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Paper Citation Record · LEDGER

Seedance 1.0: Exploring the Boundaries of Video Generation Models

As of 6 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 100 inbound Pith citation observations for arXiv:2506.09113.

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

pith.paper-citation-record.v1
2506.09113 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-11T12:09:56.836351Z

measured 135 of 135 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 100 of 122 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:04:45.597865Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

35 of 35 outbound references displayed

  • verified exact19
  • verified fuzzy11
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch3

External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation f1a92246-6b1e-4b23-986f-10426f510a19 · outbound

This paper cites artificialanalysis.

Seedance 1.0: Exploring the Boundaries of Video Generation Models artificialanalysis

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T12:09:57.618946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:455b2814289ef1b9774a1a96fa69fd9e1e15c09a76383fc7f2fd8701ff68b2bf

Observation d5c09267-a97f-477a-957f-defd9962a2c4 · outbound

This paper cites an unresolved cited work.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-05-11T12:09:57.530034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:fa0d330efa8b904d74b995684db42cb286cceda217af0661b8132db731a8151f

Observation e581bb8f-9955-4ae9-b349-8eeb4957183d · outbound

This paper cites Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:09:57.425665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:c6747abdbe2667ad22ccb15b0551789fba4a05db8b1aab6b9afc59b214c0eb61

Observation e29c714d-200d-4749-9371-a7b25f9b8bd6 · outbound

This paper cites Control-a-video: Controllable text-to-video generation with diffusion models.arXiv e-prints, pages arXiv–2305.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Control-a-video: Controllable text-to-video generation with diffusion models.arXiv e-prints, pages arXiv–2305

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T12:09:57.562438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:1fa802fd69f2135a06fdcb2b8516df82f20d0977bb4fa4c0aa429c680653cd99

Observation 69695444-88fc-4740-ab88-07e534daa587 · outbound

This paper cites Scaling rectified flow transformers for high-resolution image synthesis.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Scaling rectified flow transformers for high-resolution image synthesis

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T12:09:57.579377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:988ad11992a0771110ea15dfe26f7a88dccfc386f455ac2a92207afcb53f29aa

Observation fe535cf5-5248-4b4c-9bed-a0d2e31fafea · outbound

This paper cites Seedream 3.0 Technical Report.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Seedream 3.0 Technical Report

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:55:38.865721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:232671a62a37d0f38fdd7d75c2c54cd5446c7bbe0354d8e254a48d7b046af827

Observation 92c5a32b-915c-43dd-9291-7c9f3b31253b · outbound

This paper cites Factorizing text-to-video generation by explicit image conditioning.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Factorizing text-to-video generation by explicit image conditioning

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T12:09:57.606760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:5df17e36cb7f14ede99b89e8be9f4b755b18095abd42d8b09867fda05b509872

Observation 7108a905-1b76-480a-bd92-91ea810d679f · outbound

This paper cites Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-17T08:27:36.473449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:97dc5f498c5841c6bb138209531bf7d584617f96efcc4ef35c4b8a8e3c0a91c6

Observation f7dcf032-3a38-4c2d-ac4b-43df9576d2bc · outbound

This paper cites Long Context Tuning for Video Generation.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Long Context Tuning for Video Generation

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T12:09:57.472650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:c6f7c5742ce71b280aaf88c58903aaa0120576a51786ddb78429378084d9dc5a

Observation 26c8dadb-7c13-4d0f-8dc1-499a10b12339 · outbound

This paper cites Lora: Low-rank adaptation of large language models.ICLR, 1(2):3.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Lora: Low-rank adaptation of large language models.ICLR, 1(2):3

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T12:09:57.625092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:34316015c4fc2e30eff3a54c63bcefac315403a670192cb4dd53f9f067e06f4e

Observation ef36fcb5-f384-4551-8065-5c7526039e61 · outbound

This paper cites an unresolved cited work.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-05-11T12:09:57.633798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:585a1f600dfe8864465480318c143c0e69fbf46a7f3ae6a677a65521aa44afab

Observation 053664a5-330c-4340-9721-fcd8627a4400 · outbound

This paper cites DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models.

Seedance 1.0: Exploring the Boundaries of Video Generation Models DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:07:22.650116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:c1a41dbe76d96f704dd215ce13360e19c3424dc14e07175408d602d0fc9071c1

Observation 72f5374e-f3bb-4e4e-a52b-f8e3776384a8 · outbound

This paper cites Prompt-A-Video: Prompt Your Video Diffusion Model via Preference-Aligned LLM.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Prompt-A-Video: Prompt Your Video Diffusion Model via Preference-Aligned LLM

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:09:57.496257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:2f8d49a6c3e47ded654e174692486d472112f69f36310fb9a3eb7baf17e51dd8

Observation c79c220c-83ff-4676-b612-e246647825a0 · outbound

This paper cites Auto-Encoding Variational Bayes.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Auto-Encoding Variational Bayes

Reference 14

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T12:09:57.505352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:8b70a2a42f0681498260e61f32de9e17e34a26cc434555ee04a27406e966853d

Observation f286e790-868a-4b31-baf7-0838d7eb9f09 · outbound

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

Seedance 1.0: Exploring the Boundaries of Video Generation Models HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-05-11T12:09:57.514485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:93e55dc5d931846c71671ff86a891ec0aac901aa02337b48527eff142292c939

Observation f52f8de2-5f01-4d6b-bbc9-4c4d80d2c807 · outbound

This paper cites Diffusion adversarial post-training for one-step video generation.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Diffusion adversarial post-training for one-step video generation

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:09:57.176511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:25cb29db8dd939a25a1da30293d17058fa5dd47730615c129481461a7a6f2d7c

Observation ca28bb87-9f77-4e77-a05c-0c48ba78a4a6 · outbound

This paper cites Flow-GRPO: Training Flow Matching Models via Online RL.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Flow-GRPO: Training Flow Matching Models via Online RL

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:45:17.156367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:e0bed8850a0f1bcd9b787a870668ca338371acd60a10a5941accd787f07ec6a7

Observation ef031a42-e020-4935-a8ff-b0211f96f8d5 · outbound

This paper cites Improving Video Generation with Human Feedback.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Improving Video Generation with Human Feedback

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-13T15:30:03.116566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:86afdf94952ab7a4ae81f75e3ee5c8b4d9dca09ba594ba836d0cb0735c63446b

Observation 03067ae0-5c1f-44e7-be85-52e9097d8ec5 · outbound

This paper cites Ray: A distributed framework for emerging{AI} applications.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Ray: A distributed framework for emerging{AI} applications

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T12:09:57.638649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:338039b8fb2bc7e8407966c899c2702512b66d72f1e53e9f774c83a898aabff9

Observation 8bbe251c-8baf-4b10-8d91-703253aa13f8 · outbound

This paper cites Scalable diffusion models with transformers.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Scalable diffusion models with transformers

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T12:09:57.645790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:9fd66ba75c3b5b0580aa3a44fa5c38d7c63f265c112e5641cfee7c42d9fa7841

Observation 627c0c88-7315-4960-a0e9-a01b51421f93 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.Advancesin Neural Information Processing Systems, 36:53728–53741.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Direct preference optimization: Your language model is secretly a reward model.Advancesin Neural Information Processing Systems, 36:53728–53741

