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Paper Citation Record · LEDGER

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs

As of 10 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 2 inbound Pith citation observations for arXiv:2506.07045.

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

pith.paper-citation-record.v1
2506.07045 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:48:55.145079Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T19:51:45.257204Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

68 of 68 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved51
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0e7f8d76-f94f-4b44-a366-0d0f1e6f9a30 · outbound

This paper cites an unresolved cited work.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Unresolved cited work

Reference 1

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Observation 803ed133-5c58-4336-8a44-e4218c5fc407 · outbound

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

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Large scale gan training for high fidelity natural image synthesis

Reference 2

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Observation 4501467c-2486-4752-84fd-d6f2756acb2c · outbound

This paper cites Maskgit: Masked generative image transformer.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Maskgit: Masked generative image transformer

Reference 3

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Observation 3ac597b2-829e-4ef9-8e22-aced466b0b71 · outbound

This paper cites AntifakePrompt: Prompt-Tuned Vision-Language Models are Fake Image Detectors.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs AntifakePrompt: Prompt-Tuned Vision-Language Models are Fake Image Detectors

Reference 4

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Observation db06f4aa-8502-47bb-bccb-3ebffdae7e1d · outbound

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

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Pixart- σ: Weak-to-strong training of diffusion transformer for 4k text-to-image generation

Reference 5

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Observation 7176906a-fefb-496f-9ea7-56624645777b · outbound

This paper cites PIXART-{\delta}: Fast and Controllable Image Generation with Latent Consistency Models.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs PIXART-{\delta}: Fast and Controllable Image Generation with Latent Consistency Models

Reference 6

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Observation 95014658-ac33-4506-81cf-a8d27fed04e4 · outbound

This paper cites PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 7

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Observation d4efb5d2-1349-4dee-8bcb-eae3e34bd7bb · outbound

This paper cites R1-v: Reinforcing super generaliza- tion ability in vision-language models with less than $3.https://github.com/Deep-Agent/ R1-V, 2025.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs R1-v: Reinforcing super generaliza- tion ability in vision-language models with less than $3.https://github.com/Deep-Agent/ R1-V, 2025

Reference 8

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Observation 95898ec4-0fc4-433d-9510-367969ddd549 · outbound

This paper cites Expanding performance boundaries of open-source multimodal models with model, data, and test-time scaling, 2025.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Expanding performance boundaries of open-source multimodal models with model, data, and test-time scaling, 2025

Reference 9

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Observation f1e7c8f3-2bb6-4ed3-84f8-a8b4e4684b7c · outbound

This paper cites On the detection of synthetic images generated by diffusion models.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs On the detection of synthetic images generated by diffusion models

Reference 10

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Observation 8fda4d6e-c16c-42f2-99a3-19ef0403c29d · outbound

This paper cites Li, and Li Fei-Fei.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Li, and Li Fei-Fei

Reference 11

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Observation 39713f27-1e7a-4841-83ad-08f4a3c2e7dd · outbound

This paper cites Witherden.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Witherden

Reference 12

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ae43a7da-127d-48e9-a3ab-9f95a0978857 · outbound

This paper cites Scaling rectified flow transformers for high-resolution image synthesis, 2024.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Scaling rectified flow transformers for high-resolution image synthesis, 2024

Reference 13

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Observation e38691b6-2ff7-4c8a-8a32-70639c23e7ab · outbound

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

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Taming transformers for high-resolution image synthesis

Reference 14

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Observation 0d0e1d5f-32ed-498b-b680-09cbeb5cfaee · outbound

This paper cites Leveraging frequency analysis for deep fake image recognition.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Leveraging frequency analysis for deep fake image recognition

Reference 15

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Observation b4a016f9-8ab7-43d4-b2a1-5199f50c0867 · outbound

This paper cites an unresolved cited work.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Unresolved cited work

Reference 16

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Observation c627ae84-6a6d-4690-a634-6068160aae11 · outbound

This paper cites Fake or JPEG? Revealing Common Biases in Generated Image Detection Datasets.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Fake or JPEG? Revealing Common Biases in Generated Image Detection Datasets

Reference 17

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Observation c5733705-d799-4d65-94d4-5917ff8b4c85 · outbound

This paper cites Vector quantized diffusion model for text-to-image synthesis.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Vector quantized diffusion model for text-to-image synthesis

