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Paper Citation Record · LEDGER

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation

As of 15 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 3 inbound Pith citation observations for arXiv:2602.12155.

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

pith.paper-citation-record.v1
2602.12155 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T23:59:17.993681Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T00:38:02.427407Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T01:37:30.404151Z

Reference resolution

37 of 37 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved36
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a0b4121d-4ba3-494b-93fd-44031dafec3f · outbound

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

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling

Reference 4

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source=pdf_text observed=2026-08-02T23:59:13.320139Z digest=sha256:148ed646b36e33f2e22f15274ef75732b2892801ce56e7a31891259fb747f736

Observation 86223844-178b-4219-962d-5a12096217af · outbound

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

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack

Reference 6

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source=pdf_text observed=2026-08-02T23:59:13.788036Z digest=sha256:15113ee7d3ce1b736e6a17bc7292aaf3b3c4337edb243088ad0757d739f7322d

Observation 274bffed-081c-426a-b544-abf5f793c6a0 · outbound

This paper cites Learning Robust Rewards with Adversarial Inverse Reinforcement Learning.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Learning Robust Rewards with Adversarial Inverse Reinforcement Learning

Reference 7

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source=pdf_text observed=2026-08-02T23:59:13.978878Z digest=sha256:92840f8016c298a9aabe69da99c54f7f378e8a5302448d2bf3b98e41aa045650

Observation 4a78692d-2783-4952-afa1-acbe16800b3f · outbound

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

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again

Reference 8

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source=pdf_text observed=2026-08-02T23:59:14.132457Z digest=sha256:62d785fe2e9b6f763a4ba1990c3f17310725e97b62125b03aa49f8b8447b0cc7

Observation bb9e4bf9-2c61-4835-8079-70bdef6dd9ca · outbound

This paper cites an unresolved cited work.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Unresolved cited work

Reference 9

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source=pdf_text observed=2026-08-02T23:59:17.862417Z digest=sha256:7aaff1d0bd32fd55b2458f20cfd2726b18484329a9c4b1a33fdd9940b2a9611e

Observation 4eb4d2eb-7ccc-42e0-8226-b093c5bc099c · outbound

This paper cites Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning

Reference 10

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source=pdf_text observed=2026-08-02T23:59:14.512941Z digest=sha256:89fca94107a83a5c6757b6b684ecaa06645e05d3ce65b132a4c8844249abee86

Observation 94d76a06-1e3d-4784-acdf-3d4c5bdff26f · outbound

This paper cites FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space

Reference 12

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source=pdf_text observed=2026-08-02T23:59:14.925936Z digest=sha256:c6cb8901a0d2b6f3f815b573dd754b412f4e0620de973ea03d00b96df6aa3b49

Observation f78ed658-46cc-4566-baf4-fed0239a4fe0 · outbound

This paper cites Playground v2.5: Three Insights towards Enhancing Aesthetic Quality in Text-to-Image Generation.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Playground v2.5: Three Insights towards Enhancing Aesthetic Quality in Text-to-Image Generation

Reference 13

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source=pdf_text observed=2026-08-02T23:59:15.072317Z digest=sha256:3ccf1c646226105a909aed59e12cbc71ac32f6d7ca35a49e4369d3c1d1042b7e

Observation 8a656026-517d-4ef3-bef0-4c6615b48164 · outbound

This paper cites Flow-GRPO: Training Flow Matching Models via Online RL.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Flow-GRPO: Training Flow Matching Models via Online RL

Reference 15

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source=pdf_text observed=2026-08-02T23:59:15.386262Z digest=sha256:33bc275220834c2501b4fffd36acff726a26b75770cbc2ad6c94ab8fb16646fc

Observation 8f369ea5-f9c5-42c8-81cc-693911905620 · outbound

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

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 16

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source=pdf_text observed=2026-08-02T23:59:15.544483Z digest=sha256:a019227895e221cd4e20dd8a14de93a2f0516c238146c91e100f10d2bcd6cd67

Observation d98f1354-21d8-462d-9250-32d032ece66a · outbound

This paper cites Decoupled Weight Decay Regularization.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Decoupled Weight Decay Regularization

Reference 17

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Observation 71aaac17-d079-4327-a4b9-f971fe9f3c99 · outbound

This paper cites HPSv3: Towards Wide-Spectrum Human Preference Score.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation HPSv3: Towards Wide-Spectrum Human Preference Score

Reference 18

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source=pdf_text observed=2026-08-02T23:59:15.904880Z digest=sha256:607a6cabd44b4b3857525d778d64136309ec23afe2974bf12ae3d8e019dbd112

Observation 6110491d-3f52-421b-9f2f-7a52c6b18727 · outbound

This paper cites Flow Matching Policy Gradients.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Flow Matching Policy Gradients

