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Paper Citation Record · LEDGER

TokensGen: Harnessing Condensed Tokens for Long Video Generation

As of 14 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 2 inbound Pith citation observations for arXiv:2507.15728.

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

pith.paper-citation-record.v1
2507.15728 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:28:31.486489Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T07:06:33.290588Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

50 of 50 outbound references displayed

  • verified exact1
  • verified fuzzy18
  • unresolved31
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6b8d15a0-cc9f-41cf-b0e3-e53ac45b2ba4 · outbound

This paper cites https://kling.kuaishou.com/, 2024.

TokensGen: Harnessing Condensed Tokens for Long Video Generation https://kling.kuaishou.com/, 2024

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:28:36.123355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:27.698569Z digest=sha256:b9e1916813a32cb0db9616f9d7273ca798fe9dcaace8e95e9558723bc2dafdd9

Observation 7d6b37a8-8c03-4b72-9a82-de27b97c9318 · outbound

This paper cites an unresolved cited work.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-06T15:28:35.900536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:27.789533Z digest=sha256:f166dd536148afe37edda6a84e854d77d4b64cbf9afbe83d194518e8835141cf

Observation 7a8932dc-2a0f-483d-8420-6a54ad56f43f · outbound

This paper cites https://openai.com/sora/, 2024.

TokensGen: Harnessing Condensed Tokens for Long Video Generation https://openai.com/sora/, 2024

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:28:35.656157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:27.878536Z digest=sha256:8a9cdf531773ee274fd53248048bb2f0af08f10788734daa635cdae459d19648

Observation d08cfed8-3d36-4475-8fc5-193b9fea421c · outbound

This paper cites chatgpt.com, 2025.

TokensGen: Harnessing Condensed Tokens for Long Video Generation chatgpt.com, 2025

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:28:35.428782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:27.972647Z digest=sha256:d7e04354b0e15712c193a7a72f670890bc43b47bc617372b4715cbfa6cfdc415

Observation 3e71f12b-8e70-4b3e-b343-180b614c8a25 · outbound

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

TokensGen: Harnessing Condensed Tokens for Long Video Generation Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T15:28:28.041932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:28.041932Z digest=sha256:3234c09d9f79b5d3be8124b459a83b76992f9a457a1ac4c8c30c2b48c49f5035

Observation 40f472b8-6b64-4fe3-8fc8-5c4418789c6e · outbound

This paper cites Generating long videos of dynamic scenes.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Generating long videos of dynamic scenes

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:28:35.223884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:28.140787Z digest=sha256:a7d65375cc590df64318fc5d7a04db9f48c499c6feed0a4e4c018953e44b718c

Observation 0c9f658c-b664-48b4-adeb-6a4a915ee9e0 · outbound

This paper cites DiTCtrl: Exploring Attention Control in Multi-Modal Diffusion Transformer for Tuning-Free Multi-Prompt Longer Video Generation.

TokensGen: Harnessing Condensed Tokens for Long Video Generation DiTCtrl: Exploring Attention Control in Multi-Modal Diffusion Transformer for Tuning-Free Multi-Prompt Longer Video Generation

Reference 7

Resolution
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no resolver link, observed 2026-08-06T15:28:28.213590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:28.213590Z digest=sha256:4d4733db1a03804705878590da4304af5c47181edb311a477b75f0f85acd7ed7

Observation 693857a8-ba06-4245-b85b-54baadb58d43 · outbound

This paper cites Pyscenedetect.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Pyscenedetect

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:28:35.012541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:28.287841Z digest=sha256:be2959d9bb6f968d77f636b853cceedd1dc6b488655baaa51b7cd10bff9cf12e

Observation d1531c13-a8bc-4b7b-9a69-ef248d72f437 · outbound

This paper cites Videocrafter2: Overcoming data limitations for high-quality video diffusion models, 2024.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Videocrafter2: Overcoming data limitations for high-quality video diffusion models, 2024

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:28:34.820307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:28.342506Z digest=sha256:941ff84f39ce143763f4899eb1d8e3fef1b1ef3a80071b85c12db8a4e3c5a3ef

Observation 181fa8ed-a762-4df1-aa84-075ffc7e5012 · outbound

This paper cites Seine: Short-to-long video diffusion model for generative transition and prediction.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Seine: Short-to-long video diffusion model for generative transition and prediction

Reference 10

Resolution
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no resolver link, observed 2026-08-06T15:28:28.395493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:28.395493Z digest=sha256:b52fa1bfea89389661c77622bbd3aeb3345fdb7469c56a5e3869f01af62e5b51

Observation 8d0e91d2-e201-4590-ba4b-df59785f3670 · outbound

This paper cites Alabdul- mohsin, Avital Oliver, Piotr Padlewski, Alexey A.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Alabdul- mohsin, Avital Oliver, Piotr Padlewski, Alexey A

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:28:34.617903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:28.470566Z digest=sha256:eb74369e56f7c3d3b4c39ad6e096c45857eb89da73c7d6210864904ee824e8ab

Observation 221a3a91-45a3-4874-acc9-aa775791021e · outbound

This paper cites ExVideo: Extending Video Diffusion Models via Parameter-Efficient Post-Tuning.

