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Paper Citation Record · LEDGER

T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2405.18750.

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

pith.paper-citation-record.v1
2405.18750 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:55:28.761207Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T07:02:41.761466Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d7f15538-722a-4a8c-9e85-3090e06296c0 · inbound

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

CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 84

Resolution
verified exact
arxiv_id, observed 2026-05-10T18:26:22.324772Z

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.

source=arxiv_source observed=2026-05-10T18:26:22.224924Z digest=sha256:16a2e76aa4e5f87484eddb6e9024cb83547a8b3e9775860f5ac8b268a784575a

Observation d6ba3f1e-ce19-4a5a-96aa-163764b662ed · inbound

Emu3: Next-Token Prediction is All You Need cites this paper.

Emu3: Next-Token Prediction is All You Need T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:56:08.776459Z

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.

source=pdf_text observed=2026-05-11T10:56:06.418360Z digest=sha256:82fbf3ade168b263a470b9421e93ea0e4efa88deda10f97fe71faa75c29f28d8

Observation 90c5a284-39b7-4a49-8c32-f32ce2b82b28 · inbound

DOLLAR: Few-Step Video Generation via Distillation and Latent Reward Optimization cites this paper.

DOLLAR: Few-Step Video Generation via Distillation and Latent Reward Optimization T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-23T07:02:41.764798Z

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.

source=pdf_text observed=2026-05-23T06:57:50.897865Z digest=sha256:87224e8b7d11aa0bfd305ace960890c2de4ce67dc1eaa9f9daf9bd523b5783cf

Observation a1c60612-ad5a-42a4-a2fd-492a0722c019 · inbound

Improving Video Generation with Human Feedback cites this paper.

Improving Video Generation with Human Feedback T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-13T15:30:02.717396Z

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.

source=pdf_text observed=2026-05-13T15:30:02.578430Z digest=sha256:9219a827ecda8c3aae2abfe27f8f562a95ef03e671f60d18fcc27d55a3467b22

Observation fd030be6-b309-445a-b29d-afe56d43af43 · inbound

AlignHuman: Improving Motion and Fidelity via Timestep-Segment Preference Optimization for Audio-Driven Human Animation cites this paper.

AlignHuman: Improving Motion and Fidelity via Timestep-Segment Preference Optimization for Audio-Driven Human Animation T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T04:55:28.761207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:55:28.761207Z digest=sha256:7ec492b5aef607a463567f88148fdad9193ce156443a0319396846b584d161a5

Observation 8114b6c2-c089-4c25-a59c-d1939486774b · inbound

VQ-Insight: Teaching VLMs for AI-Generated Video Quality Understanding via Progressive Visual Reinforcement Learning cites this paper.

VQ-Insight: Teaching VLMs for AI-Generated Video Quality Understanding via Progressive Visual Reinforcement Learning T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T23:20:47.758591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:20:47.758591Z digest=sha256:f1e411849931cba01e3d74e33985b551427b7da0455243dc23e473b9837d2077

Observation 789be283-39b0-44f1-8fed-055e3d76aa16 · inbound

When Distillation Breaks Motion Control: Restoring Generative Trajectories for Fast Video Generators cites this paper.

When Distillation Breaks Motion Control: Restoring Generative Trajectories for Fast Video Generators T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T23:12:52.904057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:52.904057Z digest=sha256:c42b7948311e647dc2b3b131b24340a2466f35ec5259714fb62a5a55184847f4

Observation 122d9569-a45d-4016-860b-0db77d8a1db6 · inbound

Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling cites this paper.

Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-19T05:17:06.729045Z

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.

source=arxiv_source observed=2026-05-19T05:13:28.767788Z digest=sha256:691e85b90b71ecb8bdac6fcf8f65f6450d5482886c3518c3ab8c9f353b4044a4

Observation 07ef3d34-9444-4738-a6f1-6d3f3f07fe95 · inbound

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning cites this paper.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:41.788635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:41.788635Z digest=sha256:6adfd8fc99d700981943acf29c6446262e4a5fbbd818bba1cf2d27a5147fb691

Observation 53f460a6-c475-454f-8a14-175e3d47424d · inbound

Robust Single-Stage Fully Sparse 3D Object Detection via Detachable Latent Diffusion cites this paper.

Robust Single-Stage Fully Sparse 3D Object Detection via Detachable Latent Diffusion T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T04:36:13.480170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:36:13.480170Z digest=sha256:87602c2acc493b996ed18002b49b089a973a6190d60558527d4bd594a7d62cc4

Observation 82e642ad-4ac0-4888-ae1c-69e8054d0bf5 · inbound

RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling cites this paper.

RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-18T05:15:54.481132Z

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.

source=pdf_text observed=2026-05-18T05:13:42.934115Z digest=sha256:2653b1637dd156311387d528a02f398a5ec51413da0d54d1beadcbd4dee043d8

Observation 9133d09b-e088-45b7-8f58-df14cfd378ed · inbound

From World Action Models to Embodied Brains: A Roadmap for Open-World Physical Intelligence cites this paper.

From World Action Models to Embodied Brains: A Roadmap for Open-World Physical Intelligence T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 142

Resolution
unresolved
no resolver link, observed 2026-07-14T03:51:24.547781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T03:51:24.547781Z digest=sha256:ca8c4c6ffd14fba009006c76ccf3ce16e4f46eaff2cd120103b6265f2c2ae98d

Observation 9714246d-8506-4c44-867d-638f3bbd9dce · inbound

Reinforcement Learning: From Algorithms To Foundation Models cites this paper.

Reinforcement Learning: From Algorithms To Foundation Models T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-01T17:45:04.688549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T17:45:04.688549Z digest=sha256:24123bab1d8e81ebe9adc8f1053dddfde149f757cdea71e19be62c8a97282b23