of diffusion transformer for photorealistic text-to-image synthesis, 2023.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Pixart-α: Fast training of diffusion transformer for photorealistic text-to-image synthesis, 2023

Reference 24

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Observation c59c1604-3f3b-48b8-bef3-ab44679c43ce · outbound

This paper cites FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance

Reference 25

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Observation 952dcbcc-11d6-43be-9c07-e2150bda43a4 · outbound

This paper cites Reproducible vision-language models meet concepts out of pre-training.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Reproducible vision-language models meet concepts out of pre-training

Reference 26

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Observation dd3526ca-0a1e-4eee-b8d0-58b95ee8ab21 · outbound

This paper cites Goodhart’s law: its origins, meaning and implications for monetary policy.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Goodhart’s law: its origins, meaning and implications for monetary policy

Reference 28

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Observation 8b276d22-9aae-4f4b-be51-1e40b1709dbc · outbound

This paper cites an unresolved cited work.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Unresolved cited work

Reference 29

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Observation e4f25783-9c20-43f0-a952-ea8be02f38a1 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Imagenet: A large-scale hierarchical image database

Reference 30

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Observation 9668749d-7893-4550-80df-9e71c46e7be8 · outbound

This paper cites Hybrid llm: Cost-efficient and quality-aware query routing.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Hybrid llm: Cost-efficient and quality-aware query routing

Reference 31

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Observation f1c75388-1fe6-4243-a469-feb3e14a3d2a · outbound

This paper cites Cogview: Mastering text-to-image generation via transformers.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Cogview: Mastering text-to-image generation via transformers

Reference 32

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source=pdf_text observed=2026-08-02T06:13:52.185978Z digest=sha256:683d72f1d3db4f5a6c193274a9728b1b3fc27a8a37d05daf114c5c0a6e41f26b

Observation a81afdfe-8446-4173-a854-b51bb36ae8c9 · outbound

This paper cites Documenting large webtext corpora: A case study on the colossal clean crawled corpus.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Documenting large webtext corpora: A case study on the colossal clean crawled corpus

Reference 33

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source=pdf_text observed=2026-08-02T06:13:52.395448Z digest=sha256:600a0ebebdf7727a5712818cf9980bbe5d16b3c54b5afe9bc920aab47cbd3317

Observation a1e1ba21-7528-4e4b-8fa3-7c14c9e620a0 · outbound

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

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget An image is worth 16x16 words: Transformers for image recognition at scale

Reference 34

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source=pdf_text observed=2026-08-02T06:13:52.549079Z digest=sha256:50234e2c0e41a83e0f116dfed73a5b7230f470d67362f0279971009169b095e9

Observation 9606e237-a814-4b09-8a07-698dee244933 · outbound

This paper cites Textcrafter: Accurately rendering multiple texts in complex visual scenes.arXiv e-prints, pp.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Textcrafter: Accurately rendering multiple texts in complex visual scenes.arXiv e-prints, pp

Reference 35

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source=pdf_text observed=2026-08-02T06:13:52.717401Z digest=sha256:a247cfa5ccae5476a10eb3fcdfebef4e2b9faba730c9d92412fe94bd65578e4c

Observation eb3ac4d6-4572-4aad-9c0d-d31a18d29836 · outbound

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

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Scaling rectified flow transformers for high-resolution image synthesis

Reference 36

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source=pdf_text observed=2026-08-02T06:13:52.935384Z digest=sha256:e2a4dd2f4b13bd382c960bd90a57e571c42f7693cbff270b54248de6f9160820

Observation 35f9d990-4c6a-49a0-9f5d-7abb0d80db35 · outbound

This paper cites Datacomp: in search of the next generation of multimodal datasets.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Datacomp: in search of the next generation of multimodal datasets

Reference 37

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source=pdf_text observed=2026-08-02T06:13:53.093874Z digest=sha256:3551915f67f96f6e384578f08dc19da8158bfdb671776951d1c01ce98e56a675

