Paper Citation Record · LEDGER

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios

As of 18 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 1 inbound Pith citation observation for arXiv:2505.10584.

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

pith.paper-citation-record.v1
2505.10584 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:35:46.800014Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T18:26:58.696936Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-09T06:25:47.590920Z

Reference resolution

28 of 28 outbound references displayed

verified exact0
verified fuzzy0
unresolved28
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c25da9b1-4617-4f35-9301-c2918c0962dc · outbound

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

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.679042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89a2ccab-5ae9-485a-a01d-353547fbd607 · outbound

This paper cites FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.691604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62513cf3-fdfa-4634-8268-707435cc56f1 · outbound

This paper cites Scaling Rectified Flow Transformers for High-Resolution Image Synthesis.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Scaling Rectified Flow Transformers for High-Resolution Image Synthesis

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.696156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 793a193c-fed7-47db-a003-14ab6a21a0a7 · outbound

This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.719423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 448f0fab-4a7e-498a-a04c-b5d57fc85a58 · outbound

This paper cites Open-Sora Plan: Open-Source Large Video Generation Model.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Open-Sora Plan: Open-Source Large Video Generation Model

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.724151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed0e6f4f-713c-40b3-aa4d-350cdce4abfe · outbound

This paper cites Flow Matching for Generative Modeling.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Flow Matching for Generative Modeling

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.729257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2c24953-0e67-4d89-8172-0174682bcf84 · outbound

This paper cites Scalable Diffusion Models with Transformers.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Scalable Diffusion Models with Transformers

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.738594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff87b3f2-02cf-414f-9521-dc1857bce28a · outbound

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

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.747434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a0c538c-90f1-4594-9eeb-efd478f3d3f2 · outbound

This paper cites Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.756193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1322e092-ed32-484f-b961-859ae25486e4 · outbound

This paper cites High-Resolution Image Synthesis with Latent Diffusion Models.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios High-Resolution Image Synthesis with Latent Diffusion Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.760233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 259d5489-6839-4118-aceb-1ce78cd71cbe · outbound

This paper cites Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.764649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68584f29-eb0d-41cc-9ed8-e582bcd9d4e5 · outbound

This paper cites RoFormer: Enhanced Transformer with Rotary Position Embedding.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios RoFormer: Enhanced Transformer with Rotary Position Embedding

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.774210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85146694-698e-4cd6-92c6-fc6a77b6cff2 · outbound

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

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Wan: Open and Advanced Large-Scale Video Generative Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.778346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3bb4660-3dcd-4229-a58a-ace74a9f78f3 · outbound

This paper cites Linting Xue, Noah Constant, Adam Roberts, Mihir Kale, Rami Al-Rfou, Aditya Siddhant, Aditya Barua, and Colin Raffel.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Linting Xue, Noah Constant, Adam Roberts, Mihir Kale, Rami Al-Rfou, Aditya Siddhant, Aditya Barua, and Colin Raffel

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.782355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a17618d-c3a1-4721-b1f4-6e32534c2639 · outbound

This paper cites mT5: A massively multilingual pre-trained text-to-text transformer.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios mT5: A massively multilingual pre-trained text-to-text transformer

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.786637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38699412-8f99-4476-af74-0840b1e40e2f · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.791588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba3c6b50-4a9d-4d98-ab8f-78092cda778b · outbound

This paper cites Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.795933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f66b2f5-b20b-4c08-9b75-e089b1d87516 · outbound

This paper cites Real-Time Video Generation with Pyramid Attention Broadcast.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Real-Time Video Generation with Pyramid Attention Broadcast

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.800014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1ba77d0-58df-4684-9c9f-c0057a23bf8f · outbound

This paper cites DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models

Reference 1991

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.714880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1d694ab-6157-448e-9182-ebefdb530e61 · outbound

This paper cites Generative Adversarial Networks.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Generative Adversarial Networks

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.700667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f768bde-34cd-4f27-85bc-701b6599bf13 · outbound

This paper cites Ray: A Distributed Framework for Emerging AI Applications.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Ray: A Distributed Framework for Emerging AI Applications

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.734024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92eae137-def6-49cf-af5e-b3dca8c00aa1 · outbound

This paper cites TransNet V2: An effective deep network architecture for fast shot transition detection.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios TransNet V2: An effective deep network architecture for fast shot transition detection

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.769727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2b25d9b-2958-422e-a565-fa7ab2999420 · outbound

This paper cites Denoising Diffusion Probabilistic Models.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Denoising Diffusion Probabilistic Models

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.709540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc3a161a-8627-45a6-adca-8c6dead481f6 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Learning Transferable Visual Models From Natural Language Supervision

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.751651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35c3c781-b44f-4cda-8157-373fa8da7700 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Classifier-Free Diffusion Guidance

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.705035Z

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Unavailable: canonical work link unavailable.

Observation f50fc7b4-9415-4810-9995-4eb56e09b961 · outbound

This paper cites MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.673136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42bab8db-d6b2-44bd-b9b1-8897b48f31ba · outbound

This paper cites $\Delta$-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios $\Delta$-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.683588Z

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Unavailable: canonical work link unavailable.

Observation 31c75b5b-3bb8-4e78-b7ba-73ffea183194 · outbound

This paper cites Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-15T21:35:46.742877Z

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Unavailable: canonical work link unavailable.

Pith citing papers

Observation 70928bd8-2549-4e5f-8aea-1494b44e1581 · inbound

Mamoda2.5: Enhancing Unified Multimodal Model with DiT-MoE cites this paper.

Mamoda2.5: Enhancing Unified Multimodal Model with DiT-MoE Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:25:47.596534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.