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Paper Citation Record · LEDGER

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

As of 11 August 2026, this Paper Citation Record lists 100 of 113 outbound references and 100 inbound Pith citation observations for arXiv:2506.08009.

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

pith.paper-citation-record.v1
2506.08009 v2

Coverage vector

measured 100 of 113 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-11T01:36:53.029590Z

measured 200 of 200 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 100 of 230 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:09:13.645793Z

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

100 of 113 outbound references displayed

  • verified exact28
  • verified fuzzy70
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

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

Outbound references

Observation 578b8bc9-ef05-49f9-8417-281d709bf81a · outbound

This paper cites Block diffusion: Interpolating between autoregressive and diffusion language models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Block diffusion: Interpolating between autoregressive and diffusion language models

Reference 1

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verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.595536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:7c4a13d9d1f47a08ea305ab2b5fb7cefd718d7d86dc65378edf9a7280d1f2199

Observation d67d6f53-56bb-49a2-be07-1f0cf8980fd4 · outbound

This paper cites Toward one-second latency: Evolution of live media streaming.IEEE Communications Surveys & Tutorials.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Toward one-second latency: Evolution of live media streaming.IEEE Communications Surveys & Tutorials

Reference 2

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raw_fallback, observed 2026-05-11T01:36:53.607067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:c80ad9a066e48e915283a94b66ec26c4e5ae7e04db9f46445b0eda37d16cc887

Observation 102ac161-4c01-4a19-b371-84f71d9a07ab · outbound

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

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 3

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verified exact
local_arxiv, observed 2026-05-11T01:36:53.213466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:ae48afdfb6853a78097b9126957f2e6010a645058e41cf220d2e09c149aa9a0d

Observation 33262d86-3ebf-4b6c-8c2e-b56daa495fc6 · outbound

This paper cites Align your latents: High-resolution video synthesis with latent diffusion models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Align your latents: High-resolution video synthesis with latent diffusion models

Reference 4

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verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.611039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:130dd2cb59a86fcca01dae95e535888cd6eb50172404aa254c899ad1a4528dc3

Observation 491d179a-3a5a-49b2-b4be-9832679a8a96 · outbound

This paper cites Generating long videos of dynamic scenes.NeurIPS.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Generating long videos of dynamic scenes.NeurIPS

Reference 5

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raw_fallback, observed 2026-05-11T01:36:53.614251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:1ed8766d7b564dbfade38cb07ef67f52bf36787a67956538e3b4ae82eb0a4724

Observation bd363c4c-597b-4d07-ae40-f73b2c87bfe6 · outbound

This paper cites Video generation models as world simulators.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Video generation models as world simulators

Reference 6

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raw_fallback, observed 2026-05-11T01:36:53.618573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:ecb6bab9759f75a9f2a62be4545289dd4acd7fcf478a23bacf55455a87a5093b

Observation d2172c7a-f27f-4cb6-a377-05b46fa04bb9 · outbound

This paper cites Genie: Generative interactive environments.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Genie: Generative interactive environments

Reference 7

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raw_fallback, observed 2026-05-11T01:36:53.637270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:41711049cb45cd8e2a1b2efbf09be5cc41c38e865626fd7624c1db0d30988193

Observation 8127958a-1ad4-43a4-908b-739237f5c14b · outbound

This paper cites Diffusion forcing: Next-token prediction meets full-sequence diffusion.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Diffusion forcing: Next-token prediction meets full-sequence diffusion

Reference 8

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verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.649466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:0229037f00a63c5e25afbdd31ed35e6ede1ceaa157d33e7c449408ea6174c326

Observation 00682b39-ba19-4527-9dd0-83f065d3b68c · outbound

This paper cites Streaming Video Diffusion: Online Video Editing with Diffusion Models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Streaming Video Diffusion: Online Video Editing with Diffusion Models

Reference 9

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verified exact
arxiv_id, observed 2026-05-11T01:36:53.249961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:d0d3052bd6ffbfc2e509aff156e7e7aeb19cd17e5f6cf648acd0520709a4ef1d