TokensGen: Harnessing Condensed Tokens for Long Video Generation ExVideo: Extending Video Diffusion Models via Parameter-Efficient Post-Tuning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T15:28:28.536008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:28.536008Z digest=sha256:dc689c5a6ece24644d01d6f0538544b3ea14c184ccb5989119768bad8c2acf1d

Observation 1999f25b-47df-49ac-9cee-01cf911b5145 · outbound

This paper cites an unresolved cited work.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-06T15:28:34.368553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:28.625330Z digest=sha256:86d76ff0a956d57c994c5b30eb089b1012842aa893cf0f7b3ca4ff95d3094ab9

Observation c54510bf-8a1c-4d13-ac92-5beb02c57d86 · outbound

This paper cites Videostu- dio: Generating consistent-content and multi-scene videos.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Videostu- dio: Generating consistent-content and multi-scene videos

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:28:34.195845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:28.669470Z digest=sha256:37d886b27d28058d475587a0cab782ce2f704ed583faf25408d7248b00cba522

Observation 780bad60-0a28-4002-aa56-1497adcd6f25 · outbound

This paper cites SparseCtrl: Adding Sparse Controls to Text-to-Video Diffusion Models.

TokensGen: Harnessing Condensed Tokens for Long Video Generation SparseCtrl: Adding Sparse Controls to Text-to-Video Diffusion Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T15:28:28.719286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:28.719286Z digest=sha256:2e6fcc5e42e38c0804dcde8e33c0604ba207525ab10af0c1a38f08f83db5854e

Observation 8f594f41-db8f-45eb-a680-4e30aa8247ec · outbound

This paper cites Animatediff: Animate your personalized text-to- image diffusion models without specific tuning.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Animatediff: Animate your personalized text-to- image diffusion models without specific tuning

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:28:34.036935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:28.826647Z digest=sha256:04b08115ffa5ab7a6f3c592d0c783e5985d4142c199d8e217f4299f4f83f5753

Observation 16efe02e-cb35-49aa-a714-bbfd5530783e · outbound

This paper cites Latent video diffusion models for high-fidelity long video generation.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Latent video diffusion models for high-fidelity long video generation

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:28:33.864953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:28.927845Z digest=sha256:bd4dc26c046d4087ef23d8f20fbc22b4467e57b5ab8a445126299ae688f1c2cd

Observation f863bcfd-ba0b-42a5-8ac1-8080db758286 · outbound

This paper cites StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text.

TokensGen: Harnessing Condensed Tokens for Long Video Generation StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T15:28:29.016923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:29.016923Z digest=sha256:efd56b32a5cecf96c36b226f6f8418477eb3bcfb841bf0fe3fcbaac3de45315c

Observation 3848cff8-4747-4c14-b7d7-c44f95fadeba · outbound

This paper cites VBench: Com- prehensive benchmark suite for video generative models.

TokensGen: Harnessing Condensed Tokens for Long Video Generation VBench: Com- prehensive benchmark suite for video generative models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T15:28:29.084392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:29.084392Z digest=sha256:8dfff34d580f2e1a704bfad2db97f803d09ca5b6fe2186f6c9f0f6d8681137ab

Observation 3b1116f8-421f-4161-86d7-0ff257d86b9d · outbound

This paper cites VBench++: Comprehensive and Versatile Benchmark Suite for Video Generative Models.

