Paper Citation Record · LEDGER

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network

As of 9 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2508.16089.

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

pith.paper-citation-record.v1
2508.16089 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:34:02.646497Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

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verified fuzzy23
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 807391ab-ce77-44c8-b90c-212a12fb905f · outbound

This paper cites Vlmo: Unified vision-language pre-training with mixture-of-modality- experts.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Vlmo: Unified vision-language pre-training with mixture-of-modality- experts

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:07.275659Z

Source-reported events for the cited work

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Observation 64590cfe-e14f-49ad-827e-36655f4e277a · outbound

This paper cites Automatic image processing algorithm for light en- vironment optimization based on multimodal neural network model.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Automatic image processing algorithm for light en- vironment optimization based on multimodal neural network model

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:07.144592Z

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Observation effea056-ae49-451e-beaa-c449ba074cc6 · outbound

This paper cites Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers

Reference 3

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Observation e1f2da3c-ca74-4e8e-9c18-5197e27e4e0e · outbound

This paper cites Crd-cgan: Category- consistent and relativistic constraints for diverse text-to-image genera- tion.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Crd-cgan: Category- consistent and relativistic constraints for diverse text-to-image genera- tion

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:06.948332Z

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Observation 87c69aa9-49dd-4e08-b790-ed7954e39c91 · outbound

This paper cites Language is not all you need: Aligning perception with language models.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Language is not all you need: Aligning perception with language models

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:06.803936Z

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Observation be22b351-0e5e-44a2-8a4a-9b8400ff3ff9 · outbound

This paper cites Adaptive frequency filters as efficient global token mixers.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Adaptive frequency filters as efficient global token mixers

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:06.692902Z

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Observation 299ed658-aa87-426b-a99b-c2c3cc54a161 · outbound

This paper cites Fast and efficient image generation using variational autoencoders and k-nearest neighbor oversampling approach.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Fast and efficient image generation using variational autoencoders and k-nearest neighbor oversampling approach

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:06.511813Z

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Observation 946f70a0-0285-4c93-b365-e48688ced583 · outbound

This paper cites An underwater image enhancement method for a preprocessing framework based on generative adversarial network.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network An underwater image enhancement method for a preprocessing framework based on generative adversarial network

Reference 8

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Observation d715a7a3-7d13-4a23-99d7-375b91b6b5c5 · outbound

This paper cites Vilt: Vision-and-language transformer without convolution or region supervision.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Vilt: Vision-and-language transformer without convolution or region supervision

Reference 9

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Observation d33d5f5e-7cde-4e19-aa61-8daee01a1ad5 · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T17:34:00.199286Z

Source-reported events for the cited work

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Observation 79da46f4-044a-4ecb-b850-f74b304d4705 · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 11

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Source-reported events for the cited work

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Observation 10a08b3d-d280-4753-a246-c984f741afb7 · outbound

This paper cites Align before fuse: Vision and language representation learning with momentum distillation.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Align before fuse: Vision and language representation learning with momentum distillation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:06.154262Z

Source-reported events for the cited work

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Observation 35f40323-ed57-40d4-b829-b4e32bb89201 · outbound

This paper cites Vision-Language Foundation Models as Effective Robot Imitators.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Vision-Language Foundation Models as Effective Robot Imitators

Reference 13

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Source-reported events for the cited work

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Observation 921cecd7-bb63-4701-bc08-856a750a01be · outbound

This paper cites Scaling language-image pre-training via masking.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Scaling language-image pre-training via masking

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:05.930398Z

Source-reported events for the cited work

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Observation 7feb6fbd-6f91-4ce3-b933-acff55a14ded · outbound

This paper cites Novel creation method of feature graphics for image generation based on deep learning algorithms.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Novel creation method of feature graphics for image generation based on deep learning algorithms

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:05.706933Z

Source-reported events for the cited work

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Observation 0fe6d947-a3a7-4014-904f-75a62fcc9ace · outbound

This paper cites Comparing recognition performance and robustness of multimodal deep learning models for multimodal emotion recognition.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Comparing recognition performance and robustness of multimodal deep learning models for multimodal emotion recognition