Observation 441d8842-abf2-4b2e-b24e-2ceda306f8eb · outbound

This paper cites Lumina-t2x: Scalable flow-based large diffusion transformer for flexible resolution generation.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Lumina-t2x: Scalable flow-based large diffusion transformer for flexible resolution generation

Reference 38

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source=pdf_text observed=2026-08-02T06:13:53.237730Z digest=sha256:7c9e5ba7655c575bfc946c5b37a2be0cadcf7094a3d1d7e62658110245fbea32

Observation 5948e747-8f67-4ebe-a978-db60ae430be2 · outbound

This paper cites Seedream 3.0 Technical Report.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Seedream 3.0 Technical Report

Reference 39

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source=pdf_text observed=2026-08-02T06:13:53.357375Z digest=sha256:f5ca1eedad79c760fa78a5cc30bb16bb06cddbdff5e0da21edca5e09465218de

Observation 0fd5c2fa-7c15-40e5-ac09-b960fb9dcfdf · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 40

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source=pdf_text observed=2026-08-02T06:13:53.538640Z digest=sha256:f4015cd0f9af3c810fcf62ec45ad57eee78494a3a535bef67579c02116a72223

Observation 6846bb73-e826-47d3-aef9-238850771d3f · outbound

This paper cites X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again

Reference 41

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source=pdf_text observed=2026-08-02T06:13:53.626677Z digest=sha256:0f92a2835602eeb09601030217f4d9dec5546395278a7fc2776b386c179239b6

Observation 3299e691-b71e-4362-8e9e-05ac4c7afadc · outbound

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

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Geneval: An object-focused framework for evaluating text-to-image alignment

Reference 42

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source=pdf_text observed=2026-08-02T06:13:53.811494Z digest=sha256:31eda23dd6be465874d4876d2d06faef28059152db2908749d688c09769c9655

Observation 037969cb-5179-4c2a-9d3b-4d568d23cc26 · outbound

This paper cites Introducing nano banana pro, 2025.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Introducing nano banana pro, 2025

Reference 43

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source=pdf_text observed=2026-08-02T06:13:53.939798Z digest=sha256:401426f196c076787a0624a6dad7cb3988e691a819460b004c59683513fdd037

Observation 86cdf8b5-a645-447e-8f03-9f2d788890bb · outbound

This paper cites Nano banana 2: Combining pro capabilities with lightning-fast speed, 2026.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Nano banana 2: Combining pro capabilities with lightning-fast speed, 2026

Reference 44

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source=pdf_text observed=2026-08-02T06:13:54.024324Z digest=sha256:5a44df901acbfac9bc43cec541484181dc5bd862c041e9b3aebd699bef04a36c

Observation 60074872-590c-4bc9-aa47-475b28202597 · outbound

This paper cites Imagen 4.0.https://deepmind.google/models/imagen/, 2025.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Imagen 4.0.https://deepmind.google/models/imagen/, 2025

Reference 45

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source=pdf_text observed=2026-08-02T06:13:54.112612Z digest=sha256:cdff69b2eb510d382419130d34d56691f91128b0ce1f41f15d4c1fd19cd4c248

Observation 1628e578-8f84-4ed2-8f22-3428b1471b38 · outbound

This paper cites Gemini 3.1 pro - model card.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Gemini 3.1 pro - model card

Reference 46

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source=pdf_text observed=2026-08-02T06:13:54.291212Z digest=sha256:06ebeca2cd7858e152c3c088c1a0101d9b51000364260691e75e294a06ab1e05

Observation 044b0aa2-d269-4c75-847a-50cd569693b9 · outbound

This paper cites Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Reference 47

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source=pdf_text observed=2026-08-02T06:13:54.498576Z digest=sha256:d47b34b37dbe2bc9cdcc5285fbf6dda72d777560207d1cbe6b2cff0b5de2c07a