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T12:09:57.657648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:f3ebd5291d062b5f13153c0e8fb3ccf812f1d6ff9ff311750b32abc25f02da36

Observation efe84ecd-8df1-4d56-b8a8-84bd72039b03 · outbound

This paper cites Hyper-sd: Trajectory segmented consistency model for efficient image synthesis.Advancesin Neural Information Processing Systems, 37:117340–117362.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Hyper-sd: Trajectory segmented consistency model for efficient image synthesis.Advancesin Neural Information Processing Systems, 37:117340–117362

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T12:09:57.544827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:ba4c473d3590dc1c897375ab78dfd2f1efae36a1403ddc6bb3a052c2a485b787

Observation 87a5b848-c908-403a-bccf-86617a6b0b49 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Seedance 1.0: Exploring the Boundaries of Video Generation Models High-resolution image synthesis with latent diffusion models

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T12:09:57.597962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:8c2dca2f51ba6527e978d4f318356faa99ae352058294dc2c0e43e007ced20ea

Observation c4ccb7b5-f4c3-41b0-ba6d-ad1f01aa7b90 · outbound

This paper cites Seaweed-7B: Cost-Effective Training of Video Generation Foundation Model.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Seaweed-7B: Cost-Effective Training of Video Generation Foundation Model

Reference 24

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T12:09:57.251803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:4c81e878fc3babf0456ae59c902c07dec0d610659b296ec6a8d1e472c4f203d7

Observation 7ece4b79-ba87-468e-ad66-86ad4fca928a · outbound

This paper cites RayFlow: Instance-Aware Diffusion Acceleration via Adaptive Flow Trajectories.

Seedance 1.0: Exploring the Boundaries of Video Generation Models RayFlow: Instance-Aware Diffusion Acceleration via Adaptive Flow Trajectories

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:09:57.294124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:05e8bfa06763ca92461e5510ed4ceea2b13bec775aca7e67babe8c2c4852d3fe

Observation bd3caeda-d13b-4025-9cbe-8e913f7c4b50 · outbound

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

Seedance 1.0: Exploring the Boundaries of Video Generation Models Wan: Open and Advanced Large-Scale Video Generative Models

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-05-11T12:09:57.307085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:a4927106062565183b062c26e6c75e5a3e02f76df6e40cadab05ae3f21f211a9

Observation 166a9564-12bd-4b09-b542-16d9920fc15a · outbound

This paper cites Training-free and Adaptive Sparse Attention for Efficient Long Video Generation.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Training-free and Adaptive Sparse Attention for Efficient Long Video Generation

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:09:57.330107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:dd1f7f8322329e4226f5d00e33655f4097e2e9b8453e136b4d829994e4e3f54f

Observation 0cfb2fe1-b763-4334-90bb-4cac6f17a111 · outbound

This paper cites DanceGRPO: Unleashing GRPO on Visual Generation.

Seedance 1.0: Exploring the Boundaries of Video Generation Models DanceGRPO: Unleashing GRPO on Visual Generation

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-11T22:28:29.121023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:66f9dc41aa96d08de59aa4fbddd685ae02ffdbe5154365f3c19fa1030ce2b665

Observation bb2abc21-bb3e-4fbb-a43a-5720389ff533 · outbound

This paper cites Qwen2.5 Technical Report.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Qwen2.5 Technical Report

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-05-11T12:09:57.365334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:78c7eb61d0dc9f9e3f8c9280a0ffe237dab8611ac7fac858846a2f534e80a044

Observation a7428aa2-2ecb-44e8-8f06-668947f5ec6b · outbound

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

Seedance 1.0: Exploring the Boundaries of Video Generation Models CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 30

Resolution
verified exact
local_arxiv, observed 2026-05-11T12:09:57.377722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:810669be649311a91cd63468603db542aa6cf1a28706df7a572eec319a38087d

Observation 988a970a-d54e-43ab-a159-202120020f99 · outbound

This paper cites Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-13T20:06:45.090605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:c438840d0a69ef1a3cf487f9b40cc8c6e45517ee9d2621cac4f5c58c40ee1f16

Observation c4a72311-99ba-4367-80b0-3e7fe61effcf · outbound

This paper cites Tarsier2: Advancing Large Vision-Language Models from Detailed Video Description to Comprehensive Video Understanding.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Tarsier2: Advancing Large Vision-Language Models from Detailed Video Description to Comprehensive Video Understanding

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:09:57.400029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:e786ef43e6581bb7326c14fd2ec37f4c72a40cb4ca04c8ffa080e897106fa8ca

Observation 1612533d-4980-44c0-81ab-3ec1c2ebfd74 · outbound

This paper cites Onlinevpo: Align video diffusion model with online video-centric preference optimization.

Seedance 1.0: Exploring the Boundaries of Video Generation Models Onlinevpo: Align video diffusion model with online video-centric preference optimization

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:09:57.409960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:93f6db0ba7ca71b30ecfe829bc3176ba493af9c10a7e3327ea74595ff65a62c6

Observation f608ec62-3fd2-4f97-8430-69b72cd4162d · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

Seedance 1.0: Exploring the Boundaries of Video Generation Models The unreasonable effectiveness of deep features as a perceptual metric

Reference 34

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verified fuzzy
raw_fallback, observed 2026-05-11T12:09:57.614433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:12a619a8443ec6e1d3700c893482f8162c4795b0391e5565c612b14dc3724345

Observation 9693bc11-1736-491c-8052-2ac7ee014da0 · outbound

This paper cites PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel.

Seedance 1.0: Exploring the Boundaries of Video Generation Models PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel

Reference 35

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verified exact
arxiv_id, observed 2026-05-12T04:15:20.153254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T12:09:56.836351Z digest=sha256:2cb1c73abe7bc1d73d15e8a40df43a17f4b6c5ed158eef8a8befc0636e21ad0b

Pith citing papers

Observation 8922e4c3-e6f5-4197-9804-2f3b4ac0e0ee · inbound

Images Speak Louder Than Scores: Failure Mode Escape for Enhancing Generative Quality cites this paper.

Images Speak Louder Than Scores: Failure Mode Escape for Enhancing Generative Quality Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 13

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unresolved
no resolver link, observed 2026-08-05T21:04:45.597865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T21:04:45.597865Z digest=sha256:11be2476b24ccae12d4b3fd5d45cce2914c382249ba212d59ed7fb61950dfa2f

Observation b7f756f0-ecec-4166-a009-15f843b2d8bf · inbound

Waver: Wave Your Way to Lifelike Video Generation cites this paper.

Waver: Wave Your Way to Lifelike Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 2024

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unresolved
no resolver link, observed 2026-08-05T17:45:15.982889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:45:15.982889Z digest=sha256:a6a0adc0d723e26ce4a7f628921376a302603b00c1b00b5799455a5c96c20b16

Observation ac7e8ec9-0175-454d-913e-dcec3f7d1e40 · inbound

UniVerse-1: Unified Audio-Video Generation via Stitching of Experts cites this paper.

UniVerse-1: Unified Audio-Video Generation via Stitching of Experts Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 25

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unresolved
no resolver link, observed 2026-08-05T00:05:47.633715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T00:05:47.633715Z digest=sha256:31231cdc4801299373f2c0deb18cc8bf530a7bc679230ae013cf5ce6e76a127f

Observation 74c364d4-1825-4b38-87bc-97a4f1befbf4 · inbound

HuMo: Human-Centric Video Generation via Collaborative Multi-Modal Conditioning cites this paper.

