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Paper Citation Record · LEDGER

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos

As of 5 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2605.18233.

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

pith.paper-citation-record.v1
2605.18233 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-20T10:56:16.054496Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

  • verified exact26
  • verified fuzzy7
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch6

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7bf72822-5080-420b-851a-d529b13e20a6 · outbound

This paper cites Qwen Technical Report.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Qwen Technical Report

Reference 1

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local_arxiv, observed 2026-05-20T10:58:13.818154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation ee8d22c0-0dd0-4d4c-85e8-7f1745170478 · outbound

This paper cites Hallucination of Multimodal Large Language Models: A Survey.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Hallucination of Multimodal Large Language Models: A Survey

Reference 2

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local_arxiv, observed 2026-05-20T10:58:13.821206Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation d4f79a59-b8ae-44b1-9d96-9b438a0762da · outbound

This paper cites VideoPhy: Evaluating Physical Commonsense for Video Generation.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos VideoPhy: Evaluating Physical Commonsense for Video Generation

Reference 3

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arxiv_id, observed 2026-05-20T11:34:37.994076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation df06c1ca-ac60-4a0f-ba06-b4a4dabf0efb · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 4

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local_arxiv, observed 2026-05-20T10:58:13.809378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 9895b22e-8e71-4d93-8393-df0252b27540 · outbound

This paper cites Mixture of contexts for long video generation.arXiv preprint arXiv:2508.21058.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Mixture of contexts for long video generation.arXiv preprint arXiv:2508.21058

Reference 5

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arxiv_id, observed 2026-05-20T10:58:13.815678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 80631910-00ba-4059-859c-3d9fdb17ba82 · outbound

This paper cites Taming preference mode collapse via directional decoupling alignment in diffusion reinforcement learning.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Taming preference mode collapse via directional decoupling alignment in diffusion reinforcement learning

Reference 6

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arxiv_id, observed 2026-05-20T10:58:13.824371Z

Source-reported events for the cited work

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Observation 5b606def-ba4c-466f-80ae-8fc5cc1b8416 · outbound

This paper cites arXiv preprint arXiv:2403.05131 (2024).

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos arXiv preprint arXiv:2403.05131 (2024)

Reference 7

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arxiv_id, observed 2026-05-20T10:58:13.891523Z

Source-reported events for the cited work

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source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:c126883b10fec6aebf3e66501b1c880fe3cf3c8a24fb7692aede215fbb038c99

Observation ff6f0f07-2517-47f2-a4b2-852a49b46ccd · outbound

This paper cites Sora Detector: A Unified Hallucination Detection for Large Text-to-Video Models.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Sora Detector: A Unified Hallucination Detection for Large Text-to-Video Models

Reference 8

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arxiv_id, observed 2026-05-20T10:58:13.895291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 232d82d5-f957-450c-8fad-e9b2a5c9c16b · outbound

This paper cites Autoregressive Video Generation without Vector Quantization.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Autoregressive Video Generation without Vector Quantization

Reference 9

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local_arxiv, observed 2026-05-20T10:58:13.907649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:481d01fa7c1463cdf723bd5887b9decf547a3de437efc6c7c57f8b95f2e1a732

Observation 49630e46-f1cd-4175-a4ca-d80325a94733 · outbound

This paper cites Narrlv: Towards a comprehensive narrative-centric evaluation for long video generation.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Narrlv: Towards a comprehensive narrative-centric evaluation for long video generation

Reference 10

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arxiv_id, observed 2026-05-20T10:58:13.874323Z

Source-reported events for the cited work

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Observation d3c1eaf6-efa7-43a2-897e-1a1acbdaf243 · outbound

This paper cites Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 11

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local_arxiv, observed 2026-05-20T10:58:13.877447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 1492e97f-fa78-4d5c-b19d-b503b65b9078 · outbound

This paper cites OpenAI o1 System Card.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos OpenAI o1 System Card

Reference 12

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local_arxiv, observed 2026-05-20T10:58:13.883530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation a286e2ee-b472-4cb1-913d-da0e26898084 · outbound

This paper cites How Far is Video Generation from World Model: A Physical Law Perspective.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos How Far is Video Generation from World Model: A Physical Law Perspective

Reference 13

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arxiv_id, observed 2026-05-20T11:13:41.491170Z

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source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:8b2ec610b764d96d45846c9ee160b12dad9264fadf111598d8983210de36091c

Observation f6a4f61a-6c7e-407e-89ac-e9b1594e001c · outbound

This paper cites Auto-Encoding Variational Bayes.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Auto-Encoding Variational Bayes

Reference 14

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local_arxiv, observed 2026-05-20T10:58:13.859482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:ec20de2672efa4327f9b94bdaf4862b2a36561b77f0c5a4df69008667bd92286