Observation f804d397-80b8-48e9-b3a6-8dafd8081c80 · outbound

This paper cites Accelerate: Training and inference at scale made simple, efficient and adaptable.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Accelerate: Training and inference at scale made simple, efficient and adaptable

Reference 48

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source=pdf_text observed=2026-08-02T06:13:54.607186Z digest=sha256:e26bdab6d15908a240d0e3bbf40d4e41adcb29412f198fd9041a0991a56c0376

Observation 96a55390-e8ef-4e21-a9a3-17ef0e834002 · outbound

This paper cites R-Bench: Graduate-level Multi-disciplinary Benchmarks for LLM & MLLM Complex Reasoning Evaluation.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget R-Bench: Graduate-level Multi-disciplinary Benchmarks for LLM & MLLM Complex Reasoning Evaluation

Reference 49

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source=pdf_text observed=2026-08-02T06:13:54.686646Z digest=sha256:6d3962bb39706456a31517c9e7459953d48227edbdd90a64e210014ea3bdcf14

Observation cca0c50c-a931-40fd-acbb-3d69f9e1bdfb · outbound

This paper cites Shampoo: Preconditioned Stochastic Tensor Optimization.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Shampoo: Preconditioned Stochastic Tensor Optimization

Reference 50

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source=pdf_text observed=2026-08-02T06:13:54.765813Z digest=sha256:d3c9cbb0431c4145f215da2732388886a9cb051c86c219d243595a3bb38b8bc3

Observation 2c53b8b0-63c3-4e26-bad0-ef064c19b214 · outbound

This paper cites Optimizing prompts for text-to-image generation.Advances in Neural Information Processing Systems, 36:66923–66939, 2023.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Optimizing prompts for text-to-image generation.Advances in Neural Information Processing Systems, 36:66923–66939, 2023

Reference 51

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source=pdf_text observed=2026-08-02T06:13:54.856542Z digest=sha256:39e8f0f667a4a2735c9c2c62e6b4ef04bd51fb92294fec25d1282358670cd3c9

Observation 48ca3bed-a8e4-4b39-a739-788928365ec2 · outbound

This paper cites Deep residual learning for image recognition.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Deep residual learning for image recognition

Reference 52

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source=pdf_text observed=2026-08-02T06:13:55.039132Z digest=sha256:4eaf846168480694b0594e19e2e5011efb23202316fe2a1ccdfdf09485f89b83

Observation c0cc6a4c-b5f7-4fbe-801c-9483c3d66e56 · outbound

This paper cites Gems: Agent-native multimodal generation with memory and skills.arXiv preprint arXiv:2603.28088, 2026.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Gems: Agent-native multimodal generation with memory and skills.arXiv preprint arXiv:2603.28088, 2026

Reference 53

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source=pdf_text observed=2026-08-02T06:13:55.238304Z digest=sha256:8a1224520ad3f5c322880c3ef30c8a4aa03951d7f4262bbd67e847f909d09210

Observation 08dda659-d79e-4775-aec4-b70a117ec82d · outbound

This paper cites Clipscore: A reference-free evaluation metric for image captioning.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Clipscore: A reference-free evaluation metric for image captioning

Reference 54

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source=pdf_text observed=2026-08-02T06:13:55.418812Z digest=sha256:5e17cca75dc3e812150ba511928d0ad0a880c2bd514f9b174ac73aee3e22e9e9

Observation a965f2af-4b01-46f9-98f2-6259b803aeab · outbound

This paper cites Classifier-free diffusion guidance.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Classifier-free diffusion guidance

Reference 55

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source=pdf_text observed=2026-08-02T06:13:55.557151Z digest=sha256:f59130ca8ed7a3b97f6806e1edb733b6e702a0dcf672badb403d28824009d233

Observation 8c979a0d-60cc-43b2-9825-aab8f399cb30 · outbound

This paper cites Denoising diffusion probabilistic models.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Denoising diffusion probabilistic models