HuMo: Human-Centric Video Generation via Collaborative Multi-Modal Conditioning Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T20:35:30.268006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:35:30.268006Z digest=sha256:806607140306a37fc561c132ecdebc543dc733cfb416c2ca4743018524fe82e3

Observation e1ed9b66-e8ca-4b34-9f27-5433927eb701 · inbound

RewardDance: Reward Scaling in Visual Generation cites this paper.

RewardDance: Reward Scaling in Visual Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-04T20:08:56.802057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:08:56.802057Z digest=sha256:7547f39e401c6b5491daceeb3daac52990fc69d8b39dbb05994a4abf4832e213

Observation 65bfcb03-c29d-4609-902a-3507222072b9 · inbound

Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency cites this paper.

Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-18T08:51:09.216439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-18T08:46:16.541104Z digest=sha256:9b88e654ad88ff8d279bb699ee80ee0a449757a15bff6a50720a5b38e273accc

Observation edea4d0f-8dc8-424d-9fcb-f19dc243d1b4 · inbound

World Simulation with Video Foundation Models for Physical AI cites this paper.

World Simulation with Video Foundation Models for Physical AI Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-05-12T23:01:13.971409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-12T23:01:13.546110Z digest=sha256:26069ff0b02c1dfc9582defdc46814e04f12e4c1ce980464c1db14992acbedb5

Observation 25f1daf6-d3e0-4490-be20-ce21d4d09506 · inbound

One-to-All Animation: Alignment-Free Character Animation and Image Pose Transfer cites this paper.

One-to-All Animation: Alignment-Free Character Animation and Image Pose Transfer Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-05-21T18:25:28.433909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-21T18:25:22.486891Z digest=sha256:7bd71a1bc8c7ca6bc1f1e3dbcb8ebf422d7780b073b67959995fee30bc7058c4

Observation a178e001-4b93-4b05-af1d-ad038651c2e5 · inbound

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

Reward Forcing: Efficient Streaming Video Generation with Rewarded Distribution Matching Distillation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-05-16T18:17:55.148099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-16T18:17:54.943863Z digest=sha256:36515a53a54cb5b3fcff74b51c2ccbb8a856e07f6124333e32f43323b05ec6b8

Observation a2427e91-7cb3-4226-817f-967dc3685800 · inbound

VABench: A Comprehensive Benchmark for Audio-Video Generation cites this paper.

VABench: A Comprehensive Benchmark for Audio-Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-05-17T00:08:43.838103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-17T00:03:45.576961Z digest=sha256:f1f8e5a9df93d996583d219c898d12deae87674d850205d49dacb1b0f277dcc7

Observation 8e203a5e-1bed-447a-abfa-a1690171a891 · inbound

Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model cites this paper.

Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-05-16T01:35:37.855835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-16T01:35:37.817082Z digest=sha256:c9a613325958b8496097ff18c96e32102b4c63915c12d7155e29382a952cb06d

Observation e006029b-6473-437c-8f48-a8b3db3832a4 · inbound

WorldPlay: Towards Long-Term Geometric Consistency for Real-Time Interactive World Modeling cites this paper.

WorldPlay: Towards Long-Term Geometric Consistency for Real-Time Interactive World Modeling Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-15T14:29:56.480591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-15T14:29:56.348733Z digest=sha256:853d82f4d425cfa4a2fb4a8e265299f4484ed7c90ca139623ce41f6c3c8ead1c

Observation 19e8d15d-0f78-44e3-b57f-ddf305e7d8bc · inbound

WorldPlay: Towards Long-Term Geometric Consistency for Real-Time Interactive World Modeling cites this paper.

WorldPlay: Towards Long-Term Geometric Consistency for Real-Time Interactive World Modeling Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-03T16:11:11.679225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:11:11.679225Z digest=sha256:c1280b52a3bcef89148a94d056120f76e53714bbeced9f305bc627a6f2bba77a

Observation 5aec93c3-c8e7-42b8-ba4a-b621642c2242 · inbound

End-to-End Training for Autoregressive Video Diffusion via Self-Resampling cites this paper.

End-to-End Training for Autoregressive Video Diffusion via Self-Resampling Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 21

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unresolved
no resolver link, observed 2026-08-03T15:46:07.130648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:46:07.130648Z digest=sha256:d523221d216546636c4e7a2705884ccf9164f08a1beadc2da06091810d80a091

Observation 125adf6b-0bfc-4c02-ad98-02f062f89d62 · inbound

Kling-Omni Technical Report cites this paper.

Kling-Omni Technical Report Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-05-15T21:00:58.630323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-15T21:00:58.473043Z digest=sha256:d02e4e5cde1440826e4f2a43eb014417cd778a2694119071b702015e8dd11152

Observation a210b766-150a-4950-8b73-c787ec95394b · inbound

PhyGDPO: Physics-Aware Groupwise Direct Preference Optimization for Physically Consistent Text-to-Video Generation cites this paper.

PhyGDPO: Physics-Aware Groupwise Direct Preference Optimization for Physically Consistent Text-to-Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-03T13:24:44.694597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:24:44.694597Z digest=sha256:9f41f48192d3ebb2ae1960bfa75feb39c44a756c2adc4f8b9b921c43644ce233

Observation 97bf22b1-392b-4fb3-a57c-85f55b29d161 · inbound

Mind the Generative Details: Direct Localized Detail Preference Optimization for Video Diffusion Models cites this paper.

Mind the Generative Details: Direct Localized Detail Preference Optimization for Video Diffusion Models Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-16T16:28:05.513209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-16T16:25:03.743594Z digest=sha256:04b749f67a2422a869cff47db0be79e11ed1375e9753bba8519ddf4de2cce3b6

Observation ccacde97-e6a3-4c44-a409-6ee3f483f180 · inbound

Mind the Generative Details: Direct Localized Detail Preference Optimization for Video Diffusion Models cites this paper.

Mind the Generative Details: Direct Localized Detail Preference Optimization for Video Diffusion Models Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-21T16:04:14.657175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-21T16:01:52.150950Z digest=sha256:2535c225b711cbdf7f76f02b710e631cd0059168087ff7434947def6a31592fa

Observation fa53f610-9038-44a1-9482-2ca727d477f9 · inbound

TAGRPO: Boosting GRPO on Image-to-Video Generation with Direct Trajectory Alignment cites this paper.

TAGRPO: Boosting GRPO on Image-to-Video Generation with Direct Trajectory Alignment Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 8

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unresolved
no resolver link, observed 2026-08-03T11:36:13.613718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:36:13.613718Z digest=sha256:48580cde06894ff2315d8c96b234d276635c3e65b4ab2ff27cd07c84e3b231f7

Observation fd22971c-f86c-4b19-aa05-61d0514c725e · inbound

Transition Matching Distillation for Fast Video Generation cites this paper.

Transition Matching Distillation for Fast Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-03T10:35:06.167690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:35:06.167690Z digest=sha256:11c50e4ef524e8eb73734fbfd28412b6a14e4d2cbc28afef342c20d19c587316

Observation 56b12472-8b06-43e4-a442-49bbdebb060a · inbound

Advancing Open-source World Models cites this paper.

