Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T21:35:46.800014Z
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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-08T18:26:58.696936Z
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
Source-reported events for the cited work
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
Source-reported events for the cited work
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
Source-reported events for the cited work
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 2026-08-17T06:30:58.91139+00:00.