Reference 56

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source=pdf_text observed=2026-08-02T06:13:55.707862Z digest=sha256:a6759984c9c63b781aca2bef5d61146eec3550d88d788006a4d751fa19c8239a

Observation ffb03898-789a-4d9f-9f20-c7e65e4697ef · outbound

This paper cites ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment

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source=pdf_text observed=2026-08-02T06:13:55.904790Z digest=sha256:8802d25cf186f83d42c3821339e8e5402bfe6410a39b9b85c21673f3c6968026

Observation d4f0c738-1968-4d79-8708-6c0439bec751 · outbound

This paper cites Tifa: Accurate and interpretable text-to-image faithfulness evaluation with question answering.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Tifa: Accurate and interpretable text-to-image faithfulness evaluation with question answering

Reference 58

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source=pdf_text observed=2026-08-02T06:13:56.041830Z digest=sha256:cbbf9ffdd730da9bcf7c42fb40585b8c6b733efa67ee5bd1a3bffdbd08a52de8

Observation 4c94ec62-ab7b-4d5c-9624-4155e452756c · outbound

This paper cites T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation.Advancesin Neural Information Processing Systems, 36: 78723–78747, 2023.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation.Advancesin Neural Information Processing Systems, 36: 78723–78747, 2023

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source=pdf_text observed=2026-08-02T06:13:56.113357Z digest=sha256:e651a5d901f23db3734168ddcfd727a90bff5eb440706b80fcfa1eb698d89d97

Observation ba063118-0aa2-45fd-a584-c75445c3e781 · outbound

This paper cites APE: Agentic Prompt Enhancer for Image Generation and Editing.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget APE: Agentic Prompt Enhancer for Image Generation and Editing

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source=pdf_text observed=2026-08-02T06:13:56.352402Z digest=sha256:c09c4619c4e629cf22bd0ecb56d82c711ebf7980de10e4ae366f8e38b6b29380

Observation c5011ab0-04f2-4d95-b2f1-0893b765c17f · outbound

This paper cites Scaling up visual and vision-language representation learning with noisy text supervision.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Scaling up visual and vision-language representation learning with noisy text supervision

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source=pdf_text observed=2026-08-02T06:13:56.524762Z digest=sha256:52f6ca8752756246c8407d896d12729bf96ea8c5a740b7375bb66c365fab7969

Observation 755a992f-99af-41f4-986e-694b341663e5 · outbound

This paper cites Geditbench v2: A human-aligned benchmark for general image editing.arXiv preprint arXiv:2603.28547, 2026.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Geditbench v2: A human-aligned benchmark for general image editing.arXiv preprint arXiv:2603.28547, 2026

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source=pdf_text observed=2026-08-02T06:13:56.724747Z digest=sha256:fef91fa063bbe2a9b6efde88fbad2005411644234b9759e79529d3485cbe928f

Observation 538c7555-23b1-48ab-b710-6830f180844e · outbound

This paper cites Muon: An optimizer for hidden layers in neural networks, 2024.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Muon: An optimizer for hidden layers in neural networks, 2024

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source=pdf_text observed=2026-08-02T06:13:56.865106Z digest=sha256:5ff60ac43f1789075a36f92700a4fdd36ea07b154187fc6877144ce877e04574

Observation 80de5ee0-b980-43fd-9f59-9b376e4b5d6a · outbound

This paper cites Scaling Laws for Neural Language Models.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Scaling Laws for Neural Language Models

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source=pdf_text observed=2026-08-02T06:13:56.968702Z digest=sha256:37e0d961e53fb71754af4266618aa204efeb7d88d0e4e20dc57e307e904dd248

Observation 50192b77-a8d2-4206-863e-b0b813aa884f · outbound

This paper cites Elucidating the design space of diffusion-based generative models.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Elucidating the design space of diffusion-based generative models

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source=pdf_text observed=2026-08-02T06:13:57.079808Z digest=sha256:d482aca22b041a62658bf332cc120666ed953059196593fea38237e5fe32ce6c