Reference 19

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source=pdf_text observed=2026-08-02T23:59:16.138832Z digest=sha256:24954b1c2c9a5473e46294f3143bbee469723f8d56519d75b0878a0205307971

Observation 182e82a6-cc07-40ed-b41c-2131866326e9 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation DINOv2: Learning Robust Visual Features without Supervision

Reference 20

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source=pdf_text observed=2026-08-02T23:59:16.234675Z digest=sha256:22a5efea9be02fae09562007e9ccd7273df4664c718589b1875697ca092e6414

Observation 01f2ff38-0fa1-4bb2-b121-ba6cb451f60d · outbound

This paper cites Hybrid Inverse Reinforcement Learning.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Hybrid Inverse Reinforcement Learning

Reference 21

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source=pdf_text observed=2026-08-02T23:59:16.415376Z digest=sha256:3efeee789d5091d1e0079da54f75d3f22181a2aa284b8b9c8c8cd5f4b26fdd00

Observation 06747a69-9d39-4bbc-ba0d-282da1218ef5 · outbound

This paper cites Proximal Policy Optimization Algorithms.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Proximal Policy Optimization Algorithms

Reference 23

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source=pdf_text observed=2026-08-02T23:59:16.749269Z digest=sha256:6789ffec2b0a202607f5b2053f6e444f41e0df337b260e75ad80d160bd639093

Observation 3226be7c-d242-46f4-a027-d3641c51b797 · outbound

This paper cites Directly Aligning the Full Diffusion Trajectory with Fine-Grained Human Preference.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Directly Aligning the Full Diffusion Trajectory with Fine-Grained Human Preference

Reference 25

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source=pdf_text observed=2026-08-02T23:59:17.056636Z digest=sha256:47ae1221b9ecdc15a06c8c3947296ff5c74ae07a51feef87866784f3fe44969c

Observation e2167caf-095e-4f7b-bd71-915bfd384348 · outbound

This paper cites DINOv3.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation DINOv3

Reference 26

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source=pdf_text observed=2026-08-02T23:59:17.124942Z digest=sha256:6ab8b0fbfd25c20ec89f6ee4067966b9e16dd7610a7660cbfdc6ab35f5304b12

Observation 0e4d725a-ed8e-4c67-bb7f-4566a1961c45 · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Wan: Open and Advanced Large-Scale Video Generative Models

Reference 28

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source=pdf_text observed=2026-08-02T23:59:17.243926Z digest=sha256:74211151bd2de334933dff560ad9a7fe4f8199f704821b5f170d7fd3b811c03e

Observation c032f16a-a040-4fb4-9c40-c4286e83d5b1 · outbound

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

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Emu3: Next-Token Prediction is All You Need

Reference 29

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Observation 5081e440-d5f6-4bc2-a884-09bb00c77df0 · outbound

This paper cites Pref-GRPO: Pairwise Preference Reward-based GRPO for Stable Text-to-Image Reinforcement Learning.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Pref-GRPO: Pairwise Preference Reward-based GRPO for Stable Text-to-Image Reinforcement Learning

Reference 30

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source=pdf_text observed=2026-08-02T23:59:17.428586Z digest=sha256:72b3e58099f46967cb91edbab7ada0c8bfb13121af8d7962b59902f0b9abbe50

Observation b258675a-e4d7-4741-b290-ba436f8b0f16 · outbound

This paper cites Qwen-Image Technical Report.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Qwen-Image Technical Report

Reference 31

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source=pdf_text observed=2026-08-02T23:59:17.509783Z digest=sha256:6a0ca6ad03c01aaa5f5678cdcf4487e6ce983e8815b93d9894402e88e5f2b317

Observation 2ecd5d4b-1a6c-4aef-bc49-b849fb441aa4 · outbound

This paper cites Tackling the Generative Learning Trilemma with Denoising Diffusion GANs.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 32

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Observation 17ec8c89-3e9b-4634-bb62-eab347019ae5 · outbound

This paper cites Ad- vantage weighted matching: Aligning rl with pretraining in diffusion models.arXiv preprint arXiv:2509.25050, 2025a.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Ad- vantage weighted matching: Aligning rl with pretraining in diffusion models.arXiv preprint arXiv:2509.25050, 2025a

Reference 33

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Observation b17a2fa9-7b02-4132-993c-2e367cc34ae2 · outbound

This paper cites Therefore, we approximate the log-probability of a samplexunder policyπ θ as: logπθ(x)≈ −LCF M(θ, x) +C.(7) A.2.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Therefore, we approximate the log-probability of a samplexunder policyπ θ as: logπθ(x)≈ −LCF M(θ, x) +C.(7) A.2

Reference 34

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Observation 95b73786-1c01-4bf2-8203-4840b05c20f1 · outbound