Advancing Open-source World Models Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 63

Resolution
verified exact
local_arxiv, observed 2026-05-16T09:07:00.985117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-16T09:07:00.904794Z digest=sha256:0228ccd50e6852150a52ef2412d638e4e2e760a164cf4665f9420efb1fe51989

Observation da343538-6d13-4a19-9490-fb0384b84915 · inbound

Olaf-World: Orienting Latent Actions for Video World Modeling cites this paper.

Olaf-World: Orienting Latent Actions for Video World Modeling Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-03T01:20:04.834334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T01:20:04.834334Z digest=sha256:4dd6a562839614ba6ab94be705f277c7fefacfb10a2e90505de8dcc04a2cab9e

Observation 0f0345a5-e94e-4b1c-b033-83705e4a9bdf · inbound

LUVE : Latent-Cascaded Ultra-High-Resolution Video Generation with Dual Frequency Experts cites this paper.

LUVE : Latent-Cascaded Ultra-High-Resolution Video Generation with Dual Frequency Experts Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-03T00:09:56.295258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T00:09:56.295258Z digest=sha256:516c299e8320c7f5d259bfa0280d6ceceeb062e887179b30c6c40bee71e887f4

Observation 4d23110c-0efc-4ce2-9572-b3274b78370e · inbound

Beyond End-to-End Video Models: An LLM-Based Multi-Agent System for Educational Video Generation cites this paper.

Beyond End-to-End Video Models: An LLM-Based Multi-Agent System for Educational Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 11

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unresolved
no resolver link, observed 2026-08-03T00:03:23.295524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T00:03:23.295524Z digest=sha256:14e265a692da7ec9279a8d5c6e9b811120bdb0912883b23e4b257ca78b2bf15c

Observation 68fa0439-54c3-4938-8364-d57bf529aa0a · inbound

UCM: Unified Modeling of Camera Control and Memory with Time-aware Positional Encoding Warping for World Models cites this paper.

UCM: Unified Modeling of Camera Control and Memory with Time-aware Positional Encoding Warping for World Models Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-02T20:36:09.386089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T20:36:09.386089Z digest=sha256:d5b38adb0e913b3e52ba4507d0c161712896b484fc515fddf90bd1cdcbb7b51b

Observation 8a9f8fbd-ea12-4460-a00e-c84015389eea · inbound

VIGOR: VIdeo Geometry-Oriented Reward for Temporal Generative Alignment cites this paper.

VIGOR: VIdeo Geometry-Oriented Reward for Temporal Generative Alignment Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-13T23:54:26.281624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T23:54:26.281624Z digest=sha256:2f2975e7dc21893182fdf36939cd54616a7073d584049b84c8db42d0190d9340

Observation 4d9ea67e-c501-4f67-9834-6cc79c97c396 · inbound

AHOY! Animatable Humans under Occlusion from YouTube Videos with Gaussian Splatting and Video Diffusion Priors cites this paper.

AHOY! Animatable Humans under Occlusion from YouTube Videos with Gaussian Splatting and Video Diffusion Priors Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-07-13T22:49:03.259461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T22:49:03.259461Z digest=sha256:33c747d57f4f670d34c4b67fa72b13025eb9af3e67d24c5ab0ee3c84b7f5cc2f

Observation a2023a89-760f-4435-b20e-badf22d5f0ae · inbound

Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms cites this paper.

Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-05-14T01:38:36.174540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-14T01:35:14.878069Z digest=sha256:2ad86ae0d25c520345f708795d39eb94912c908ed6fa63dff0caff4bd6faf3b3

Observation b72a6ea8-29f3-48a2-a0d3-4276991eeef3 · inbound

DWDP: Distributed Weight Data Parallelism for High-Performance LLM Inference on NVL72 cites this paper.

DWDP: Distributed Weight Data Parallelism for High-Performance LLM Inference on NVL72 Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-05-13T21:28:17.587170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-13T21:26:59.767793Z digest=sha256:343d33d30a683ed3258565e0938a0ca1042646007351d9e5c5dea929e4fd5ed1

Observation f33265c4-5c84-4978-b739-1555a104fc6d · inbound

Rethinking Position Embedding as a Context Controller for Multi-Reference and Multi-Shot Video Generation cites this paper.

Rethinking Position Embedding as a Context Controller for Multi-Reference and Multi-Shot Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-07-13T12:23:05.876881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T12:23:05.876881Z digest=sha256:8d7b8015ebb017e89fed6bfe4434168808abf2ded7948d5b9cd48812f4c5965b

Observation 38785125-45ea-4400-ab08-47c5626099d0 · inbound

OmniCamera: A Unified Framework for Multi-task Video Generation with Arbitrary Camera Control cites this paper.

OmniCamera: A Unified Framework for Multi-task Video Generation with Arbitrary Camera Control Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T20:11:35.077141Z digest=sha256:16afb67ef8b9a576402496c4c07b9ae6418dad8377e00362a346620368bd5b0e

Observation 5b6715df-3325-4fe4-ab11-0dbe987eabcb · inbound

Evolution of Video Generative Foundations cites this paper.

Evolution of Video Generative Foundations Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T18:41:38.616611Z digest=sha256:ec4d42e83946b3112aa137a29ad08fb6ba2ee58bbb2fa0fdb399b004114b69b0

Observation 6893445f-a12b-4b70-b39b-31a5e2760d37 · inbound

Not all tokens contribute equally to diffusion learning cites this paper.

Not all tokens contribute equally to diffusion learning Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T18:55:51.020912Z digest=sha256:772652467e5d1d551c9be02ab4095f9363795b5e85a613a2106b75fff4062506

Observation 3900d100-7723-4b28-ba91-34ed95964807 · inbound

ImVideoEdit: Image-learning Video Editing via 2D Spatial Difference Attention Blocks cites this paper.

ImVideoEdit: Image-learning Video Editing via 2D Spatial Difference Attention Blocks Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T17:49:33.822264Z digest=sha256:91d7ca5c82af12fa4b242042214a87e211621c2776aead9e490c38842c5ba334

Observation 11cf859b-c8b1-4f15-a041-2c12183c0997 · inbound

Long-Horizon Streaming Video Generation via Hybrid Attention with Decoupled Distillation cites this paper.

Long-Horizon Streaming Video Generation via Hybrid Attention with Decoupled Distillation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 11

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arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T16:10:54.363560Z digest=sha256:28efb9824c5bd734d891948117486ada4a6a242abf1c53e6518f387606203f44

Observation 6b7f9a8b-5771-427b-b42a-567763907f6e · inbound

Tracking High-order Evolutions via Cascading Low-rank Fitting cites this paper.

Tracking High-order Evolutions via Cascading Low-rank Fitting Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 12

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verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-05-10T15:55:27.722919Z digest=sha256:2528ab42b57d8212b5640a7a23825c782426fe5551f096b72b6975c8836d7404

Observation 37ad101b-963f-4a7c-a8de-da0a4851923c · inbound

Continuous Adversarial Flow Models cites this paper.

Continuous Adversarial Flow Models Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 15

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T15:25:53.420119Z digest=sha256:4a325a6ba812a488ff516fb9fed037e99735fdaf5b5db602423027bb2b496b86

Observation 8632b087-13c6-498e-bf7c-85d18347efe4 · inbound

Seedance 2.0: Advancing Video Generation for World Complexity cites this paper.