Observation 1f9f2373-913a-437e-bfa2-655ada8ef4ab · outbound

This paper cites Analyzing and Improving the Training Dynamics of Diffusion Models.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Analyzing and Improving the Training Dynamics of Diffusion Models

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source=pdf_text observed=2026-08-02T06:13:57.216009Z digest=sha256:1ef3c52f1fa1c52416e41151c148e6e22d4d0e00956713f35b6ba4f68ef6cc40

Observation 04a0050a-c1e6-4be8-bed4-0d4e1b45ebbf · outbound

This paper cites Auto-Encoding Variational Bayes.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Auto-Encoding Variational Bayes

Reference 67

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source=pdf_text observed=2026-08-02T06:13:57.438770Z digest=sha256:8c77448f5ed933bcd8cc761cd286d35da168dfc458cab23c227dcb07f294089f

Observation 2267cbb9-8e49-4103-9fa7-62647a3972de · outbound

This paper cites Pick-a-pic: An open dataset of user preferences for text-to-image generation.Advancesin neural information processing systems, 36:36652–36663, 2023.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Pick-a-pic: An open dataset of user preferences for text-to-image generation.Advancesin neural information processing systems, 36:36652–36663, 2023

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source=pdf_text observed=2026-08-02T06:13:57.501051Z digest=sha256:f0ebdd4c65ddf0992e155e7bac13f1bdc2906a211b1f066dda40ada6945a1751

Observation 50b4faf5-9f72-4782-95a7-a07eeb4edde8 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Imagenet classification with deep convolutional neural networks

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source=pdf_text observed=2026-08-02T06:13:57.566848Z digest=sha256:a7b33ae6fe4b3ace009d687cbca723e9cdce6827805523694dabfa29c4f77e19

Observation 2530bb18-dd66-4894-9842-686a3f70b91b · outbound

This paper cites Kling-image-2.1.https://kling.ai/explore/kling_2.1_api, 2025.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Kling-image-2.1.https://kling.ai/explore/kling_2.1_api, 2025

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source=pdf_text observed=2026-08-02T06:13:57.795681Z digest=sha256:cd46092c955e35c32c852ae4d312a7df3fd592419c0de28baad4b1ea5ef596ba

Observation 4ff55b39-e1d7-422c-8704-f9522f870a07 · outbound

This paper cites Improved precision and recall metric for assessing generative models.Advances in neural information processing systems, 32, 2019.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Improved precision and recall metric for assessing generative models.Advances in neural information processing systems, 32, 2019

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source=pdf_text observed=2026-08-02T06:13:57.949322Z digest=sha256:5a12546d9aa5b800072b98e560ad38e9f8beb718aee1abd72dfc7947397cce05

Observation 48c8b77c-ecca-4584-bea4-b27ad8f95e79 · outbound

This paper cites Krea 2.https://www.krea.ai/blog/krea-2-technical-report, 2026.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Krea 2.https://www.krea.ai/blog/krea-2-technical-report, 2026

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source=pdf_text observed=2026-08-02T06:13:58.148903Z digest=sha256:052ab3fa216c3bf95cf326f045ab0a3aa29962d0275486c282eb4b209f99a1f0

Observation 5fbbbe22-1d65-450a-bd7e-799bf4e581b1 · outbound

This paper cites Qwen-image-bench: From generation to creation in text-to-image evaluation,.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Qwen-image-bench: From generation to creation in text-to-image evaluation,

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source=pdf_text observed=2026-08-02T06:13:58.345604Z digest=sha256:d33921fe5894a6d7b8cd19f64ae805e16e1a1ccbbeac3c46056485264386c44d

Observation ab592bfc-a6f0-46ee-898b-263ba1844a83 · outbound

This paper cites Omnicorpus: A unified multimodal corpus of 10 billion-level images interleaved with text.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Omnicorpus: A unified multimodal corpus of 10 billion-level images interleaved with text

