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Paper Citation Record · LEDGER

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning

As of 17 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 2 inbound Pith citation observations for arXiv:2505.17540.

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

pith.paper-citation-record.v1
2505.17540 v1

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:49:08.313317Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T05:13:42.934115Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T05:15:54.348264Z

Reference resolution

63 of 63 outbound references displayed

  • verified exact3
  • verified fuzzy7
  • unresolved53
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2a237e53-70eb-4d21-acf4-6ab9f50f2106 · outbound

This paper cites GPT-4 Technical Report.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning GPT-4 Technical Report

Reference 1

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source=pdf_text observed=2026-08-07T14:49:01.837447Z digest=sha256:7ab73b498b037830c382b015588c9b7f3a67e15eb06362aa91cc10bb516f0cf7

Observation b0e3d67d-b7fb-43de-9f14-a6bb56885238 · outbound

This paper cites Improving image generation with better captions.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Improving image generation with better captions

Reference 2

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source=pdf_text observed=2026-08-07T14:49:01.917329Z digest=sha256:df5a5f887952dbb0772d2bcf68c839ed3471bac3d27beddb172d438a7e5c085c

Observation a90988b7-628c-4705-a937-36d702fec898 · outbound

This paper cites Training Diffusion Models with Reinforcement Learning.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Training Diffusion Models with Reinforcement Learning

Reference 3

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source=pdf_text observed=2026-08-07T14:49:02.074364Z digest=sha256:3c26e36203cd0ddea8b6a67496f7e2eb98db107308274ff4f5c5ba333d5f0234

Observation 5f503239-41b8-4818-8b80-9e3eec994d17 · outbound

This paper cites BeautifulPrompt: Towards Automatic Prompt Engineering for Text-to-Image Synthesis.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning BeautifulPrompt: Towards Automatic Prompt Engineering for Text-to-Image Synthesis

Reference 4

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local_arxiv, observed 2026-08-07T14:49:09.678792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:49:02.193944Z digest=sha256:10fb879a2ef8ac49679529dfbfd5bd8110fccabfaeabacb0a6ce78e320c0c35b

Observation c7d13886-23d5-49a9-bdf1-470abd134858 · outbound

This paper cites Training-free Regional Prompting for Diffusion Transformers.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Training-free Regional Prompting for Diffusion Transformers

Reference 5

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source=pdf_text observed=2026-08-07T14:49:02.298652Z digest=sha256:6409592f890e9018780d56a8b32e4e9a82147b19770f0d3ab091beba50af7edf

Observation f1beb165-4cd6-467f-8366-e2183308954a · outbound

This paper cites Pixart- σ: Weak-to-strong training of diffusion transformer for 4k text-to-image generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Pixart- σ: Weak-to-strong training of diffusion transformer for 4k text-to-image generation

Reference 6

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source=pdf_text observed=2026-08-07T14:49:02.417696Z digest=sha256:e71357769054237247512464a7960c44a1fdad666265692ede64d246901f8f77

Observation 1bd9abf5-2e31-4fa1-b3e6-414c3f330de4 · outbound

This paper cites Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling

Reference 7

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source=pdf_text observed=2026-08-07T14:49:02.511529Z digest=sha256:f418b64a14a5be498255106967308cb00cbb88b2fadb89ac8004bd11b9cd9b33

Observation 0e337797-abd4-473d-9d18-3f649e88ccb2 · outbound

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

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Scaling rectified flow trans- formers for high-resolution image synthesis

Reference 8

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source=pdf_text observed=2026-08-07T14:49:02.578086Z digest=sha256:767c71df8130e9e56b95a919ce4b5eb0ed2dabb48efc5ba8b44d9457adbc45d4

Observation 4a9c9932-7e71-461e-ba8b-098fefaff345 · outbound

This paper cites Video-R1: Reinforcing Video Reasoning in MLLMs.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Video-R1: Reinforcing Video Reasoning in MLLMs

Reference 9

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source=pdf_text observed=2026-08-07T14:49:02.659124Z digest=sha256:099d50642092d8450dd67e36b8f6cbc12da8c2b112f274b09580058ac4754b9c

Observation d095863d-ec7e-4611-bcdc-7744fe5767fd · outbound

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

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Geneval: An object-focused framework for evaluating text-to-image alignment

Reference 10

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source=pdf_text observed=2026-08-07T14:49:02.758559Z digest=sha256:91565829f7e74b8505d84527225aa0c6ff2fbdad15eb4d742c35e1a39341f2bd