TokensGen: Harnessing Condensed Tokens for Long Video Generation VBench++: Comprehensive and Versatile Benchmark Suite for Video Generative Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T15:28:29.174408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:29.174408Z digest=sha256:51cbe2e6ce5a1be6e341be89f38ff09dc190bae5dad18c4516943bbc19446438

Observation 249be0f2-6a35-4326-af29-f02ca811d21a · outbound

This paper cites Pyramidal flow matching for efficient video generative modeling.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Pyramidal flow matching for efficient video generative modeling

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T15:28:29.218063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:29.218063Z digest=sha256:d88ddcb3a67e6eae0eae8e28b52db15350d331ec2ff9f76b22452d6bf1a062b4

Observation 4ae3edc4-061a-4155-ad5f-fa476cbebca3 · outbound

This paper cites Miradata: A large-scale video dataset with long durations and structured captions, 2024.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Miradata: A large-scale video dataset with long durations and structured captions, 2024

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:28:33.711098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:29.269154Z digest=sha256:3dd930ea8c8739118c16f77a103498c65f093a4da9cf5bfb37a8436041f43936

Observation c832b773-4ed9-43a7-97ca-f3961f4551f1 · outbound

This paper cites FIFO-Diffusion: Generating Infinite Videos from Text without Training.

TokensGen: Harnessing Condensed Tokens for Long Video Generation FIFO-Diffusion: Generating Infinite Videos from Text without Training

Reference 23

Resolution
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no resolver link, observed 2026-08-06T15:28:29.382296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:29.382296Z digest=sha256:53cb8c5552b618352fa6227c3b3a04814c4e8637f8c3518f46fa292d91cf2e31

Observation 0531271c-a2f0-419a-a0ef-b55e68c7cf00 · outbound

This paper cites Auto-Encoding Variational Bayes.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Auto-Encoding Variational Bayes

Reference 24

Resolution
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no resolver link, observed 2026-08-06T15:28:29.502212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:29.502212Z digest=sha256:445cff9c4f4fd4194fad5465a2d7e28666e5cf7a43ee225667531b26d98e1766

Observation 4cc786b5-208d-4086-8437-b1060560bcac · outbound

This paper cites Open-Sora Plan: Open-Source Large Video Generation Model.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Open-Sora Plan: Open-Source Large Video Generation Model

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T15:28:29.555990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:29.555990Z digest=sha256:4deb7c607811acf592db225edddb596b0d25ae12539d9bc084fd62faf115cc62

Observation 94655e04-eda0-40d0-9846-d5f652f16340 · outbound

This paper cites Videodirectorgpt: Consistent multi-scene video generation via llm-guided planning.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Videodirectorgpt: Consistent multi-scene video generation via llm-guided planning

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:28:33.512729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:29.634240Z digest=sha256:31aebd7ee18a17800b1b80d98ec322da4bb12a1c818ade7847ced9cff3af3f42

Observation d2b20662-2cda-4d85-9335-52c9a7fc8462 · outbound

This paper cites FreeLong: Training-Free Long Video Generation with SpectralBlend Temporal Attention.

TokensGen: Harnessing Condensed Tokens for Long Video Generation FreeLong: Training-Free Long Video Generation with SpectralBlend Temporal Attention

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T15:28:29.693518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:29.693518Z digest=sha256:200ab3d8588c4d9d7dace3fddaf3f2a7dbdaced41a332ec2328351c5b3f5f04e

Observation 4b697eee-44f4-4b1f-9333-196137b71b5d · outbound

This paper cites Latte: Latent Diffusion Transformer for Video Generation.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Latte: Latent Diffusion Transformer for Video Generation

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T15:28:29.772044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:29.772044Z digest=sha256:9fd1785302877384732373fc442d19c44cf0b58ec07b69923bcf1ed148cacf27

Observation cd3b24b7-519f-4c8c-9e91-e2a0ec074014 · outbound

This paper cites Tuning-Free Long Video Generation via Global-Local Collaborative Diffusion.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Tuning-Free Long Video Generation via Global-Local Collaborative Diffusion

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:28:31.802642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:29.815825Z digest=sha256:158b5c2146662cfa7ec3fdefec276996e858985871696f4d5cc052ea4f5e06ef

Observation 7eb421af-573a-406e-9532-2e491f83c27a · outbound

This paper cites Freenoise: Tuning-free longer video diffusion via noise rescheduling, 2023.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Freenoise: Tuning-free longer video diffusion via noise rescheduling, 2023

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:28:33.306331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:29.882776Z digest=sha256:5bd79704b3e827456def91761f19d985812ee2f90de34328769e4f8e747492cd

Observation fd57168a-2864-466b-bb1e-4d5753f928b0 · outbound

This paper cites Rolling Diffusion Models.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Rolling Diffusion Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T15:28:29.959732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:29.959732Z digest=sha256:49ead4466c166b9fe760fa681ab1f14e4130370344636bd174b72126fc91b8a8

Observation 5854ad69-242f-4937-87db-c21142f337ff · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Roformer: Enhanced transformer with rotary position embedding

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T15:28:30.079674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:30.079674Z digest=sha256:264e23f7e8106ecc475a558bd615b9b87340c364cf62a992d0479b67de3d44b0