Reference 18

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Observation 772af3bd-20b0-4bc5-9b4e-17ffa5d60199 · outbound

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

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 19

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Observation b9dd8cd8-0564-4a0f-a727-4bedf20e389b · outbound

This paper cites Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis

Reference 20

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Observation 3331b2a9-7ba8-484e-aa06-82f4db5dc329 · outbound

This paper cites Denoising Diffusion Probabilistic Models.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Denoising Diffusion Probabilistic Models

Reference 21

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Observation 48441d9a-76fc-44e2-a92a-af8794007c85 · outbound

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

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 22

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Observation 8746c636-0c81-4f9d-a86c-4920d717200c · outbound

This paper cites OpenAI o1 System Card.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs OpenAI o1 System Card

Reference 23

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Observation f8cfe678-9952-47c6-8012-f97e01aa4c3f · outbound

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

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoT

Reference 24

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Observation 2c20a2d8-01bc-4ab9-86a4-ea0b8fc6d9ee · outbound

This paper cites A style-based generator architecture for generative adversarial networks.2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 4396–4405, 2018.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs A style-based generator architecture for generative adversarial networks.2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 4396–4405, 2018

Reference 25

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Observation 7d6f2faa-3b59-4dfc-808a-3e105841c2b3 · outbound

This paper cites Flux.https://github.com/black-forest-labs/flux, 2024.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Flux.https://github.com/black-forest-labs/flux, 2024

Reference 26

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Observation 581d1329-37cd-4107-8be0-da8572df8ebf · outbound

This paper cites FakeBench: Probing Explainable Fake Image Detection via Large Multimodal Models.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs FakeBench: Probing Explainable Fake Image Detection via Large Multimodal Models

Reference 27

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Observation fe6721fe-3541-4b89-b4cd-deacd7399960 · outbound

This paper cites an unresolved cited work.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Unresolved cited work

Reference 28

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Observation c28363fa-ba59-4d2b-8d3c-a040c7f15fc3 · outbound

This paper cites an unresolved cited work.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Unresolved cited work

Reference 29

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Observation cb7e5213-8ff5-4313-9378-fdbe5e3da131 · outbound

This paper cites Midjourney, 2023.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Midjourney, 2023

Reference 30

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 11a71384-23b1-4a1c-8cc7-25c3ce55430c · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 31

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Observation 6d49cb2a-fd81-4305-a838-a30531a11118 · outbound

This paper cites Towards universal fake image detectors that generalize across generative models.2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 24480–24489, 2023.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Towards universal fake image detectors that generalize across generative models.2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 24480–24489, 2023

Reference 32

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Observation 70fd46fc-2543-4fe2-b18a-c314c456dd73 · outbound

This paper cites Dall·e 3 system card, 2023.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Dall·e 3 system card, 2023

Reference 33

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Observation 6244c030-da6a-4d4c-83b2-81c53d7c81f3 · outbound

This paper cites Introducing 4o image generation, Mar 2025.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Introducing 4o image generation, Mar 2025

Reference 34

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 8f5a04ac-0987-46c5-80d8-e87cd012a2e5 · outbound

This paper cites Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022

Reference 35

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source=pdf_text observed=2026-08-07T05:48:50.955102Z digest=sha256:a179f4962fff5ef89b0dc76dd2cba387ce8919209af0aa98992db0f080f7ce8f

Observation 04b3b00c-b072-4a79-9734-767ad16a5a2c · outbound

This paper cites MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning

Reference 36

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source=pdf_text observed=2026-08-07T05:48:51.106955Z digest=sha256:77b2f0cdf94f01dd60c06739dae9dfa1d958b98fe8a1ca0b3ffc3edd15c4da2d

Observation 41ab725f-d6d2-4d24-bdf7-07f5f05ca2f1 · outbound

This paper cites Community forensics: Using thousands of generators to train fake image detectors, 2024.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Community forensics: Using thousands of generators to train fake image detectors, 2024

Reference 37

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raw_fallback, observed 2026-08-07T05:48:57.547665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:48:51.249174Z digest=sha256:ca746e23365152c40b595a826493ca963abf820cd818543701aee420f791e64c

Observation 0567dd4b-b0e8-429a-b921-f4c965670d52 · outbound

This paper cites Scalable diffusion models with transformers.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Scalable diffusion models with transformers