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source=pdf_text observed=2026-08-02T06:13:58.706872Z digest=sha256:dc3fb315bf603da9478e72febc383706af3fd84b5b25b59d2b5fbb02ae313041

Observation d106f05c-e611-472e-b178-05939b2ff582 · outbound

This paper cites Reflect-dit: Inference-time scaling for text-to-image diffusion transformers via in-context reflection.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Reflect-dit: Inference-time scaling for text-to-image diffusion transformers via in-context reflection

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source=pdf_text observed=2026-08-02T06:13:58.913557Z digest=sha256:24c0b07403a0678094f2e47486205a440eaebea03fd07271dd7c05b768d2f746

Observation 3cf9eb3e-3acd-4661-a627-9a159725b674 · outbound

This paper cites Holistic Evaluation of Language Models.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Holistic Evaluation of Language Models

Reference 76

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source=pdf_text observed=2026-08-02T06:13:59.051742Z digest=sha256:5dd078cd0bfaa68e7c539c0aaed8f72a6c00b898f00bc95215cdbfa611842928

Observation bba40d7e-840c-4703-b615-17d26829a106 · outbound

This paper cites Scaling laws for diffusion transformers.arXiv preprint arXiv:2410.08184, 2024.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Scaling laws for diffusion transformers.arXiv preprint arXiv:2410.08184, 2024

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source=pdf_text observed=2026-08-02T06:13:59.249642Z digest=sha256:0c26ceda61078983fce2986ebff6abc431208c66d90204d0bcabd73582f2e1c1

Observation 83294cd2-6ba9-4983-9caf-3e87b519b8b4 · outbound

This paper cites Aegis: Exploring the limit of world knowledge capabilities for unified mulitmodal models.arXiv preprint arXiv:2601.00561, 2026.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Aegis: Exploring the limit of world knowledge capabilities for unified mulitmodal models.arXiv preprint arXiv:2601.00561, 2026

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source=pdf_text observed=2026-08-02T06:13:59.391516Z digest=sha256:a676c16160eed6235104dedec9eddb69a42f823f9879fa6f3cf670e74a523511

Observation 2d35ffb8-c0b4-4ed0-ae88-409ad3f1bd86 · outbound

This paper cites Flow Matching for Generative Modeling.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Flow Matching for Generative Modeling

Reference 79

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source=pdf_text observed=2026-08-02T06:13:59.515766Z digest=sha256:a22d671f7304fd6983e905ae9d2d8a59ec8a5f8f8c478c7214c11a7af0fd920c

Observation 5c858956-67dd-4edf-92b1-c351d1bfc1ca · outbound

This paper cites Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023

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source=pdf_text observed=2026-08-02T06:13:59.574336Z digest=sha256:ddea5e5bada0e3840bfe1b4622b68200543a60f70f767de3efcebf476f46955f

Observation 85f32cd7-747d-45a2-8a92-63a6da5e5d70 · outbound

This paper cites ERNIE-Image Technical Report.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget ERNIE-Image Technical Report

Reference 81

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source=pdf_text observed=2026-08-02T06:13:59.666650Z digest=sha256:1c42e577e8173f8bc1098ae47ecbbde56b0f7e051f6a4971eae79954f8dc23b8

Observation 06c03042-f0b2-40e4-b62f-3b2100b9a800 · outbound

This paper cites Flow-grpo: Training flow matching models via online rl, 2025.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Flow-grpo: Training flow matching models via online rl, 2025

Reference 82

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source=pdf_text observed=2026-08-02T06:13:59.767161Z digest=sha256:3e636595b90535fda9e661880cdb42dd8ff575473cb36005556a54e03d600936

Observation 69616bd8-0930-4e78-8012-2c89c4e9de56 · outbound

This paper cites Step1X-Edit: A Practical Framework for General Image Editing.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Step1X-Edit: A Practical Framework for General Image Editing