Observation 3c30ae6f-238c-4a9e-91c6-1a5e4a8fa7f2 · outbound

This paper cites Video-Infinity: Distributed Long Video Generation.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Video-Infinity: Distributed Long Video Generation

Reference 33

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unresolved
no resolver link, observed 2026-08-06T15:28:30.162287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:30.162287Z digest=sha256:2a43b634f1c1c1871657cd82faed6a84211577eef986925bfec7f2bbb06fff51

Observation 6b68542f-f5df-47d4-b151-885b4e37bb24 · outbound

This paper cites an unresolved cited work.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-06T15:28:33.100424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:30.218238Z digest=sha256:240e2e1436a2431868c97601ba001adb2f5abac4636332c62dc6974dccd9143b

Observation adf452e4-f75a-47c8-acc9-3d2f8b7465db · outbound

This paper cites VideoTetris: Towards Compositional Text-to-Video Generation.

TokensGen: Harnessing Condensed Tokens for Long Video Generation VideoTetris: Towards Compositional Text-to-Video Generation

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T15:28:30.276884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:30.276884Z digest=sha256:6fb0af80a3b8e20586a55410297c78109481876c7f52c26f5fc5478d673f693e

Observation 05b365b8-e324-4737-876f-a97c2bcbaab0 · outbound

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

TokensGen: Harnessing Condensed Tokens for Long Video Generation Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-Denoising

Reference 36

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source=pdf_text observed=2026-08-06T15:28:30.321287Z digest=sha256:35d1c1dbdd6b142091fe82b6cf946e0e96a3dc88fc22aa3e1ad8bef9040d3107

Observation 58416333-b7fe-4c73-bf81-aaf5dcbd7b29 · outbound

This paper cites ModelScope Text-to-Video Technical Report.

TokensGen: Harnessing Condensed Tokens for Long Video Generation ModelScope Text-to-Video Technical Report

Reference 37

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source=pdf_text observed=2026-08-06T15:28:30.394069Z digest=sha256:0b46c07082c056f30e2ad2234f49f79d863e156aa639f12f289c5b4633cc2710

Observation be357ccc-b38b-4148-8931-1879725f5f54 · outbound

This paper cites Lavie: High-quality video generation with cascaded latent diffusion models.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Lavie: High-quality video generation with cascaded latent diffusion models

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-06T15:28:32.911714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:30.510792Z digest=sha256:706ee690521f31e453271beb32c1af9ea6ae507a80f22f6b5a7dc0a967177b2e

Observation 7f4c72cf-7aea-430b-bf5e-81a1e9075b20 · outbound

This paper cites Loong: Generating Minute-level Long Videos with Autoregressive Language Models.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Loong: Generating Minute-level Long Videos with Autoregressive Language Models

Reference 39

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source=pdf_text observed=2026-08-06T15:28:30.643014Z digest=sha256:e70d34536835df3106ba130086f70f27992f02849b9f485d66f87e7c9c7714e1

Observation a55a1ef5-243e-4225-8e2c-e6d197cf0489 · outbound

This paper cites Progressive Autoregressive Video Diffusion Models.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Progressive Autoregressive Video Diffusion Models

Reference 40

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source=pdf_text observed=2026-08-06T15:28:30.696472Z digest=sha256:923cfec24d724fce5f363c70a66a7e65d6456db3404b433acf659dcb20d71cf1

Observation 1adb4979-161f-43d2-bfb0-70a793f893dd · outbound

This paper cites DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors.

TokensGen: Harnessing Condensed Tokens for Long Video Generation DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors

Reference 41

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source=pdf_text observed=2026-08-06T15:28:30.738068Z digest=sha256:8c071489afe31a2a9c5cf0d041c5fcf7fc5c8bac3422b09fc8b985427290fac2

Observation e36c13c2-ca72-401b-a968-8c2d73967b3a · outbound

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

TokensGen: Harnessing Condensed Tokens for Long Video Generation CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 42

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source=pdf_text observed=2026-08-06T15:28:30.848440Z digest=sha256:ebe04c6b2e118b322716c31b54916764587c7c5a0f50951d4303f4056bab33ed

Observation 6440d349-3cd5-4a3e-bff8-67b44d7502f6 · outbound

This paper cites NUWA-XL: Diffusion over Diffusion for eXtremely Long Video Generation.