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:05.531871Z

Source-reported events for the cited work

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Observation 5ed001aa-81d2-4c8c-a99e-f81dbc9d923f · outbound

This paper cites Cogan: Cooperatively trained conditional and unconditional gan for person image generation.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Cogan: Cooperatively trained conditional and unconditional gan for person image generation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:05.382658Z

Source-reported events for the cited work

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Observation 29a9f4b4-55b6-4509-92fa-82439cfa4e7a · outbound

This paper cites Learning transferable visual models from natural language supervision.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Learning transferable visual models from natural language supervision

Reference 18

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This paper cites Explor- ing the limits of transfer learning with a unified text-to-text transformer.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Explor- ing the limits of transfer learning with a unified text-to-text transformer

Reference 19

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Observation 8ad94daa-7b47-4bee-a05c-ffe133b0f482 · outbound

This paper cites Generative multimodal models are in-context learners.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Generative multimodal models are in-context learners

Reference 20

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Observation c329a4c6-9edb-4265-91cd-8ef687e88ab1 · outbound

This paper cites Attentional generative adversarial networks with representativeness and diversity for generating text to realistic image.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Attentional generative adversarial networks with representativeness and diversity for generating text to realistic image

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:05.093550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b683f7ec-3cf0-45da-b83d-23cfa7dfcc4f · outbound

This paper cites Improving the quality of image generation in art with top-k training and cyclic generative methods.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Improving the quality of image generation in art with top-k training and cyclic generative methods

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:04.957270Z

Source-reported events for the cited work

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Observation f3705f24-c791-4f63-a289-3f61ecc1505f · outbound

This paper cites Image generation and recognition technology based on attention residual gan.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Image generation and recognition technology based on attention residual gan

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:04.700687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4b80da1b-58b7-46f3-89d4-0af64770e6a8 · outbound

This paper cites Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks

Reference 24

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Observation 52f2e878-0718-4778-b710-d7566931bf27 · outbound

This paper cites Rca-gan: An improved image denoising algorithm based on generative adversarial networks.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Rca-gan: An improved image denoising algorithm based on generative adversarial networks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:04.479728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8b5c4c48-daf3-46d8-beda-09af2f5425c9 · outbound

This paper cites GenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editing.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network GenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editing

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T17:34:01.898001Z

Source-reported events for the cited work

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Observation 62e09caa-9ced-409a-b069-f9baa68df613 · outbound

This paper cites Lpgan: A lbp-based proportional input generative adversarial network for image fusion.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Lpgan: A lbp-based proportional input generative adversarial network for image fusion

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:04.143415Z

Source-reported events for the cited work

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Observation b900d4cd-3e2c-43a4-8d71-6a1b80ff14b4 · outbound

This paper cites Vsa: Learning varied-size window attention in vision transformers.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Vsa: Learning varied-size window attention in vision transformers

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:03.894380Z

Source-reported events for the cited work

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Observation b56fd965-992a-4f7f-ac04-fc18e07569a3 · outbound

This paper cites Joint generative image deblurring aided by edge attention prior and dynamic kernel selection.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Joint generative image deblurring aided by edge attention prior and dynamic kernel selection

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:03.657397Z

Source-reported events for the cited work

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Observation 9cf712a0-2da6-4bf7-9953-87b5e763845c · outbound

This paper cites Cyclic generative attention- adversarial network for low-light image enhancement.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Cyclic generative attention- adversarial network for low-light image enhancement

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:03.400026Z

Source-reported events for the cited work

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Observation c953e967-ddb9-49a9-bbe8-26f3ebf106cb · outbound

This paper cites Adapt or perish: Adaptive sparse transformer with attentive feature refinement for image restoration.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Adapt or perish: Adaptive sparse transformer with attentive feature refinement for image restoration

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:03.192686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9840be96-bf92-43a3-bbe7-7c1e96ab7293 · outbound

This paper cites Wdig: a wavelet domain image generation framework based on frequency domain op- timization.

Two-flow Feedback Multi-scale Progressive Generative Adversarial Network Wdig: a wavelet domain image generation framework based on frequency domain op- timization

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:34:03.004159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.