Observation 1d684b91-246c-474c-ae73-8e3bb940a83e · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 11

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source=pdf_text observed=2026-08-07T14:49:02.820798Z digest=sha256:fdf6f9604c4fb48fa148803dfd7e903569f9ff18b8207f0d27a343315d3a1748

Observation 68985570-cf22-4c64-a81b-df78e17297cc · outbound

This paper cites VersaT2I: Improving Text-to-Image Models with Versatile Reward.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning VersaT2I: Improving Text-to-Image Models with Versatile Reward

Reference 12

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source=pdf_text observed=2026-08-07T14:49:02.905061Z digest=sha256:3a3e18391daa45a459c10cb97d3c41707cf66753a2ea600b34d72a33ec3a839e

Observation d2ea6fd7-5eff-4b53-b889-422edfe5faf5 · outbound

This paper cites Can We Generate Images with CoT? Let's Verify and Reinforce Image Generation Step by Step.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Can We Generate Images with CoT? Let's Verify and Reinforce Image Generation Step by Step

Reference 13

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source=pdf_text observed=2026-08-07T14:49:03.001071Z digest=sha256:d62ad8a323c0065ab9abda7137012f077c80c8511b8687ef3b3bb372810763fd

Observation b545ffe2-00e7-4534-a532-0b48f2ba55d1 · outbound

This paper cites A simple and effective reinforcement learning method for text-to-image diffusion fine-tuning.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning A simple and effective reinforcement learning method for text-to-image diffusion fine-tuning

Reference 14

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source=pdf_text observed=2026-08-07T14:49:03.111538Z digest=sha256:58e801cad3ec3f9f3c9f85f56bd7cc8a09ac83c4b67979da421d7fbd23bd93c9

Observation e7f967d9-bfc1-4578-b2d6-e2ecd55d571d · outbound

This paper cites Optimizing prompts for text-to-image generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Optimizing prompts for text-to-image generation

Reference 15

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raw_fallback, observed 2026-08-07T14:49:11.406579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:49:03.241841Z digest=sha256:8143e32481d5592b776fdaef9549a449a422762b62593152c5b8dbcf1efaed55

Observation fdc1ef76-50d7-44c3-ba88-4d5d7ed4ccc1 · outbound

This paper cites T2i-compbench: A compre- hensive benchmark for open-world compositional text-to-image generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning T2i-compbench: A compre- hensive benchmark for open-world compositional text-to-image generation

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:49:03.344646Z digest=sha256:8df5a73c09e5bc3bb87881ad2a8c9b87cbf5e1506398853e09d21005f468756f

Observation efb91d72-2bd2-4ef7-9da4-e9e7d1f49cac · outbound

This paper cites Boosting MLLM Reasoning with Text-Debiased Hint-GRPO.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Boosting MLLM Reasoning with Text-Debiased Hint-GRPO

Reference 17

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source=pdf_text observed=2026-08-07T14:49:03.494449Z digest=sha256:c583027a9961c56882deb0fedb0c0f5ed1ed4865bbfea0670cdbc4b740bfd575

Observation 546980d3-7fa9-4def-a44c-bb5048126620 · outbound

This paper cites Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 18

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source=pdf_text observed=2026-08-07T14:49:03.656408Z digest=sha256:aa95e1cc7d1c378c121b56fed230febd44542566c5c848368504b964aa23cccf

Observation 86004940-c933-4699-aa4e-dbe24a3520fc · outbound

This paper cites OpenAI o1 System Card.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning OpenAI o1 System Card

Reference 19

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source=pdf_text observed=2026-08-07T14:49:03.753170Z digest=sha256:857d81cc2d4f5a0488cd5d9ad4c79fbadc787db941cfa47e8d31e0398a5acd19

Observation 7ee20ec3-bc98-4ba6-beea-86807f72809f · outbound

This paper cites T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoT.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoT

Reference 20

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source=pdf_text observed=2026-08-07T14:49:03.893674Z digest=sha256:d1a68e5ff88369ff08312e9b808e0f1ba41deedb31494e16778161b59f297b3c

Observation 5a4467ca-7c90-4c8d-8e12-ff6f8406d14e · outbound

This paper cites Pick-a-pic: An open dataset of user preferences for text-to-image generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Pick-a-pic: An open dataset of user preferences for text-to-image generation

Reference 21

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source=pdf_text observed=2026-08-07T14:49:04.002901Z digest=sha256:e38654ad46e93ec16f639a7a1bd7b3726c347bb01f312006b97748e82f34b07e