Observation 52e7bde3-5946-472d-b1a0-dd0e99ce460c · outbound

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

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 15

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local_arxiv, observed 2026-05-20T10:58:13.862434Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:52d5c233d425b6379cc8597088ed0eaedafc37edf47b6b4d43ccd80c542d463a

Observation 8999917c-b504-4cfe-869c-c28a8d730312 · outbound

This paper cites Exploring the Evolution of Physics Cognition in Video Generation: A Survey.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Exploring the Evolution of Physics Cognition in Video Generation: A Survey

Reference 16

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arxiv_id, observed 2026-05-20T10:58:13.865460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:50fac8f6f335a7b188c5f7719fc93fd4c214bf70641413896f6f0f954e62f37a

Observation b4b42a60-c302-4ac6-b85e-b48235c82247 · outbound

This paper cites Flow Matching for Generative Modeling.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Flow Matching for Generative Modeling

Reference 17

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local_arxiv, observed 2026-05-20T10:58:13.868114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:75f72551d97a92a2f6f5951121ebbb5be1bbbb1ab3dbea02edd49c4ada0f5807

Observation 7d0ae787-941f-4156-9080-ee5cc7c23304 · outbound

This paper cites Video-T1: Test-Time Scaling for Video Generation.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Video-T1: Test-Time Scaling for Video Generation

Reference 18

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arxiv_id, observed 2026-05-20T10:58:13.880901Z

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Observation d323e2c1-56fa-4d5c-8b5a-00321816f9c7 · outbound

This paper cites Reward Forcing: Efficient Streaming Video Generation with Rewarded Distribution Matching Distillation.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Reward Forcing: Efficient Streaming Video Generation with Rewarded Distribution Matching Distillation

Reference 19

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local_arxiv, observed 2026-05-20T10:58:13.910955Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:d083c7b537e6f1052f7432e6649eb9930c18c7c816b98ad5495eff1c4eb928d2

Observation 3093e1ce-6273-4c35-bfb4-bfca0c8723a8 · outbound

This paper cites Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps

Reference 20

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arxiv_id, observed 2026-05-20T11:45:17.785272Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:899177154fc5bf1dde2881609145d394420d791581c4b2fac59c3588a2753b8b

Observation ec071824-533c-4f7b-a38e-142ce591a7c0 · outbound

This paper cites FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling

Reference 21

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arxiv_id, observed 2026-05-20T10:58:13.849872Z

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source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:16a339a4ae2685471cf42ef81d92daac4d97e3a20e43eb8151609cdd414086e5

Observation 92ba20b9-5292-4fef-a1d8-6803b6cf4272 · outbound

This paper cites Denoising Diffusion Implicit Models.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Denoising Diffusion Implicit Models

Reference 22

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local_arxiv, observed 2026-05-20T10:58:13.846474Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:aefa8054641cf6b84873583361c1b958bb5fcd96771a9292f4edd75b0f3a79e1

Observation 91ef9cb6-7633-453b-a010-29cc39832092 · outbound

This paper cites MAGI-1: Autoregressive Video Generation at Scale.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos MAGI-1: Autoregressive Video Generation at Scale

Reference 23

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local_arxiv, observed 2026-05-20T10:58:13.898251Z

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source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:ddd58e621904143c13b087f7a807b519d67ea5857eed62d34dad5d919386c369

Observation d58781dd-0f21-4123-811f-132263f24712 · outbound

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

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Wan: Open and Advanced Large-Scale Video Generative Models

Reference 24

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local_arxiv, observed 2026-05-20T10:58:13.901396Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 79e42a55-fa65-4bc7-b59c-3d1c310a73e7 · outbound

This paper cites Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-Denoising.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-Denoising

Reference 25

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arxiv_id, observed 2026-05-20T10:58:13.904551Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation ed620966-a4cf-4a2b-a333-065cb5f1806b · outbound

This paper cites Video Is Worth a Thousand Images: Exploring the Latest Trends in Long Video Generation.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Video Is Worth a Thousand Images: Exploring the Latest Trends in Long Video Generation

Reference 26

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arxiv_id, observed 2026-05-20T10:58:13.837416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 6e7b2159-26e6-463b-b6b5-d4a0da43a82f · outbound

This paper cites Imagery- search: Adaptive test-time search for video generation beyond semantic dependency constraints.arXiv preprint arXiv:2510.14847.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Imagery- search: Adaptive test-time search for video generation beyond semantic dependency constraints.arXiv preprint arXiv:2510.14847

Reference 27

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arxiv_id, observed 2026-05-20T10:58:13.843633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:c7479e531f1f44f269efac618eb7fa90c033d7c4113f24fd63ce577604fef021

Observation ef195e7e-f74a-4fbc-a190-e241234cd53f · outbound

This paper cites Captain Cinema: Towards Short Movie Generation.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Captain Cinema: Towards Short Movie Generation

Reference 28

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arxiv_id, observed 2026-05-20T10:58:13.834486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:cb7f41e1368a726ed717293794f772b38fbe90aaad88e32fe13eaecfb38efbf8

