Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-27T17:16:44.500338Z
Paper Citation Record · LEDGER
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution
As of 7 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2606.09250.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
18 of 18 outbound references displayed
- verified exact11
- verified fuzzy0
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch5
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 96968f5d-6d71-4f60-b7de-03d50a8a06ff · outbound
This paper cites Relactrl: Relevance-guided efficient control for diffusion transformers.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution Relactrl: Relevance-guided efficient control for diffusion transformers
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T00:17:29.638999Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0b1f2bb2-52c8-4667-b2ce-4762ec0471cd · outbound
This paper cites AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T00:17:29.649295Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 351d0494-41da-4172-bd25-3bbf2d98a4e7 · outbound
This paper cites VEnhancer: Generative Space-Time Enhancement for Video Generation.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution VEnhancer: Generative Space-Time Enhancement for Video Generation
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T00:17:29.654857Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 33c3a37d-f1e1-444b-89d6-a26fc56748ba · outbound
This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution HunyuanVideo: A Systematic Framework For Large Video Generative Models
Reference 4
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T00:17:29.652052Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 40a6d4e9-5549-43f8-8739-6ebbb563ed2a · outbound
This paper cites DiffVSR: Revealing an Effective Recipe for Taming Robust Video Super-Resolution Against Complex Degradations.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution DiffVSR: Revealing an Effective Recipe for Taming Robust Video Super-Resolution Against Complex Degradations
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T00:17:29.641498Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation aca7a694-e983-45aa-a81f-c5cdcaaf5a92 · outbound
This paper cites Flow Matching for Generative Modeling.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution Flow Matching for Generative Modeling
Reference 6
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-03T00:17:29.638231Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 7473ff3c-23dc-4a53-a5bb-a1081628a837 · outbound
This paper cites Ntire 2019 challenge on video deblurring and super-resolution: Dataset and study.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution Ntire 2019 challenge on video deblurring and super-resolution: Dataset and study
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T17:16:44.500338Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 052945ae-22b4-4299-84f3-6da103ec1f46 · outbound
This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution Score-Based Generative Modeling through Stochastic Differential Equations
Reference 8
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-03T00:17:29.633686Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation cc50c99d-4c2c-45a0-a7ce-702911e093ea · outbound
This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution Wan: Open and Advanced Large-Scale Video Generative Models
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T00:17:29.649129Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 2a713525-41ae-4314-9492-796073ef8e62 · outbound
This paper cites VideoRoPE: What Makes for Good Video Rotary Position Embedding?.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution VideoRoPE: What Makes for Good Video Rotary Position Embedding?
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T00:17:29.629230Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation add99661-9f53-4b5c-8856-5e4b3c2d23de · outbound
This paper cites arXiv preprint arXiv:2508.08227 (2025).
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution arXiv preprint arXiv:2508.08227 (2025)
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T00:17:29.646914Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation af08fef3-0528-45d7-bce0-2da33fc592d3 · outbound
This paper cites STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution
Reference 12
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T00:17:29.626720Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d51cddb7-d851-4050-b17c-02e0f5fdda9a · outbound
This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
Reference 13
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-03T00:17:29.635952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 51b49335-3ea2-4c7a-987f-6e4760a1c449 · outbound
This paper cites Exploring Diffusion Time-steps for Unsupervised Representation Learning.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution Exploring Diffusion Time-steps for Unsupervised Representation Learning
Reference 14
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T00:17:29.631468Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 47716348-de32-4bd6-a745-ef86bc3f9cc1 · outbound
This paper cites RealisVSR: Detail-enhanced Diffusion for Real-World 4K Video Super-Resolution.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution RealisVSR: Detail-enhanced Diffusion for Real-World 4K Video Super-Resolution
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T00:17:29.652011Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 70ad99ca-06be-4d5b-ac7b-5faf20c8bb3a · outbound
This paper cites Open-Sora: Democratizing Efficient Video Production for All.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution Open-Sora: Democratizing Efficient Video Production for All
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T00:17:29.646753Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation fdeb6d1e-7c1d-462c-9f6c-3e47d9cda335 · outbound
This paper cites Flashvsr: Towards real- time diffusion-based streaming video super-resolution.
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution Flashvsr: Towards real- time diffusion-based streaming video super-resolution
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T00:17:29.618877Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b9a14ef8-b0ac-458d-a7be-860c3ae74d24 · outbound
This paper cites For DOVER, we follow the official implementation from the original paper (Wu et al., 2023).
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution For DOVER, we follow the official implementation from the original paper (Wu et al., 2023)
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T17:16:44.500338Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.