Seedance 2.0: Advancing Video Generation for World Complexity Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 6

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verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T13:34:36.248186Z digest=sha256:69394c672da5a2fa8eccea218181c8c7692928de23891b4cf9fc19d271ada69e

Observation 4ea6f258-5e67-49da-bf53-9c67a7da3067 · inbound

AnimationBench: Are Video Models Good at Character-Centric Animation? cites this paper.

AnimationBench: Are Video Models Good at Character-Centric Animation? Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 6

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verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T11:47:27.131584Z digest=sha256:e6288493fe9f8fde61cbd0f127c92da2416517cd978dee52f874a102397e62ef

Observation 9639c4b1-8852-45aa-890d-090ec0eb65ef · inbound

Efficient Video Diffusion Models: Advancements and Challenges cites this paper.

Efficient Video Diffusion Models: Advancements and Challenges Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 276

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verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T08:28:29.706249Z digest=sha256:cc034b8d8d6c001b0b0706ece281eb14c7aa7331605542dcedbd145cc29b4a93

Observation 5688cdf8-fe5f-463c-b86c-14fdcb0ff23d · inbound

Latent-Compressed Variational Autoencoder for Video Diffusion Models cites this paper.

Latent-Compressed Variational Autoencoder for Video Diffusion Models Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 12

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verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T15:23:19.583713Z digest=sha256:4de8dfc3e8d7cefd97591b1d4da6802abde95749531312afc0efd36cf52a42ca

Observation 996a1c68-8ff1-42fe-ae86-7646887d7502 · inbound

Motif-Video 2B: Technical Report cites this paper.

Motif-Video 2B: Technical Report Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T15:50:04.001693Z digest=sha256:85399c6d7435987b86a9cfd29cb85f742bedd37ee88c1adc870ce2c1b5d86465

Observation 85ff7eaa-b669-4c50-a985-a9482be387bd · inbound

Motif-Video 2B: Technical Report cites this paper.

Motif-Video 2B: Technical Report Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-05-21T00:13:53.102580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-21T00:12:23.096146Z digest=sha256:176b98d6e1dcefc569d63b2fe4c03a01384ab69fdafbb0837d70dba5f34c2c42

Observation d61366cd-23f7-4441-ba99-8881189cecdf · inbound

DreamShot: Personalized Storyboard Synthesis with Video Diffusion Prior cites this paper.

DreamShot: Personalized Storyboard Synthesis with Video Diffusion Prior Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 11

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verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T07:21:45.633310Z digest=sha256:bb038579fd1d8fac76711b6b4399d61b4d21db03467bb1d306080b73aaf9df11

Observation 615a1e6e-c95b-4108-a8fb-3c6143d70e22 · inbound

Memorize When Needed: Decoupled Memory Control for Spatially Consistent Long-Horizon Video Generation cites this paper.

Memorize When Needed: Decoupled Memory Control for Spatially Consistent Long-Horizon Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T04:49:44.525757Z digest=sha256:83ce715b72c0280aa2cdb26ccdf352dddf3715fa97ada177f3bf0c9e912d3e9b

Observation d1ac718d-2ca2-4251-bddc-72c778e80576 · inbound

RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation cites this paper.

RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 16

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T03:02:26.084185Z digest=sha256:e349118373128896f385c9c2c7fe5363fea6554d5d9a99537d455b87430f6650

Observation 79332d76-5aa8-4cbf-8627-ad0823d6d1e0 · inbound

RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation cites this paper.

RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 16

Resolution
metadata mismatch
local_arxiv, observed 2026-05-15T06:19:50.193493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-15T06:15:32.881140Z digest=sha256:6299f7538009e1f341508683acedc939227db7ec0a6a3ee6773267d4a33f87f3

Observation e7761890-8b9d-4960-8f5d-a0f59ec0b1ae · inbound

CityRAG: Stepping Into a City via Spatially-Grounded Video Generation cites this paper.

CityRAG: Stepping Into a City via Spatially-Grounded Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 49

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T13:11:25.505008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T02:10:54.935053Z digest=sha256:f1527dd74da6fb9975401cd3c147fb611ed31beb3b7297bbb71e9a14683152db

Observation 00900349-0fab-4ab8-922d-9ef0c77b8d09 · inbound

HumanScore: Benchmarking Human Motions in Generated Videos cites this paper.

HumanScore: Benchmarking Human Motions in Generated Videos Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 16

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T13:41:04.501565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T01:17:16.513512Z digest=sha256:d11d223709fa3e88ea2514f85024f137eb8219480ae547de905a073863628b4a

Observation 8d73c6e0-77ae-4697-8bcf-a8de3b2b7d48 · inbound

Reshoot-Anything: A Self-Supervised Model for In-the-Wild Video Reshooting cites this paper.

Reshoot-Anything: A Self-Supervised Model for In-the-Wild Video Reshooting Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 8

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verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-09T23:00:45.496971Z digest=sha256:9c6f86a5bdcf266fba9ff6c8ba0c4dead461b1ef3237a9616e87599e782e1dd9

Observation d17cae76-e52f-45db-8da0-68039e15dce5 · inbound

A Systematic Post-Train Framework for Video Generation cites this paper.

A Systematic Post-Train Framework for Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 7

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verified exact
local_arxiv, observed 2026-05-11T23:26:21.527454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-07T16:58:33.014401Z digest=sha256:1bcd2dbcf98199f1ac2b801f3f7ee0b93d176dfcab3b8c134eb6c665eeb04f29

Observation 22c86b1f-06bd-4fde-b59a-a50793a5a369 · inbound

Leveraging Verifier-Based Reinforcement Learning in Image Editing cites this paper.

Leveraging Verifier-Based Reinforcement Learning in Image Editing Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-05-12T10:06:27.478470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-07T08:00:33.307429Z digest=sha256:c1eb7f52a2a6665afadf1398e8564b323f4bd915d7b89dce41d3d4db913812e9

Observation 31b7bafa-ead6-4c8b-9a78-fd1d99fc530e · inbound

Leveraging Verifier-Based Reinforcement Learning in Image Editing cites this paper.

Leveraging Verifier-Based Reinforcement Learning in Image Editing Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-05-21T09:14:06.005580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-21T09:11:02.183133Z digest=sha256:562dac97d7b4501d8cc59712c366639b461494542b9f2d542fc62a20e25ab9c5

Observation 53fe4436-a248-41e7-aa47-662583f1cfff · inbound

VAnim: Rendering-Aware Sparse State Modeling for Structure-Preserving Vector Animation cites this paper.

VAnim: Rendering-Aware Sparse State Modeling for Structure-Preserving Vector Animation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 251

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verified exact
local_arxiv, observed 2026-05-11T17:06:04.055644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-05-09T14:05:15.742176Z digest=sha256:35975a29edad26d7cf380562a4776a0ecad89a21cc72495ad4c5dc0343a4cf49

Observation bd42a3f7-7923-433b-8703-8e962768aca8 · inbound

Motion-Aware Caching for Efficient Autoregressive Video Generation cites this paper.