Observation dfd53082-325b-45ab-95bf-ddc8aec15881 · outbound

This paper cites an unresolved cited work.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Unresolved cited work

Reference 22

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source=pdf_text observed=2026-08-07T14:49:04.114737Z digest=sha256:deb7f3875a5d8062f629343f8c028581ef582f88c7e649094fc34a907e928609

Observation 5315e9e0-89e8-46bc-a49a-4f8df1aeef1a · outbound

This paper cites Aligning Text-to-Image Models using Human Feedback.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Aligning Text-to-Image Models using Human Feedback

Reference 23

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source=pdf_text observed=2026-08-07T14:49:04.234638Z digest=sha256:b12c11f4929c5f415aa05a0665966ec654703c54c7661367045eb72caef0532d

Observation b91ce33d-a12b-4f34-81bf-72b7637961d7 · outbound

This paper cites Parrot: Pareto-optimal multi-reward reinforcement learning framework for text-to-image generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Parrot: Pareto-optimal multi-reward reinforcement learning framework for text-to-image generation

Reference 24

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source=pdf_text observed=2026-08-07T14:49:04.355793Z digest=sha256:77892237a1a2c696bb65cd47ab381286aca0ad5a337867305424b8a3fdba356d

Observation cda6905f-c5b1-4793-87b6-7c120fbe169d · outbound

This paper cites VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning

Reference 25

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source=pdf_text observed=2026-08-07T14:49:04.492737Z digest=sha256:bfe506d7c5f8d0e228d9ad59120d04a1f7def678bd16b11a0d2b037365b795a1

Observation 0ed0ac74-e055-4076-b538-1f802b9a5f00 · outbound

This paper cites Rich human feedback for text-to-image generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Rich human feedback for text-to-image generation

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:49:04.616829Z digest=sha256:7916a5cede5439ba49ed68dd56f4f4c2034a92cf50349ad784ffd1c2f2336294

Observation 5b7f518a-5f1d-4917-824d-cf9e5d79b6bf · outbound

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

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Playground v3: Improving Text-to-Image Alignment with Deep-Fusion Large Language Models

Reference 27

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source=pdf_text observed=2026-08-07T14:49:04.771360Z digest=sha256:6847b18a139e783045edc15608ce05ead30addf58acd59a1d73cf4b52c74d272

Observation 8e1dd84c-fab1-43d0-9340-31f6ef219a45 · outbound

This paper cites UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning

Reference 28

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source=pdf_text observed=2026-08-07T14:49:04.878809Z digest=sha256:3dd95e65b5b8a43cb5af9605088bb8312fe1434b4f6f7d47f479115aa9da0dc8

Observation aaa4947c-353b-441b-96d5-ec5513b83962 · outbound

This paper cites Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps

Reference 29

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source=pdf_text observed=2026-08-07T14:49:04.986986Z digest=sha256:65ae70184d902282ac2c1e0afed9d165b641a4050f98256bfe8e16da805fddcd

Observation fa0ade0d-1170-4d39-a89b-fd0e2150e4a1 · outbound

This paper cites Deepperception: Advancing r1-like cognitive visual perception in mllms for knowledge-intensive visual grounding.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Deepperception: Advancing r1-like cognitive visual perception in mllms for knowledge-intensive visual grounding

Reference 30

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source=pdf_text observed=2026-08-07T14:49:05.118052Z digest=sha256:36032eab6fc63045d9e4ec1744f63c9508eaa4316c1d9adabf07f5e7f18363c6

Observation d1cf3905-27a2-4b85-b117-a4f7c8cd9960 · outbound

This paper cites Improving Text-to-Image Consistency via Automatic Prompt Optimization.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Improving Text-to-Image Consistency via Automatic Prompt Optimization

Reference 31

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source=pdf_text observed=2026-08-07T14:49:05.244513Z digest=sha256:697797838298a67dfa8ffcad1817c7b084e3b3a4b9de990e2db41cb51894645c

Observation ef35f0ff-7164-4f28-8241-11009701c900 · outbound

This paper cites Dynamic prompt optimizing for text-to-image generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Dynamic prompt optimizing for text-to-image generation

Reference 32

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raw_fallback, observed 2026-08-07T14:49:10.705624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:49:05.399264Z digest=sha256:f2e5839cf3f1faa0965fa5887b06952294b73cebbd9e40ac198275bb9e31aebf