TokensGen: Harnessing Condensed Tokens for Long Video Generation NUWA-XL: Diffusion over Diffusion for eXtremely Long Video Generation

Reference 43

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source=pdf_text observed=2026-08-06T15:28:30.902462Z digest=sha256:8fe6fc00db76f771e1ed3c7f6d5945aebd765c94cebefa3929960cbf87c6b634

Observation 88f54eef-26d3-45ad-9c29-10bcbc1eef69 · outbound

This paper cites From slow bidirectional to fast causal video generators.

TokensGen: Harnessing Condensed Tokens for Long Video Generation From slow bidirectional to fast causal video generators

Reference 44

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source=pdf_text observed=2026-08-06T15:28:30.967710Z digest=sha256:91853dd0df95f7480c5c8055413622650b66544d1b83e799c9ec35a0065df3cf

Observation 7be0dcfb-ac0f-4300-97f5-7a2bdaa28b53 · outbound

This paper cites Mora: Enabling Generalist Video Generation via A Multi-Agent Framework.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Mora: Enabling Generalist Video Generation via A Multi-Agent Framework

Reference 45

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source=pdf_text observed=2026-08-06T15:28:31.054557Z digest=sha256:133d5cbf88a4a172bd86f25ab97af552f77d675ae9fd31c1ade66a2a584b0b6e

Observation c42ed040-268e-47f8-a811-2afb30564af4 · outbound

This paper cites I2vgen-xl: High-quality image-to-video syn- thesis via cascaded diffusion models.

TokensGen: Harnessing Condensed Tokens for Long Video Generation I2vgen-xl: High-quality image-to-video syn- thesis via cascaded diffusion models

Reference 46

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:31.108134Z digest=sha256:8dd49374c95ad936ac9f980542b70e1c486861a5f14d2cd5fdcf47812f5d235c

Observation 67abd083-9273-43f4-a082-cc3eaab5c16b · outbound

This paper cites Moviedreamer: Hier- archical generation for coherent long visual sequence, 2024.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Moviedreamer: Hier- archical generation for coherent long visual sequence, 2024

Reference 47

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:31.200019Z digest=sha256:e61a427714dfc675c467a6a7cbeed91c38db17035357e1320c1f607c20f9cce8

Observation c66d2837-da08-4504-a942-e34e054e82d0 · outbound

This paper cites Open-sora: Democratizing efficient video production for all, 2024.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Open-sora: Democratizing efficient video production for all, 2024

Reference 48

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verified fuzzy
raw_fallback, observed 2026-08-06T15:28:32.364448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:31.301863Z digest=sha256:57651d6138de97c68770af3e25b5ab9f038bbfb81ceabe85a6115f0d50c95bf6

Observation 10b6a484-1add-4249-8798-aefbda007d62 · outbound

This paper cites Storydiffusion: Consistent self-attention for long-range image and video generation.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Storydiffusion: Consistent self-attention for long-range image and video generation

Reference 49

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verified fuzzy
raw_fallback, observed 2026-08-06T15:28:32.202605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T15:28:31.365833Z digest=sha256:bd29e8e6bb3576e7085572a4cae2e8ffd6c30138cb2eac3175b9132d4cdc50a6

Observation 5a541034-3ac2-4f29-be2c-ea9415702346 · outbound

This paper cites Vlogger: Make Your Dream A Vlog.

TokensGen: Harnessing Condensed Tokens for Long Video Generation Vlogger: Make Your Dream A Vlog

Reference 50

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source=pdf_text observed=2026-08-06T15:28:31.486489Z digest=sha256:c7df3e1049bc77b5b2de6b9c8ba6c2eb3ec4f4db10fdcc08489aa90965cb201b

Pith citing papers

Observation 7d9ec9f4-a98d-4d5d-a104-8b8b3f0b6ac0 · inbound

SemanticAudio: Audio Generation and Editing in Semantic Space cites this paper.

SemanticAudio: Audio Generation and Editing in Semantic Space TokensGen: Harnessing Condensed Tokens for Long Video Generation

Reference 23

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source=pdf_text observed=2026-08-03T07:06:33.290588Z digest=sha256:ddf1d4b4148740f89b3e4771c0256d718c8c8e5d70bd5a905e3b9d0e9ab3a838

Observation be4158ea-3211-4fb7-8778-99ffce26305d · inbound

LatSearch: Latent Reward-Guided Search for Faster Inference-Time Scaling in Video Diffusion cites this paper.

LatSearch: Latent Reward-Guided Search for Faster Inference-Time Scaling in Video Diffusion TokensGen: Harnessing Condensed Tokens for Long Video Generation

Reference 39

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source=pdf_text observed=2026-07-14T21:09:36.040879Z digest=sha256:b41c732a55f3b46c3dfa2e8cef5d664f300a09c546f3bf630f4dccb98502596c