Motion-Aware Caching for Efficient Autoregressive Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 12

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verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T15:40:03.605239Z digest=sha256:3359c49ad3c9863f45160efe22cba323d4d10f2bf2339648214514f813f85380

Observation 672af5f5-38b8-4ece-957e-8a2b1951cef6 · inbound

Motion-Aware Caching for Efficient Autoregressive Video Generation cites this paper.

Motion-Aware Caching for Efficient Autoregressive Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 18

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verified exact
local_arxiv, observed 2026-05-15T07:19:49.960186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-15T07:16:05.225105Z digest=sha256:931ffd437de6520f614f3621d440dc24eb8769987091a05fe238e106f345f317

Observation ccba4af7-e543-4576-ac2f-7355f1099641 · inbound

TrajShield: Trajectory-Level Safety Mediation for Defending Text-to-Video Models Against Jailbreak Attacks cites this paper.

TrajShield: Trajectory-Level Safety Mediation for Defending Text-to-Video Models Against Jailbreak Attacks Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-08T19:27:00.278658Z digest=sha256:81a9ed89f404692cfcbf97bedac77a8f8ce7086285a6d0b315010891a7f4ada2

Observation 1f35c0c1-b5bd-4c52-8e39-9e6b7a2ff45d · inbound

Video Generation with Predictive Latents cites this paper.

Video Generation with Predictive Latents Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 16

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verified exact
local_arxiv, observed 2026-05-11T16:26:09.118585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-09T16:55:54.709581Z digest=sha256:5f4a339ba041191be6a0a9b097efd19196293316a746ef08739522927ad9ef72

Observation 8688a19d-b0df-40e1-9a69-e740fc6d30f1 · inbound

Mamoda2.5: Enhancing Unified Multimodal Model with DiT-MoE cites this paper.

Mamoda2.5: Enhancing Unified Multimodal Model with DiT-MoE Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 49

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verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-08T18:26:58.696936Z digest=sha256:b843d4bfdb803a68a23ad6631d38e92455d6eed50f341525f08143d8f3ac946c

Observation ffc96837-e530-4754-9317-9a13776c6811 · inbound

AniMatrix: An Anime Video Generation Model that Thinks in Art, Not Physics cites this paper.

AniMatrix: An Anime Video Generation Model that Thinks in Art, Not Physics Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-05-12T10:56:32.127279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-08T01:23:27.990472Z digest=sha256:7b709fe8b9ae8146b47bb6ee7f7623ddcc6ff450290b1ce671ece3a025b11eae

Observation 18a32a30-21e4-4f42-8c45-08bec52de03d · inbound

AniMatrix: An Anime Video Generation Model that Thinks in Art, Not Physics cites this paper.

AniMatrix: An Anime Video Generation Model that Thinks in Art, Not Physics Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-08T19:04:02.414172Z digest=sha256:0cf675ccdbb82b9edc2ca0abb22fc90d7e8cd0d926a32153a6a9c5bf07c080fc

Observation 9224daca-c65e-40d9-bcd7-90c678a45361 · inbound

AniMatrix: An Anime Video Generation Model that Thinks in Art, Not Physics cites this paper.

AniMatrix: An Anime Video Generation Model that Thinks in Art, Not Physics Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-05-12T07:11:24.360046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-12T03:39:47.335022Z digest=sha256:9866e666951f8136d3361fbc90d5264d277b4fca134c0baa39323a30bb1d03ad

Observation 89687e5c-e8b8-42a1-8b3c-2d45f07fbade · inbound

FaithfulFaces: Pose-Faithful Facial Identity Preservation for Text-to-Video Generation cites this paper.

FaithfulFaces: Pose-Faithful Facial Identity Preservation for Text-to-Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 6

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verified exact
local_arxiv, observed 2026-05-11T17:21:09.707923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-08T17:40:00.224358Z digest=sha256:89d919b88bc0d8d5fed3149d21d177c25ce1838b8099e0ed3edc92fb6b8a34f3

Observation 1c51f09d-45a7-4df7-97ed-cd83decb5b15 · inbound

Advancing Reliable Synthetic Video Detection: Insights from the SAFE Challenge cites this paper.

Advancing Reliable Synthetic Video Detection: Insights from the SAFE Challenge Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 23

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arxiv_id, observed 2026-05-11T12:09:57.662354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T00:53:18.735506Z digest=sha256:67894a6d659f337d94319af4b5825f63f58bf15b67a4b64dc9600a21d7b3d872

Observation e83486e1-99ba-4383-9640-2d13ab7f1568 · inbound

SocialDirector: Training-Free Social Interaction Control for Multi-Person Video Generation cites this paper.

SocialDirector: Training-Free Social Interaction Control for Multi-Person Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 15

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verified exact
local_arxiv, observed 2026-05-12T07:21:23.949678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-12T03:28:30.471533Z digest=sha256:e7cce2a1c99705266b537885cb7b6082adcb556ca76d28456c7e418748483fe9

Observation f5f114ce-7341-40da-bcc2-94d833f745f2 · inbound

WorldReasonBench: Human-Aligned Stress Testing of Video Generators as Future World-State Predictors cites this paper.

WorldReasonBench: Human-Aligned Stress Testing of Video Generators as Future World-State Predictors Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-05-12T07:11:25.269393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-12T03:39:01.254916Z digest=sha256:17ef0553aeab4f8c95ccddd5625322db8d1db79b1d32097b04714a6e4a8d0b16

Observation 6b92c864-7b56-4f74-9f74-690f737ad70f · inbound

TeDiO: Temporal Diagonal Optimization for Training-Free Coherent Video Diffusion cites this paper.

TeDiO: Temporal Diagonal Optimization for Training-Free Coherent Video Diffusion Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 15

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verified exact
local_arxiv, observed 2026-05-15T04:59:44.947343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-15T04:59:34.046044Z digest=sha256:79635badd1816af1b3dfee209033c7736d6ad85ccbb17dba145023aee4f8058e

Observation 1b3b0056-23d7-42a0-a7d6-38ba1fd01d67 · inbound

PhyMotion: Structured 3D Motion Reward for Physics-Grounded Human Video Generation cites this paper.

PhyMotion: Structured 3D Motion Reward for Physics-Grounded Human Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-05-15T02:49:41.394047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-15T02:49:21.291716Z digest=sha256:d93441e487e11a3c0df362ce289422754022d642252eb046450d1411eb9b3475

Observation fd846be1-e966-4be7-aa57-7a7d22b61a82 · inbound

EverAnimate: Minute-Scale Human Animation via Latent Flow Restoration cites this paper.

EverAnimate: Minute-Scale Human Animation via Latent Flow Restoration Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-06-30T21:25:04.921322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T21:21:58.123630Z digest=sha256:6f7a1527d733f5900d7b165ea0f3513038d5fe3e5bc475b717e69c365d803b67

Observation da520bb7-503d-430c-be6b-adbd44814b3a · inbound

RAVEN: Real-time Autoregressive Video Extrapolation with Consistency-model GRPO cites this paper.

RAVEN: Real-time Autoregressive Video Extrapolation with Consistency-model GRPO Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-07-01T14:35:47.215138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T20:38:28.328436Z digest=sha256:4f3113426eeb458ff093206ecb0bdc99d30bbd23d6a1b7bacaa59b8182b4350a

Observation 8b9f42a3-0eca-4de5-9dc2-ff96bb728f22 · inbound

A3D: Agentic AI flow for autonomous Accelerator Design cites this paper.