Observation eceddefc-29c9-4928-8e43-ebd1b33057a8 · outbound

This paper cites Preference Adaptive and Sequential Text-to-Image Generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Preference Adaptive and Sequential Text-to-Image Generation

Reference 33

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source=pdf_text observed=2026-08-07T14:49:05.508199Z digest=sha256:8b5c9029be970057903fe6fd71289324ffe4e6a98e3f0b452db711e44ffb6963

Observation 4424fbae-01e6-47ba-a757-3d834ac3d637 · outbound

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

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 34

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source=pdf_text observed=2026-08-07T14:49:05.605645Z digest=sha256:97ca8106c6de10a7905057c1864477c2cf3843813e48a0f6e4bd88e8014cbdfc

Observation 6f66e5d7-2e63-4922-892d-d6e88607e9e7 · outbound

This paper cites Diffusiongpt: Llm-driven text-to-image generation system.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Diffusiongpt: Llm-driven text-to-image generation system

Reference 35

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source=pdf_text observed=2026-08-07T14:49:05.678066Z digest=sha256:e02db238cd994ee11c5026c100a96f473d208adb5d12ca792443edde56c97c4f

Observation 917512dd-4ce3-414b-abc4-897d38cb3bca · outbound

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

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning High- resolution image synthesis with latent diffusion models

Reference 36

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source=pdf_text observed=2026-08-07T14:49:05.783083Z digest=sha256:a97ef6f35da225fca3582b11abada0cf7bf11700a53619ef44ab4e36e4118f2d

Observation 85c5a8ad-419a-4a28-80c0-5850a818c3fc · outbound

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

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Photorealistic text-to-image diffusion models with deep language understanding

Reference 37

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source=pdf_text observed=2026-08-07T14:49:05.849176Z digest=sha256:822e2247ef62413a61f97fa0093f0e1e322864666b328cba6e1513e591088ac7

Observation 61c0ab3d-4406-45d7-89e3-fdbba3079fde · outbound

This paper cites FairCoT: Enhancing Fairness in Text-to-Image Generation via Chain of Thought Reasoning with Multimodal Large Language Models.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning FairCoT: Enhancing Fairness in Text-to-Image Generation via Chain of Thought Reasoning with Multimodal Large Language Models

Reference 38

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source=pdf_text observed=2026-08-07T14:49:05.928871Z digest=sha256:ef1f8b89b7d4233873099222e929997891d0a2a582a5b647cf41fc757e407b24

Observation fb7847d3-d40f-446d-96c8-2222cc23b10a · outbound

This paper cites VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model

Reference 39

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source=pdf_text observed=2026-08-07T14:49:06.046543Z digest=sha256:94d511485c02f0d6fb6af171638a1577ce27501bd81c62246ffd87c19e2e7726

Observation 20e3a568-51e3-47ce-a953-bb8eb8dae86f · outbound

This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 40

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source=pdf_text observed=2026-08-07T14:49:06.145848Z digest=sha256:62d745094a292bcb08488a8be740f9c72e154399c93a88eae8cc96214f86e56c

Observation 07f4aa66-f7c1-4cd8-babb-e82b3a5475b0 · outbound

This paper cites Reft: Reason- ing with reinforced fine-tuning.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Reft: Reason- ing with reinforced fine-tuning

Reference 41

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:49:06.222540Z digest=sha256:4501eade9e51142ec74c794a95b2906014c18da697bd75a96096e3e7fe8e648b

Observation d72d288b-ab7e-4198-9fbd-b109f3043ea1 · outbound

This paper cites Diffusion model alignment using direct preference optimization.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Diffusion model alignment using direct preference optimization

Reference 42

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source=pdf_text observed=2026-08-07T14:49:06.282736Z digest=sha256:c3d6d523c8682c2897b45399d598710b9289435b571874a897a2f0439056cbfc

Observation 8354ca32-de60-4a27-815f-afb0b02f0c36 · outbound

This paper cites SimpleAR: Pushing the Frontier of Autoregressive Visual Generation through Pretraining, SFT, and RL.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning SimpleAR: Pushing the Frontier of Autoregressive Visual Generation through Pretraining, SFT, and RL

Reference 43

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source=pdf_text observed=2026-08-07T14:49:06.404856Z digest=sha256:f3b2e18c7eed223e727234fcd5c04557883e49c1523d3e0e0f76609c4b160791

Observation 3f6b87a9-df61-4eab-95f2-9149e0a580e8 · outbound

This paper cites Mint: Multi-modal chain of thought in unified generative models for enhanced image generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Mint: Multi-modal chain of thought in unified generative models for enhanced image generation