This paper cites For inference, we generate 4 images per prompt for UniGen and DPG, and 1 image per prompt for Alchemist.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation For inference, we generate 4 images per prompt for UniGen and DPG, and 1 image per prompt for Alchemist

Reference 36

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Observation 38ded7db-07c0-4538-a564-121e087e3c5e · outbound

This paper cites Subsequently, from step 100 to 400, the optimization shifts focus to refining low-level details, resulting in significant improvements in text rendering and fine-grained textures.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Subsequently, from step 100 to 400, the optimization shifts focus to refining low-level details, resulting in significant improvements in text rendering and fine-grained textures

Reference 37

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Observation 3ed0c257-6fec-4467-b33e-a268a69c9105 · outbound

This paper cites Qwen3-VL Technical Report.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Qwen3-VL Technical Report

Reference 2004

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Observation 5593e5a7-9ffa-46d9-bb08-b66bd3f16928 · outbound

This paper cites Fast high-resolution image synthe- sis with latent adversarial diffusion distillation.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Fast high-resolution image synthe- sis with latent adversarial diffusion distillation

Reference 2011

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Observation 856a6ee4-ac84-43be-9b18-dd5e22efcbe7 · outbound

This paper cites Flow Matching for Generative Modeling.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Flow Matching for Generative Modeling

Reference 2015

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Observation d96873e6-8d3a-4d72-965d-fbccdbc9e5f0 · outbound

This paper cites Classifier-Free Diffusion Guidance.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Classifier-Free Diffusion Guidance

Reference 2016

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Observation 521b2c4b-8a75-44fc-9bbf-d7e9050b8194 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 2017

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Observation 2dbf4cb5-45fe-4559-b77f-46e77d2443e0 · outbound

This paper cites Alchemist: Turning public text-to-image data into generative gold.arXiv preprint arXiv:2505.19297,.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Alchemist: Turning public text-to-image data into generative gold.arXiv preprint arXiv:2505.19297,

Reference 2020

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Observation 58864310-b306-4983-b100-3a323443aa4b · outbound

This paper cites A Large-Scale Study on Regularization and Normalization in GANs.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation A Large-Scale Study on Regularization and Normalization in GANs

Reference 2022

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Observation fd15ab86-c4cc-4ca0-a4f3-28920028d1b0 · outbound

This paper cites Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer

Reference 2023

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Observation fe582972-1d29-471a-a6a1-684d1920a535 · outbound

This paper cites Training Diffusion Models with Reinforcement Learning.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Training Diffusion Models with Reinforcement Learning

Reference 2024

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Observation ce9abb3d-6204-471d-97b7-4969ea6631f0 · outbound

This paper cites Directly Fine-Tuning Diffusion Models on Differentiable Rewards.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Directly Fine-Tuning Diffusion Models on Differentiable Rewards

Reference 2025

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unresolved
no resolver link, observed 2026-08-02T23:59:13.557517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:59:13.557517Z digest=sha256:017689f578640b27af02a71974a180e7c7ed4dd81041302127741187251d186b

Pith citing papers

Observation d28d6489-dbe1-4a67-a3b1-d5ceb1e74a9e · inbound

Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges cites this paper.

Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges FAIL: Flow Matching Adversarial Imitation Learning for Image Generation

Reference 174

Resolution
verified exact
arxiv_id, observed 2026-06-30T03:17:27.371081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T13:58:53.430492Z digest=sha256:141e5548014cf54dd8c52270b3ccbdf376523e204a45d2e56203f3d2623d1931

Observation df89d157-c801-4394-b017-29a36d388137 · inbound

Proxy Reward Internalization and Mechanistic Exploitation: A Learned Precursor to Reward Hacking and Its Generalization cites this paper.

Proxy Reward Internalization and Mechanistic Exploitation: A Learned Precursor to Reward Hacking and Its Generalization FAIL: Flow Matching Adversarial Imitation Learning for Image Generation

Reference 286

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T01:37:30.405440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-06-27T16:26:34.918099Z digest=sha256:e3df7d64315af42d56e6bbee629bcefe3721967781e2ec7b05f697e494347c07

Observation dc0c84c3-4acb-4a32-8d6f-2d329ef53ada · inbound

AnyBand: Unified Multi-Bandwidth Speech Extension via Frequency-Aware In-Context Spectral Infilling cites this paper.

AnyBand: Unified Multi-Bandwidth Speech Extension via Frequency-Aware In-Context Spectral Infilling FAIL: Flow Matching Adversarial Imitation Learning for Image Generation

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T00:38:02.427407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T00:38:02.427407Z digest=sha256:43e8729ffae362884c66bb6238b9d278056ed4a36ae6438b92ac5326bb3e0ef0