A3D: Agentic AI flow for autonomous Accelerator Design Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-05-19T16:23:08.515765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-19T16:23:07.321817Z digest=sha256:9fca05c5ea1de0646393add9ea7d864e8608a51d65be4cd3e93d9bb563593077

Observation 45f64739-0247-4cfb-b7ce-f535b88c81de · inbound

Flash-GRPO: Efficient Alignment for Video Diffusion via One-Step Policy Optimization cites this paper.

Flash-GRPO: Efficient Alignment for Video Diffusion via One-Step Policy Optimization Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:28:52.852485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-20T18:28:06.253200Z digest=sha256:5e30503cd7b09ab7da0b0c36a5fabd3b0f7822ac8f8974d62fd841f1e44df9ba

Observation d2722a7b-4034-4218-9495-9a73b94f50cd · inbound

Flash-GRPO: Efficient Alignment for Video Diffusion via One-Step Policy Optimization cites this paper.

Flash-GRPO: Efficient Alignment for Video Diffusion via One-Step Policy Optimization Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-06-30T19:45:00.977095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T19:37:18.563704Z digest=sha256:24e8156db426c8ba7abe32a4792ec6b6d0529913038da7e65b23a96f526a54d5

Observation 9d4839fd-97af-445d-ad7f-a84ba8a67f84 · inbound

Image-to-Video Diffusion: From Foundations to Open Frontiers cites this paper.

Image-to-Video Diffusion: From Foundations to Open Frontiers Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-05-20T15:08:25.044183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-20T15:06:02.084336Z digest=sha256:24ed59c36d3baa6b9208b4273042427f1224e4d0c85eb20432fb185439323d93

Observation d16ae3ac-b188-4de7-9c67-c832642d87ca · inbound

Tweedie's Formulae and Diffusion Generative Models Beyond Gaussian cites this paper.

Tweedie's Formulae and Diffusion Generative Models Beyond Gaussian Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-05-20T03:23:00.906823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-20T03:20:14.232357Z digest=sha256:8a929460b6e90580ab79eb470872293dc35179e2352724ef263cd79ae1d13a90

Observation f2d7432c-eb3f-4958-a2c9-65baed3d9fb7 · inbound

Precise: SDE-Consistent Stochastic Sampling for RL Post-Training of Flow-Matching Models cites this paper.

Precise: SDE-Consistent Stochastic Sampling for RL Post-Training of Flow-Matching Models Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-25T05:05:22.143581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-25T05:05:09.178674Z digest=sha256:41504c5f79b7f2fe7173e1a8d735c79f993dd1b4063d156b5af8adedcc8c89f7

Observation 9d28e263-4cfb-4f3c-b862-6d752477acfc · inbound

EM-Vid: Training-Free Entity-Centric Memory for Efficient and Consistent Multi-Shot Video Generation cites this paper.

EM-Vid: Training-Free Entity-Centric Memory for Efficient and Consistent Multi-Shot Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 3

Resolution
metadata mismatch
local_arxiv, observed 2026-05-25T05:00:22.359546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-25T04:57:13.479165Z digest=sha256:f2239cf72cd21d20f5c340b2b9720913ffad15ecd6096beb2b6d2fab5e185360

Observation d74c5ef8-b9a3-4d02-96d8-5d6cdc9fd9b6 · inbound

LaMo: Self-Supervised Latent Motion Priors for Physical Realism in Video Generation cites this paper.

LaMo: Self-Supervised Latent Motion Priors for Physical Realism in Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-05-25T04:45:20.439438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-25T04:42:32.717968Z digest=sha256:0688cdcda562edae19d6897c55ba5046b98c787b3f4ba152ecd3a90490170180

Observation d688b603-ab28-4550-84a4-67e3f911945a · inbound

Smart-Insertion-V: Photorealistic Video Insertion via a Closed-Loop Feedback Dual-Stream Framework cites this paper.

Smart-Insertion-V: Photorealistic Video Insertion via a Closed-Loop Feedback Dual-Stream Framework Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-05-25T04:35:21.913747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-25T04:30:20.593882Z digest=sha256:8ef196a0fa1b0f73b54f1733a16606df15ab977bb8aa570b0980ba3370544005

Observation cc94ef7f-e915-4333-9d95-97c365fd6276 · inbound

MTAVG-Bench 2.0: Diagnosing Failure Modes of Cinematic Expressiveness in Multi-Talker Audio-Video Generation cites this paper.

MTAVG-Bench 2.0: Diagnosing Failure Modes of Cinematic Expressiveness in Multi-Talker Audio-Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-06-29T13:03:26.191814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-29T12:58:56.555335Z digest=sha256:ecd10423d90d76dc0bb2bc8d67882a2f77da1ddc32ee046991fff2f225634b7f

Observation c594143b-0f3c-4587-8f48-1f90d0c43d63 · inbound

Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players cites this paper.

Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-06-29T13:53:29.104907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-29T13:34:03.020051Z digest=sha256:d7d3d529d367db652b500c7be6f3802127e83e943cc0db17f396d2262ecc3f21

Observation 31a20469-788d-47df-b70d-f0ee279a9011 · inbound

SANA-Streaming: Real-time Streaming Video Editing with Hybrid Diffusion Transformer cites this paper.

SANA-Streaming: Real-time Streaming Video Editing with Hybrid Diffusion Transformer Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-06-29T07:43:13.653893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-29T07:39:41.553623Z digest=sha256:18209658e91f00fc7fd500e7075a563ebcc3848acba681216624a9fb59d939ff

Observation ac415f27-0fd9-47b1-b059-cafb1f24c8f7 · inbound

CameraNoise: Enabling Faithful Camera Control in Video Diffusion through Geometry-Flow-Guided Noise Warping cites this paper.

CameraNoise: Enabling Faithful Camera Control in Video Diffusion through Geometry-Flow-Guided Noise Warping Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-06-28T23:22:46.706224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-28T23:21:12.987597Z digest=sha256:7a982f5e550f6d25dede8aac0c377741f80dbb59fdef024a0fb0bd0f92bd9ed4

Observation e8886b14-d5b2-4067-b17e-d1c2ba532b62 · inbound

Dexterity-BEV: Aligning 3D World and Actions for Generalizable Robot Policies Learning cites this paper.

Dexterity-BEV: Aligning 3D World and Actions for Generalizable Robot Policies Learning Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-07-01T23:06:20.416880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-28T14:41:50.084254Z digest=sha256:79365341f39fe23dc27bfaec82464384a6abd899373c8edae3eb3e1bf7c3bc82

Observation 4adca9f7-ab3f-4812-8cfb-f7c74c3fe290 · inbound

VLMs are Good Teachers for Video Reasoning via Adaptive Test-Time Optimization cites this paper.

VLMs are Good Teachers for Video Reasoning via Adaptive Test-Time Optimization Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-07-01T22:26:17.298401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-28T15:26:21.284810Z digest=sha256:4786d68c968196d3f1a1997e8da47bfbe094449d50f09141313a790d35d3b563

Observation 364255a2-df29-48f6-aed3-827cbf2f0eb4 · inbound

VLMs are Good Teachers for Video Reasoning via Adaptive Test-Time Optimization cites this paper.