Reference 44

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source=pdf_text observed=2026-08-07T14:49:06.461069Z digest=sha256:8aecce0b9b107399f3ff6bb3f4239f5e84d696e866ae7c30fe2c1ffa8598b59b

Observation b0e7fb15-ba11-491a-aefc-2f068c793b79 · outbound

This paper cites Genartist: Multimodal llm as an agent for unified image generation and editing.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Genartist: Multimodal llm as an agent for unified image generation and editing

Reference 45

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source=pdf_text observed=2026-08-07T14:49:06.590652Z digest=sha256:c238019fa477716747adbda372488703dd390be432b40aaa0ba2fb0843fb950b

Observation 23281936-61ec-463e-a03f-4de7b5244e6f · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Chain-of-thought prompting elicits reasoning in large language models

Reference 46

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source=pdf_text observed=2026-08-07T14:49:06.695683Z digest=sha256:703b7f49fa39ca46614f64a69be9ff7db98271f598911d88acff57dc4388fa8f

Observation 5b1c4e98-ff2d-4f58-9808-0ee440b83591 · outbound

This paper cites Self-correcting llm-controlled diffusion models.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Self-correcting llm-controlled diffusion models

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:49:10.202580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:49:06.840329Z digest=sha256:c68cb5ccfd7d662ee57ccd92a69f7bb295c57c274175f8e7e509263927273555

Observation 24c293dc-da51-4b7a-9485-9148647fb7a2 · outbound

This paper cites SANA 1.5: Efficient Scaling of Training-Time and Inference-Time Compute in Linear Diffusion Transformer.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning SANA 1.5: Efficient Scaling of Training-Time and Inference-Time Compute in Linear Diffusion Transformer

Reference 48

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source=pdf_text observed=2026-08-07T14:49:06.921433Z digest=sha256:2d101d8bb56c406f45efb1d83aa49c9e9488807a479327b75ac5b4a0a89b0b5c

Observation 9ea9f249-8fbf-4f1a-8828-0a09e7ebae22 · outbound

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

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

Reference 49

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source=pdf_text observed=2026-08-07T14:49:07.003942Z digest=sha256:f9ad06fa1ad058902976eaf287b7f06433397c3978a412dbd468d8b69fd46468

Observation a9790556-0bfd-4fc9-ad41-d1583cf49b71 · outbound

This paper cites Imagereward: Learning and evaluating human preferences for text-to-image generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Imagereward: Learning and evaluating human preferences for text-to-image generation

Reference 50

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source=pdf_text observed=2026-08-07T14:49:07.081695Z digest=sha256:ed90c22e8f3cddc9c8a89655c6676bd4cc8c4da3a1ca3a448482d71058203b91

Observation ba061631-dbb1-4e8d-88ce-825f77bf570f · outbound

This paper cites DanceGRPO: Unleashing GRPO on Visual Generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning DanceGRPO: Unleashing GRPO on Visual Generation

Reference 51

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source=pdf_text observed=2026-08-07T14:49:07.170807Z digest=sha256:9cdb28a217f1a65a0a1fc4e1d63721d56e38ac9638d6d145656b938c4e257c9b

Observation e6a25805-b53e-4bcc-b613-19fabd885838 · outbound

This paper cites Qwen2.5 Technical Report.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Qwen2.5 Technical Report

Reference 52

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source=pdf_text observed=2026-08-07T14:49:07.247590Z digest=sha256:4a0d6549992ac6b9983cca11a894f72e45c714d7450069513a7841eeae258f3e

Observation b0a09c41-c0aa-4579-9cd9-a805a73c02ff · outbound

This paper cites Mastering text-to-image diffusion: Recaptioning, planning, and generating with multimodal llms.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Mastering text-to-image diffusion: Recaptioning, planning, and generating with multimodal llms

Reference 53

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source=pdf_text observed=2026-08-07T14:49:07.305264Z digest=sha256:f2dfa5d191c1212a81658716c149f0953aef2207d027355f6659ecfd52aae54e

Observation cc0e0cbb-c811-422f-a6c2-66f66137d865 · outbound

This paper cites A Dense Reward View on Aligning Text-to-Image Diffusion with Preference.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning A Dense Reward View on Aligning Text-to-Image Diffusion with Preference

Reference 54

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source=pdf_text observed=2026-08-07T14:49:07.407728Z digest=sha256:05af7ceec05d6d4aadb2a95f3c07bdce49c24fe94ef2fe244e5e8f8f70efb333