Reference 83

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source=pdf_text observed=2026-08-02T06:13:59.853626Z digest=sha256:afb65aa887b4fc283eb8851899589a3b0228d42c6715390cb77fd525148ebe62

Observation 62cdb099-cff2-440b-852b-b74a5be0a285 · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 84

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source=pdf_text observed=2026-08-02T06:13:59.940144Z digest=sha256:43019d26044da924de76b8bc6494abceb80027856573e8cc2924d2c0bfcaea2b

Observation d37fb147-be7c-4c12-803b-49c83bf35939 · outbound

This paper cites DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps

Reference 85

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source=pdf_text observed=2026-08-02T06:14:00.030437Z digest=sha256:6cebd3daaf410a93fd5367f302ed7fc00a9a9fdb83068f3d4e10b3703fc0ab23

Observation 15bff975-6b88-4b74-8c77-6731e2feb991 · outbound

This paper cites Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models.Machine Intelligence Research, 22(4):730–751, June 2025.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models.Machine Intelligence Research, 22(4):730–751, June 2025

Reference 86

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source=pdf_text observed=2026-08-02T06:14:00.164612Z digest=sha256:8c6133a6f5fcb5a90884dd66bae8ec4461bca5f7b0578f856177562151033a63

Observation e7c78af9-1734-4328-8a70-714b749a41ad · outbound

This paper cites Ovis: Structural Embedding Alignment for Multimodal Large Language Model.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Ovis: Structural Embedding Alignment for Multimodal Large Language Model

Reference 87

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source=pdf_text observed=2026-08-02T06:14:00.278259Z digest=sha256:eea0fe43e2a9a4c4b8951af1e9252824788289930187bc04358b542e3c5fada7

Observation 83a1c502-6ea1-4e04-975d-4b659acf135d · outbound

This paper cites Murphy.Probabilistic Machine Learning: Advanced Topics.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Murphy.Probabilistic Machine Learning: Advanced Topics

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source=pdf_text observed=2026-08-02T06:14:00.383398Z digest=sha256:fde191e2a10af6715dc0b58e54c732b2ff758fd9d547920c584214dfcc68bbcd

Observation 932d2aab-c4a1-408a-92bf-f40297455938 · outbound

This paper cites Some matrix-inequalities and metrization of matric-space.Tomsk.Univ.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Some matrix-inequalities and metrization of matric-space.Tomsk.Univ

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source=pdf_text observed=2026-08-02T06:14:00.512440Z digest=sha256:34744fd5408efd0bfd4a0157997fec787c56a9786fe9935c0f29a2687299e770

Observation 3bfc1697-7297-457d-940f-81c0916db196 · outbound

This paper cites Improveddenoisingdiffusionprobabilisticmodels.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Improveddenoisingdiffusionprobabilisticmodels

Reference 90

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source=pdf_text observed=2026-08-02T06:14:00.761659Z digest=sha256:1a05d8726234609eaaf8f4ad7264c2b4ceb0653b9607a9e6e2ba6070101688c5

Observation 4b5eb209-ee01-4f12-94ba-d9a297c6c03a · outbound

This paper cites WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation

Reference 91

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source=pdf_text observed=2026-08-02T06:14:00.915135Z digest=sha256:c50176cbf3c94249e2eec80cf3d236107bf05508b413d5ecb93f7bf72f9f4e2e

Observation c96e4c6d-15f5-43a8-b0b6-02191a0fce95 · outbound

This paper cites RouteLLM: Learning to Route LLMs with Preference Data.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget RouteLLM: Learning to Route LLMs with Preference Data

Reference 92

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source=pdf_text observed=2026-08-02T06:14:01.054277Z digest=sha256:210db11e892c53a6a5aa2e462e09d6df64f74c4a2f2e5b2c2ce0d0db08fe564e

Observation a11cee70-5056-46ee-8127-b20f9bd355c4 · outbound

This paper cites Gpt image 1.https://developers.openai.com/api/docs/models/gpt-image-1, 2025.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Gpt image 1.https://developers.openai.com/api/docs/models/gpt-image-1, 2025