Reference 38

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source=pdf_text observed=2026-08-07T05:48:51.373781Z digest=sha256:fa50eec9c9032fc490663c0438103264cbf254e4dd3c4c1e88e205143e4c4ea7

Observation ea4d3ae2-260f-47cd-a298-c91581a5d099 · outbound

This paper cites LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL

Reference 39

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source=pdf_text observed=2026-08-07T05:48:51.514329Z digest=sha256:f5fa8d4790dac4e92417863b989208956c813d680257a34fed1d4e852ade5d12

Observation 036a4fa0-38bc-4bcd-a2e1-03361296afbc · outbound

This paper cites Qwen2.5-vl, January 2025.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Qwen2.5-vl, January 2025

Reference 40

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source=pdf_text observed=2026-08-07T05:48:51.636135Z digest=sha256:ad62a93d7b0edaf612563ae5c3de1545db2ceff68ac95c9a5415dd1d196b27ef

Observation 3bee05a3-5f7a-4c42-a890-a080ce2b6ce4 · outbound

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

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 41

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source=pdf_text observed=2026-08-07T05:48:51.752372Z digest=sha256:4f2112839953885461b4782e4498c04052792cad043030fc6c67196fdddd4dc2

Observation 5a4cfdbc-4fa5-4024-8de3-304dc0f17d93 · outbound

This paper cites Rapidata openai 4o preference, Mar 2025.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Rapidata openai 4o preference, Mar 2025

Reference 42

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raw_fallback, observed 2026-08-07T05:48:57.262378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:48:51.867586Z digest=sha256:e1f6fba48149538562d3743cccadf1914eb8950ec92ac671aab88f567189a18e

Observation 9069a64d-d0b9-422c-8785-73cfac203fcb · outbound

This paper cites an unresolved cited work.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Unresolved cited work

Reference 43

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:48:51.996273Z digest=sha256:3c97157ac4548cc934677db6359e84d234679d5f6a64daa5af0a2583eeb2f35b

Observation 8e3322b7-803e-4288-87c0-52a0c6746e25 · outbound

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

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs High- resolution image synthesis with latent diffusion models

Reference 45

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source=pdf_text observed=2026-08-07T05:48:52.246543Z digest=sha256:d92da05d4089e88e35b82d55ff37074a77c80f8c516c4baf5656290bd3f9325c

Observation b42a3a56-990c-49bd-96c5-c26fab66c890 · outbound

This paper cites FaceForensics++: Learning to detect manipulated facial images.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs FaceForensics++: Learning to detect manipulated facial images

Reference 46

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verified fuzzy
raw_fallback, observed 2026-08-07T05:48:56.739978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:48:52.364865Z digest=sha256:c027499cd59dd568a655ced43bbdeb13f0afe14bb823f0c0dd1c15319ddfe19a

Observation b4bdfadc-0be5-48c3-a2b4-d9ffefec4e29 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.Advances in Neural Information Processing Systems, 35:36479–36494, 2022.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Photorealistic text-to-image diffusion models with deep language understanding.Advances in Neural Information Processing Systems, 35:36479–36494, 2022

Reference 47

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T05:48:52.519229Z digest=sha256:8a763d23b65e0552cf22889402ed7637da1b781f3c624620eae7caba9a3e4746

Observation 50934704-7f11-4a33-a645-7069c477362b · outbound

This paper cites Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra

Reference 48

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verified fuzzy
raw_fallback, observed 2026-08-07T05:48:56.529751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:48:52.635706Z digest=sha256:82f29aa7a8bdf9b28358e808e6e5d4215630cdeff3c11e00daf3dec1712ec22f

Observation ef605562-9d20-4cea-adc2-958f60edb5f4 · outbound

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

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 49

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T05:48:52.739165Z digest=sha256:aa4030a81505bee0c8a4d7f5b59791f7eb72bc471f0a24798703aa86dc8b2622

Observation 7f41f5c8-a783-4870-a1a8-35f6ea756aff · outbound

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

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model

Reference 50

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source=pdf_text observed=2026-08-07T05:48:52.835129Z digest=sha256:f08df99e1cbe9692a84806e017c7725a5666d7b7e7fcd251a88029eb6239d7a5