Observation 67869d98-7605-42e3-8156-6b6374ba421f · outbound

This paper cites R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization

Reference 55

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source=pdf_text observed=2026-08-07T14:49:07.511716Z digest=sha256:b85cf02635a4538d23322e3abf217354e7397325f0edbcd56fff26fabdd1a0ee

Observation 0120178c-f175-421a-a517-dc5473fad00b · outbound

This paper cites Idea2img: Iterative self-refinement with gpt-4v for automatic image design and generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Idea2img: Iterative self-refinement with gpt-4v for automatic image design and generation

Reference 56

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:49:07.616883Z digest=sha256:aa9cc8605f4349ea97f87d5d390852cb599915f65f66304f33688a91d9af2780

Observation e3298c3e-744e-4c1d-8de9-4682084dd23d · outbound

This paper cites Tipo: Text to image with text presampling for prompt optimization.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Tipo: Text to image with text presampling for prompt optimization

Reference 57

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:49:07.691290Z digest=sha256:d5e83fa00dfa3666119493211f1e60e926cf73b677b30679ae011c158b5ff78b

Observation 131b1d12-7e74-488f-9639-5a66260a5684 · outbound

This paper cites Perception-R1: Pioneering Perception Policy with Reinforcement Learning.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Perception-R1: Pioneering Perception Policy with Reinforcement Learning

Reference 58

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source=pdf_text observed=2026-08-07T14:49:07.789675Z digest=sha256:583b9f88a6ca9bb4669efe7f177555cafbada261326d46642a2a9e84226a0039

Observation 6dbcd73b-01e5-41dd-a884-60c1e51580d2 · outbound

This paper cites Learning to Sample Effective and Diverse Prompts for Text-to-Image Generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Learning to Sample Effective and Diverse Prompts for Text-to-Image Generation

Reference 59

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local_arxiv, observed 2026-08-07T14:49:08.623995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:49:07.892684Z digest=sha256:209631378f50949893798322183da8648c9621c49a619cbf459952c32a16cda2

Observation 1740fecb-eff9-4db1-8641-235519ede143 · outbound

This paper cites R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization

Reference 60

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source=pdf_text observed=2026-08-07T14:49:08.000931Z digest=sha256:6f3b92945188a3993dea2c6508d923485a7d02b30c6da250589f8bb8e93f1f4e

Observation 8a3e481c-55bb-4e0e-ae96-8a598fe009f5 · outbound

This paper cites IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation

Reference 61

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source=pdf_text observed=2026-08-07T14:49:08.072338Z digest=sha256:a6cc4f244eac181b0fd4c30d6d3b5135e7e845f671789b02dd90c833982d3363

Observation 7cee6f8d-aeec-459c-90c2-f47d0a55674b · outbound

This paper cites Layercraft: Enhancing text-to-image generation with cot reasoning and layered object integration.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Layercraft: Enhancing text-to-image generation with cot reasoning and layered object integration

Reference 62

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source=pdf_text observed=2026-08-07T14:49:08.176819Z digest=sha256:c0c46c0e0ccccda28559d8faeafe993d9d179dd580d518359f6bf4e08fa872a4

Observation 672d72ac-72a6-4fa0-99a9-2a968adf0d0a · outbound

This paper cites Scores as Actions: a framework of fine-tuning diffusion models by continuous-time reinforcement learning.

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning Scores as Actions: a framework of fine-tuning diffusion models by continuous-time reinforcement learning

Reference 63

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source=pdf_text observed=2026-08-07T14:49:08.313317Z digest=sha256:23c44ac682874d490b8792af70c268e46d5ac830ad2181d56a0ccbc42d8ccf5b

Pith citing papers

Observation dcda053b-3db9-47d6-9614-6f5ec6395dcc · inbound

RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling cites this paper.

RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning

Reference 29

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arxiv_id, observed 2026-05-18T05:15:54.350941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-18T05:13:42.934115Z digest=sha256:76a0953f03e79c5b0fc4b6656468427b1d9728daf70a560ab705c3b555ce0813

Observation cb3317d0-c110-49a5-9976-de4a07b49920 · inbound

A Systematic Post-Train Framework for Video Generation cites this paper.

A Systematic Post-Train Framework for Video Generation RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning

Reference 18

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arxiv_id, observed 2026-05-11T23:26:21.417103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-07T16:58:33.014401Z digest=sha256:06ddb1609fbac2c67b613ba5283b2d4b59fe721ab615d12f6cd582ac4514f35d