Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-25T04:34:58.052261Z
Paper Citation Record · LEDGER
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation
As of 13 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2605.23271.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T13:41:47.645087Z
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
18 of 18 outbound references displayed
- verified exact15
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch3
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 6455ac7b-2013-41de-9d9a-edf433af8d3e · outbound
This paper cites Qwen3-VL Technical Report.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation Qwen3-VL Technical Report
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T04:35:20.698662Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 6828905e-a7c2-4479-a955-dce2b689f442 · outbound
This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T04:35:20.730209Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation c7f8c163-c5d7-4198-8621-1a406d76f5bf · outbound
This paper cites Agneet Chatterjee, Rahim Entezari, Maksym Zhuravinskyi, Maksim Lapin, Reshinth Adithyan, Amit Raj, Chitta Baral, Yezhou Yang, and Varun Jampani.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation Agneet Chatterjee, Rahim Entezari, Maksym Zhuravinskyi, Maksim Lapin, Reshinth Adithyan, Amit Raj, Chitta Baral, Yezhou Yang, and Varun Jampani
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:35:20.719528Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 2ffd9576-db17-4bfc-98b5-5ab01fa5990b · outbound
This paper cites LTX-Video: Realtime Video Latent Diffusion.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation LTX-Video: Realtime Video Latent Diffusion
Reference 4
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T04:35:20.708025Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation fe31804c-6963-4d3e-b907-2b5a11e16710 · outbound
This paper cites Datbench: Discriminative, faithful, and efficient vlm evaluations.arXiv preprint arXiv:2601.02316.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation Datbench: Discriminative, faithful, and efficient vlm evaluations.arXiv preprint arXiv:2601.02316
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:35:20.703389Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 33c77a3a-bff1-4259-99ff-af06a7cb8322 · outbound
This paper cites A survey of reinforcement learning from human feedback.arXiv preprint arXiv:2312.14925.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation A survey of reinforcement learning from human feedback.arXiv preprint arXiv:2312.14925
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:35:20.679663Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 5bbe3152-a4d0-44f3-984b-dd352996c758 · outbound
This paper cites YOLOv11: An Overview of the Key Architectural Enhancements.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation YOLOv11: An Overview of the Key Architectural Enhancements
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T04:35:20.694454Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 37f9ec9a-566a-4474-8ffe-401ac2abc228 · outbound
This paper cites Team Seawead, Ceyuan Yang, Zhijie Lin, Yang Zhao, Shanchuan Lin, Zhibei Ma, Haoyuan Guo, Hao Chen, Lu Qi, Sen Wang, et al.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation Team Seawead, Ceyuan Yang, Zhijie Lin, Yang Zhao, Shanchuan Lin, Zhibei Ma, Haoyuan Guo, Hao Chen, Lu Qi, Sen Wang, et al
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-25T04:35:20.641809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation b8fc1b3f-e690-47fd-bbad-003a7e0250c8 · outbound
This paper cites DINOv2: Learning Robust Visual Features without Supervision.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation DINOv2: Learning Robust Visual Features without Supervision
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T04:35:20.655424Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 1503a620-d6a1-4d58-85e2-8bbdb72392fc · outbound
This paper cites Qianqian Qiao, DanDan Zheng, Yihang Bo, Bao Peng, Heng Huang, Longteng Jiang, Huaye Wang, Jingdong Chen, Jun Zhou, and Xin Jin.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation Qianqian Qiao, DanDan Zheng, Yihang Bo, Bao Peng, Heng Huang, Longteng Jiang, Huaye Wang, Jingdong Chen, Jun Zhou, and Xin Jin
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:35:20.668383Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 1ce8ddf9-9b2c-4995-877f-b7434f284fb3 · outbound
This paper cites Msvbench: Towards human-level evaluation of multi-shot video generation.arXiv preprint arXiv:2602.23969.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation Msvbench: Towards human-level evaluation of multi-shot video generation.arXiv preprint arXiv:2602.23969
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:35:20.713935Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 8e3a2508-8f77-42fb-b711-8487476808ed · outbound
This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation HunyuanVideo: A Systematic Framework For Large Video Generative Models
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T04:35:20.725114Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation b3ba6e2a-1fb4-486f-baa0-b95c3f23d93c · outbound
This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation Wan: Open and Advanced Large-Scale Video Generative Models
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T04:35:20.689738Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 71913a7a-57d9-4af1-97d2-c238a6b37849 · outbound
This paper cites Xierui Wang, Siming Fu, Qihan Huang, Wanggui He, and Hao Jiang.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation Xierui Wang, Siming Fu, Qihan Huang, Wanggui He, and Hao Jiang
Reference 14
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-25T04:35:20.735446Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation a5b5b38b-ce19-4a43-9470-27871902ffb2 · outbound
This paper cites Automated Movie Generation via Multi-Agent CoT Planning.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation Automated Movie Generation via Multi-Agent CoT Planning
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:35:20.684884Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 9cd7a3cc-694b-4efc-9ced-bf62dfd59a74 · outbound
This paper cites DanceGRPO: Unleashing GRPO on Visual Generation.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation DanceGRPO: Unleashing GRPO on Visual Generation
Reference 16
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-25T04:35:20.673668Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 276d323f-ee54-43a1-8f14-61fa64022021 · outbound
This paper cites MuSS: A Large-Scale Dataset and Cinematic Narrative Benchmark for Multi-Shot Subject-to-Video Generation.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation MuSS: A Large-Scale Dataset and Cinematic Narrative Benchmark for Multi-Shot Subject-to-Video Generation
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T04:35:20.662842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 2823c6e8-d942-4878-b9bf-803d8a700c40 · outbound
This paper cites VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness.
EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T04:35:20.647662Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Pith citing papers
Observation 66ea7fcf-b8ec-45fb-b3fa-6c6daa835767 · inbound
FilmWorld: Agentic Novel-to-Film Generation through Dynamic Cinematic World Modeling cites this paper.
FilmWorld: Agentic Novel-to-Film Generation through Dynamic Cinematic World Modeling EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T13:41:47.645087Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.