Observation 3fdfd517-3cf0-4e12-98c9-dd7271710d31 · outbound

This paper cites Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 51

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source=pdf_text observed=2026-08-07T05:48:52.935967Z digest=sha256:d9f74716c11ae03ce92289fc156b321d020554c34a5a4882d1ab4249262896b1

Observation f02bd0a1-16bb-487d-b07c-803ca65569e4 · outbound

This paper cites Denoising Diffusion Implicit Models.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Denoising Diffusion Implicit Models

Reference 52

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source=pdf_text observed=2026-08-07T05:48:53.041425Z digest=sha256:66499e4b4562ada297b0fcff0eeb13266f3dcc2ab0d1c0b4d91c73be7307dacd

Observation cf0e2900-bde2-45ff-ba06-6eb85915a682 · outbound

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

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 53

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source=pdf_text observed=2026-08-07T05:48:53.184151Z digest=sha256:901b0da7ca2a413de217cf66486d4bb72753ddc3cc22e92350abcad0b4296155

Observation 35060b25-8ffb-42d1-a720-756a33f7dab4 · outbound

This paper cites Axiomatic attribution for deep networks.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Axiomatic attribution for deep networks

Reference 54

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verified fuzzy
raw_fallback, observed 2026-08-07T05:48:56.308422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:48:53.324987Z digest=sha256:4e530a207d28f4b330d6a500d57ab950d6fd82e7dc9c97424960c3bc88083a7a

Observation 8a093ee3-ee65-4fdf-8528-ce90f5a08efe · outbound

This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 55

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source=pdf_text observed=2026-08-07T05:48:53.454345Z digest=sha256:4d4b2ba613a649555245129726f12da69a9323a75d2c3db09c7fc0d724b8a00c

Observation cb0e83bd-2e69-4a4b-8dc3-4db9c942bfc2 · outbound

This paper cites Galip: Generative adversarial clips for text-to-image synthesis.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Galip: Generative adversarial clips for text-to-image synthesis

Reference 56

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raw_fallback, observed 2026-08-07T05:48:56.142569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:48:53.588159Z digest=sha256:6ad0edb738a91d7821e8623901386fb6e5acfd379db0189d0f92b1d9c19a658e

Observation 27ab6bfe-108a-474e-af38-98c75799394e · outbound

This paper cites Visual autoregressive modeling: Scalable image generation via next-scale prediction.Advances in neural information processing systems, 37:84839–84865, 2024.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Visual autoregressive modeling: Scalable image generation via next-scale prediction.Advances in neural information processing systems, 37:84839–84865, 2024

Reference 57

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source=pdf_text observed=2026-08-07T05:48:53.682291Z digest=sha256:cf3e7e5577ee9e0bac18aa219c85c716d5b8cfde705976e3f7e9b64b05965535

Observation 9165d7d7-7170-488d-aabb-8e0ba2ffba10 · outbound

This paper cites Neural discrete representation learning.Advances in neural information processing systems, 30, 2017.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Neural discrete representation learning.Advances in neural information processing systems, 30, 2017

Reference 58

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source=pdf_text observed=2026-08-07T05:48:53.797233Z digest=sha256:7f836a3823a473e7b1ca9762487be8ecdebd50207a766ef856e3766b69039147

Observation e5ef4c12-43f8-4160-9034-7a2fe3057d22 · outbound

This paper cites VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning

Reference 59

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source=pdf_text observed=2026-08-07T05:48:53.929107Z digest=sha256:5c809102eb98a9f9b350704e708f3332bf717acd40975cc8332b378395a4601b

Observation b9c2cce1-18f5-4bcd-bbaa-83f297ab0191 · outbound

This paper cites Objectformer for image manipulation detection and localization.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Objectformer for image manipulation detection and localization

Reference 60

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raw_fallback, observed 2026-08-07T05:48:55.996473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:48:54.057267Z digest=sha256:2ba719297c42a72ea549327e7350ac7514490d37f518553e0a01f67a16a7ecc2

Observation 721ae601-ec48-4c43-8434-5c0e0d0e68a1 · outbound

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

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 61

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source=pdf_text observed=2026-08-07T05:48:54.134553Z digest=sha256:423a14fba8f864b0be65b076a99102cf2958f15ede46edb6d3b04530b24fc2f2

Observation b4dc13ff-6422-4a7c-b142-6dcdabbf60b4 · outbound

This paper cites Cnn- generated images are surprisingly easy to spot.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Cnn- generated images are surprisingly easy to spot