Reference 93

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source=pdf_text observed=2026-08-02T06:14:01.112173Z digest=sha256:3a1aca1d9c51f0d9b382757e82a2b40681238b56b5136dfe1565cd2347f04a5d

Observation 6429ecc9-4650-4d1b-acee-f2c6f9d01816 · outbound

This paper cites Introducing chatgpt images 2.0, 2026.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Introducing chatgpt images 2.0, 2026

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source=pdf_text observed=2026-08-02T06:14:01.157118Z digest=sha256:8e3fd15e86877d4cb754569b84eefad7f961cff011e5203bd80798da13104a72

Observation 7c3a3f45-ca7e-41c3-a48b-02775085e3bf · outbound

This paper cites The Neglected Tails in Vision-Language Models.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget The Neglected Tails in Vision-Language Models

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source=pdf_text observed=2026-08-02T06:14:01.246448Z digest=sha256:6c837c35b504d4be4c953909300a95017582448b106e090ec0c577b489d09919

Observation 5f4faa72-776c-4c8d-9e17-56c2163a7f7d · outbound

This paper cites On aliased resizing and surprising subtleties in gan evaluation.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget On aliased resizing and surprising subtleties in gan evaluation

Reference 96

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source=pdf_text observed=2026-08-02T06:14:01.305543Z digest=sha256:5216d7a4db11ee002b0018df156dabfb7d1d412c93fde5c831eced9e7de3bb1b

Observation a08d4a57-272f-4bbe-bbaf-42e63e8049dc · outbound

This paper cites Scalable Diffusion Models with Transformers.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Scalable Diffusion Models with Transformers

Reference 97

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source=pdf_text observed=2026-08-02T06:14:01.347373Z digest=sha256:a3ad4e84531ed2608a623d66ffd5ca8d712dfaaa289a4aef12de2b344f0acf06

Observation 0ae2d21b-1cb2-4e24-b130-bdb5f5565789 · outbound

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

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Sdxl: Improving latent diffusion models for high-resolution image synthesis

Reference 98

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source=pdf_text observed=2026-08-02T06:14:01.400475Z digest=sha256:b2bae2403d6383e682151364b7e711e197c5a89f7beec68e00b1ad3de2a3bdbe

Observation 9dbde912-babf-48c5-8464-718b6810e908 · outbound

This paper cites Qwen-image-2512: Finer details, greater realism.https://qwen.ai/blog?id= qwen-image-2512, 2025.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Qwen-image-2512: Finer details, greater realism.https://qwen.ai/blog?id= qwen-image-2512, 2025

Reference 99

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source=pdf_text observed=2026-08-02T06:14:01.440759Z digest=sha256:8c0242346e8abeff963bafaa1eb8ca6e3f371b8e1460d1fc38c42b7d0ece4f60

Observation 6dfed77a-d776-4ce5-adf0-c74fbd9b45d6 · outbound

This paper cites Qwen-image-edit-2509: Multi-image support, improved consistency.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Qwen-image-edit-2509: Multi-image support, improved consistency

Reference 100

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source=pdf_text observed=2026-08-02T06:14:01.489522Z digest=sha256:db76a91e0d3ae415b2c76717daf7a433d35764f37448d3bc4856925b72abe6dd

Observation 29045739-ae7c-4be3-9af6-1644e456e694 · outbound

This paper cites Qwen-image-2511.https://qwen.ai/blog?id=qwen-image-2512, 2025.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Qwen-image-2511.https://qwen.ai/blog?id=qwen-image-2512, 2025

Reference 101

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source=pdf_text observed=2026-08-02T06:14:01.543829Z digest=sha256:f26165c48908a0919ec57ad9724a413310fa1dd627e41f4e64bbf6cbc4059812

Pith citing papers

No inbound Pith citation observations are available.