VLMs are Good Teachers for Video Reasoning via Adaptive Test-Time Optimization Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-06-30T10:44:36.764583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T10:38:22.619277Z digest=sha256:183b3a8f2bef1788a3b549110685558f14d7643d8ee600ed2eb03da84226412b

Observation 79385f51-789f-48aa-97c3-febffed3ce2a · inbound

Follow-Your-Preference++: Rethinking Preference Alignment for Image Inpainting cites this paper.

Follow-Your-Preference++: Rethinking Preference Alignment for Image Inpainting Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-07-02T02:36:26.434409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-28T10:51:40.605583Z digest=sha256:62e4f15952a6af952d58197697670569a8b89c7a031b5678f32a6d1e476c11ef

Observation 51dddd86-5d8a-45e7-896b-753e0b9ba119 · inbound

GeoVolDiff: Taming 3D Geological Volumes with Latent Diffusion cites this paper.

GeoVolDiff: Taming 3D Geological Volumes with Latent Diffusion Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-07-02T06:16:43.677804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-28T07:28:26.968075Z digest=sha256:b9f5fde3373b95e728aab0be15b839a4e1bca988c174762d96bb9236cf84fbd2

Observation dc096517-9b95-4e9c-bbfd-06650ac569d3 · inbound

Ultra Flash: Scaling Real-Time Streaming Video Generation to High Resolutions cites this paper.

Ultra Flash: Scaling Real-Time Streaming Video Generation to High Resolutions Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 43

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T00:37:29.768967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-27T17:07:57.743780Z digest=sha256:7626cb3484c6ce1488a616c2ff63de6d83aca31e9d4d85268d8bad3b44a75597

Observation 2b360bfd-7174-440c-ae5b-6caf68665367 · inbound

Echo-Memory: A Controlled Study of Memory in Action World Models cites this paper.

Echo-Memory: A Controlled Study of Memory in Action World Models Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-07-03T00:57:29.746650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-27T16:58:37.552036Z digest=sha256:00bb379a49d07bea7024e3c901707f4d5c96305204964d2d870e02c0555dd649

Observation ddb3b5d2-d00e-4e07-9411-6d475235125b · inbound

SpecLoR: Spectral Lookahead Rectification for Motion-Coherent Text-to-Video Generation cites this paper.

SpecLoR: Spectral Lookahead Rectification for Motion-Coherent Text-to-Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-07-03T10:27:56.783988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-27T10:00:35.608696Z digest=sha256:11f9ae8d9b9a155637f6d8ee22869f020fc8e9dfe7ea9b7c0826994cbf329e5b

Observation 5d687878-7b42-4294-922e-76610029f618 · inbound

GF-DiT: Scheduling Parallelism for Diffusion Transformer Serving cites this paper.

GF-DiT: Scheduling Parallelism for Diffusion Transformer Serving Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 12

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T16:28:39.311455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-27T05:35:01.339479Z digest=sha256:df25435be645ada8582249db823b4907a423947bbb6038a03fb129c1c071c1c6

Observation 90e1add3-e247-4a5d-b821-bffbcc6a0f21 · inbound

GF-DiT: Scheduling Parallelism for Diffusion Transformer Serving cites this paper.

GF-DiT: Scheduling Parallelism for Diffusion Transformer Serving Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 12

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T23:59:06.289888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-03T23:50:39.241880Z digest=sha256:94ba50405f6684fe238a8bad08437d2b69ebfc0706f82071616717bad665615e

Observation 6eaf742d-e0af-431a-ba9b-0a28c7af7488 · inbound

Through the PRISM: Preference Representation in Intermediate States of Video Diffusion Models cites this paper.

Through the PRISM: Preference Representation in Intermediate States of Video Diffusion Models Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 27

Resolution
metadata mismatch
local_arxiv, observed 2026-07-04T03:09:29.394263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-26T18:25:49.041639Z digest=sha256:7f2f99d70e63af4593344dce6d6e60771600ffe31bc58209fd68c173715118d9

Observation 178efe36-0829-4425-909b-189062701521 · inbound

GroundShot: Visually Consistent Multi-Shot Long Video Generation via Entity-Grounded Shot Scheduling cites this paper.

GroundShot: Visually Consistent Multi-Shot Long Video Generation via Entity-Grounded Shot Scheduling Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-07-04T03:19:30.339038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-26T18:15:51.862192Z digest=sha256:538067685a3bff5c0955d8355723eb69a8a108fddc08667d4994b659a8ca6e87

Observation d97e0e6e-e598-4acc-9984-219615aa9a19 · inbound

GroundShot: Visually Consistent Multi-Shot Long Video Generation via Entity-Grounded Shot Scheduling cites this paper.

GroundShot: Visually Consistent Multi-Shot Long Video Generation via Entity-Grounded Shot Scheduling Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-02T10:48:04.448638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T10:48:04.448638Z digest=sha256:a7e19bfaf0e7d41932b5293e382a31ccd0d268e44f3a728db400fb5fbe657eff

Observation 60f7a849-c5a4-4de3-8b94-a582ca169de5 · inbound

FLUX3D: High-Fidelity 3D Gaussian Generation with Diffusion-Aligned Sparse Representation cites this paper.

FLUX3D: High-Fidelity 3D Gaussian Generation with Diffusion-Aligned Sparse Representation Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 11

Resolution
metadata mismatch
local_arxiv, observed 2026-07-04T16:49:57.565204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-26T00:13:52.289469Z digest=sha256:88214f9af9331df71acf8bfb3ac76aa29961ad7fbb3eed9676c126f9bc128089

Observation 6f98ea1e-cc59-4d60-9ea9-d86f8142eb86 · inbound

EchoStyle: Unlocking High-Fidelity Video Stylization with Reverse Data Synthesis cites this paper.

EchoStyle: Unlocking High-Fidelity Video Stylization with Reverse Data Synthesis Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 8

Resolution
metadata mismatch
local_arxiv, observed 2026-06-25T21:08:21.647894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-25T21:00:00.682243Z digest=sha256:ad036e29049f2a8690888108b8b884e5fd21cdf1d6aaae3139c58f348fcaf6d2

Observation cbd91e17-d882-4bd6-902a-c889fdb51a1c · inbound

Causal-rCM: A Unified Teacher-Forcing and Self-Forcing Open Recipe for Autoregressive Diffusion Distillation in Streaming Video Generation and Interactive World Models cites this paper.

Causal-rCM: A Unified Teacher-Forcing and Self-Forcing Open Recipe for Autoregressive Diffusion Distillation in Streaming Video Generation and Interactive World Models Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-07-04T19:50:11.377892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-25T20:57:30.765802Z digest=sha256:e63d33a8a3354efe6ba301048b3a0f7c65c62efd0de806ec769a68c33c233675

Observation 9adafd8a-9c06-4f66-ba66-f8e8497f1553 · inbound

Disco-LoRA: Disentangled Composition of Content, Style, and Motion for Multi-concept Video Customization cites this paper.

Disco-LoRA: Disentangled Composition of Content, Style, and Motion for Multi-concept Video Customization Seedance 1.0: Exploring the Boundaries of Video Generation Models

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-07-04T12:49:52.826252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-26T05:51:29.839498Z digest=sha256:72f95cb1e45a4a6c2bc30a68c5043067948a31e59bdf1eaf45bb3bc45e47524c