Reference 62

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source=pdf_text observed=2026-08-07T05:48:54.203270Z digest=sha256:0cd881969122bb3bb005141ae63afe7ff9df7f9605d4b9e0c1c9841cc0410099

Observation 67d4c699-1623-44f4-b2b0-3a5e4d881b44 · outbound

This paper cites Dire for diffusion-generated image detection.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Dire for diffusion-generated image detection

Reference 63

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source=pdf_text observed=2026-08-07T05:48:54.348033Z digest=sha256:35d975aaecf2863debbaff765fa52ffed47682357b525380189cd6d0a940449f

Observation 3f8897c8-3c31-4f32-8a2d-e0cc3e02ea8b · outbound

This paper cites Fast-slow thinking for large vision-language model reasoning.arXiv preprint arXiv:2504.18458, 2025.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Fast-slow thinking for large vision-language model reasoning.arXiv preprint arXiv:2504.18458, 2025

Reference 64

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source=pdf_text observed=2026-08-07T05:48:54.453592Z digest=sha256:3f07cc2a8900839323d83bd11e7e9f4c7b98c299c246e5fcb56666168391a6e2

Observation 3b06c47f-d3be-4171-951b-60878842d293 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Segformer: Simple and efficient design for semantic segmentation with transformers

Reference 65

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verified fuzzy
raw_fallback, observed 2026-08-07T05:48:55.814632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:48:54.590355Z digest=sha256:cae2ffb24d04b75015f6022dcf109fe6cfe885dceaa617db453e0679542e3dd4

Observation a8bfaf4e-1672-4d46-b297-4a163a4f8466 · outbound

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

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization

Reference 66

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source=pdf_text observed=2026-08-07T05:48:54.733441Z digest=sha256:d4c8dc69d51478aaaac0ea74c7973c6892c119da759fd402d61e79058b11e2e8

Observation 354205a5-d3e9-423a-9aeb-e0e6f77dfbc6 · outbound

This paper cites A-Bench: Are LMMs Masters at Evaluating AI-generated Images?.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs A-Bench: Are LMMs Masters at Evaluating AI-generated Images?

Reference 67

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source=pdf_text observed=2026-08-07T05:48:54.850810Z digest=sha256:9ebb25150efac8f61c4051ede914addcc98584f16e81db35a57ac7798afacfe5

Observation cf516f23-fc17-4eb7-a91a-500d0b8a3847 · outbound

This paper cites Swift: a scalable lightweight infrastructure for fine-tuning.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs Swift: a scalable lightweight infrastructure for fine-tuning

Reference 68

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:48:55.023878Z digest=sha256:0068b27f212f76487d4b43c12aa24166d59b927c41132ecfbd46f9a616776ce3

Observation dafa2d1b-efdb-4b0b-a124-67545590b87d · outbound

This paper cites R1-Zero's "Aha Moment" in Visual Reasoning on a 2B Non-SFT Model.

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs R1-Zero's "Aha Moment" in Visual Reasoning on a 2B Non-SFT Model

Reference 69

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:48:55.145079Z digest=sha256:33285da056a491590eda7596efc810f7c322750bdc2fbe0795053a007b3cb2f1

Pith citing papers

Observation 58107120-92a3-49ae-9527-a2a7309da508 · inbound

AgentFoX: LLM Agent-Guided Fusion with eXplainability for AI-Generated Image Detection cites this paper.

AgentFoX: LLM Agent-Guided Fusion with eXplainability for AI-Generated Image Detection Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs

Reference 12

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source=pdf_text observed=2026-07-13T19:51:45.257204Z digest=sha256:09fca41db8956cce282cab9b30a36b50146c4cbc558838c54df3f35f610a0e65

Observation a3c20b4e-4204-443f-9e34-d6ec153f28b3 · inbound

XPlainVerse: A Million-Scale Benchmark for Explainable Deepfake Detection cites this paper.

XPlainVerse: A Million-Scale Benchmark for Explainable Deepfake Detection Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs

Reference 16

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no resolver link, observed 2026-07-12T01:35:43.979206Z

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source=pdf_text observed=2026-07-12T01:35:43.979206Z digest=sha256:ddc0abff3f313be3471d8cf0f6fc2041bb9a7b5c5e7dfce6b0be7d21d6541c37