Observation fa8b0cf1-6927-426f-be09-785cc5e832e1 · outbound

This paper cites ScalingNoise: Scaling Inference-Time Search for Generating Infinite Videos.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos ScalingNoise: Scaling Inference-Time Search for Generating Infinite Videos

Reference 29

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arxiv_id, observed 2026-05-20T10:58:13.840545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:38b06d09cc6f8638aa4427507ab169ad170bd332ab12db7e1a96b4e224322fab

Observation f1d816fd-0a7f-427e-b6b0-809ffaa9a09a · outbound

This paper cites Infinity-RoPE: Action-controllable infinite video generation emerges from autoregressive self- rollout.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Infinity-RoPE: Action-controllable infinite video generation emerges from autoregressive self- rollout

Reference 30

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arxiv_id, observed 2026-05-20T10:58:13.853129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:a4d0e06f51e174b172e6b9c743b38b167e8fcf70d4f30adfd7f4f29e21d0c7f9

Observation 1b6aa264-76fe-4380-a872-7747055fc08c · outbound

This paper cites A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 31

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local_arxiv, observed 2026-05-20T10:58:13.827505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:d671389a6e57fa3983c371aef9a81c25872c81561ec56ee65a1be8585b9f9236

Observation cb5fa0c7-c061-41a7-9106-9e35672592f5 · outbound

This paper cites RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers

Reference 32

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arxiv_id, observed 2026-05-20T10:58:13.831092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:28e91b3d0fc456449b464e4d6280fd4b6b7d8392aebf57bbc7b970e2f8e0b76f

Observation bd9e5e95-3116-4957-abbe-2bae79935b88 · outbound

This paper cites an unresolved cited work.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Unresolved cited work

Reference 33

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raw_fallback, observed 2026-05-20T11:13:27.098382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:800ce8e7e63fca9ee1207965436508ccba23594b958bdbc23fd1bbbec2d7fcd1

Observation 865b276c-13d4-4765-a192-7ada97135c5e · outbound

This paper cites Analysis of Framework Unification In Sec.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Analysis of Framework Unification In Sec

Reference 34

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raw_fallback, observed 2026-05-20T11:13:27.096679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:9fda32bd915dee6baa2f5ab682a69ab61acf615cd963209f196dc81858df1412

Observation 79da99dd-c847-46b5-8a66-957f9ee8628d · outbound

This paper cites Consequently, both ϵθ(·)andϕ(·)need to store and utilize information from previous steps during each operation.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Consequently, both ϵθ(·)andϕ(·)need to store and utilize information from previous steps during each operation

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T11:13:27.094873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:9d8f0028b0e4ffe673d9eccd8b5c4d13574abdad6eaa6c57ceb8ebf4566849df

Observation afe8a9d9-c0cd-402c-a26b-6badeafe53b8 · outbound

This paper cites The main reason is that these models concatenate text and video features, and jointly interact with the noise timestep condition.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos The main reason is that these models concatenate text and video features, and jointly interact with the noise timestep condition

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T11:13:27.092810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:1ffe63d9f7243a7799b56dec37bd09cece7c12eac6ff4c3d4af4c9997ad60fb4

Observation 00f39d42-c359-4616-a0a9-b5e6df219129 · outbound

This paper cites 6 illustrates the impact of varying the number of stage 2 denoising steps on model performance, highlighting the overall score metric across different settings.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos 6 illustrates the impact of varying the number of stage 2 denoising steps on model performance, highlighting the overall score metric across different settings

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T11:13:27.090513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:3c4db57228115063fa4daad5680fc9ef8e2fc2b8dbc850ee7a5f51ca94ffc1f7

Observation 3bb13534-5cd0-4fdd-b531-9622ee58e3c1 · outbound

This paper cites Values in parentheses indicate the relative memory increase compared to VideoCrafter2.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Values in parentheses indicate the relative memory increase compared to VideoCrafter2

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T11:13:27.088300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:84cfb13f18a2991f8b5cd08916913e7aa964f2283277d5b9ecbb324d8af9429b

Observation c00134dc-d261-4241-a137-6c1a14457cb7 · outbound

This paper cites As shown in Tab.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos As shown in Tab

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T11:13:27.086441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:84d9e4cb80a4ff8d751ecc61d36394a5e38ca0965842f325044e26db42ca9ef5

Observation 23779921-3727-40d9-962a-3ca0e96d1e7b · outbound

This paper cites Such issues are not only specific to long video generation tasks but also represent a major challenge for the entire field of video generation (Kang et al., 2024).

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos Such issues are not only specific to long video generation tasks but also represent a major challenge for the entire field of video generation (Kang et al., 2024)

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T11:13:27.084652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-20T10:56:16.054496Z digest=sha256:42223afaa2ff501ae19a7fcae92613a6170d60f8c01800e62f56c9d0509a2a6f

Pith citing papers

No inbound Pith citation observations are available.