Observation 47be411e-0349-4f65-be91-78a19ca8cf22 · outbound

This paper cites SkyReels-V2: Infinite-length Film Generative Model.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion SkyReels-V2: Infinite-length Film Generative Model

Reference 10

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verified exact
arxiv_id, observed 2026-05-14T20:23:04.486750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:45149c7e2a952098310de3cc8ff53937ea886d8da4d1ee304138e6e2192aeb64

Observation ae2faadb-a07d-4eb5-b841-8af11526dbd8 · outbound

This paper cites Oasis: A universe in a transformer.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Oasis: A universe in a transformer

Reference 11

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raw_fallback, observed 2026-05-11T01:36:53.653927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:642f592cb031324dc84a50d0f3a55d383c8db12774ad630826f4805f90d7d86f

Observation 7d5a059e-c83d-4dba-ad0f-16bf25ad7f50 · outbound

This paper cites Causal Diffusion Transformers for Generative Modeling.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Causal Diffusion Transformers for Generative Modeling

Reference 12

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verified exact
arxiv_id, observed 2026-05-11T01:36:53.235817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:5ef96b68c7e95fcd375ee31b8ae93db539fdd0db7f0977fdf50c691007a67039

Observation ef4e11c2-1293-49a2-9334-790d60d59692 · outbound

This paper cites Autoregressive video generation without vector quantization.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Autoregressive video generation without vector quantization

Reference 13

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raw_fallback, observed 2026-05-11T01:36:53.661637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:84c8f844814f82c33c4367c4a7e62981c55ea6e845462256105487014a123a7d

Observation e34f0958-36bd-4bb3-864c-96f0dd9d7b08 · outbound

This paper cites Unsupervised learning of disentangled representations from video.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Unsupervised learning of disentangled representations from video

Reference 14

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raw_fallback, observed 2026-05-11T01:36:53.668271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:935667d0dcdb5cd111171e406efe41eb57c745968d5542009a63dffc7ec0c71b

Observation 91cbba34-4b26-4742-8e3f-2747bd661701 · outbound

This paper cites Flex Attention: A Programming Model for Generating Optimized Attention Kernels.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Flex Attention: A Programming Model for Generating Optimized Attention Kernels

Reference 15

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arxiv_id, observed 2026-05-17T21:27:16.810492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:71c957f5487f09638d089f54915e71ba66985d8291aeaaa71727ddefb6715d33

Observation 4f9735f1-ae02-45dc-8a3d-0ad4c05d0e04 · outbound

This paper cites Ca2-VDM: Efficient Autoregressive Video Diffusion Model with Causal Generation and Cache Sharing.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Ca2-VDM: Efficient Autoregressive Video Diffusion Model with Causal Generation and Cache Sharing

Reference 16

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arxiv_id, observed 2026-05-11T01:36:53.142419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:3b5f2eb3ddae078a32477374ce9ecf1c124570c55128b0110014282ef08fa34b

Observation eb7c4b6d-9853-48e9-91cd-56a65320ca51 · outbound

This paper cites Long video generation with time-agnostic vqgan and time-sensitive transformer.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Long video generation with time-agnostic vqgan and time-sensitive transformer

Reference 17

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raw_fallback, observed 2026-05-11T01:36:53.680351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:eb01c66741e92dfdbc54d53dd47b17d770369498e47c55006ddf3587d7c15fac

Observation 343d5a26-4911-470d-a41c-67b0d3961726 · outbound

This paper cites Generative adversarial nets.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Generative adversarial nets

Reference 18

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raw_fallback, observed 2026-05-11T01:36:53.683460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:d387293c5cb08e77988d580af4edce90e39c25e0b4a60dd79a06ef464ca277f6

Observation b9f91b42-9989-4c9f-8058-21cf8735e15f · outbound

This paper cites Mamba: Linear-time sequence modeling with selective state spaces.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Mamba: Linear-time sequence modeling with selective state spaces

Reference 19

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verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.689105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:36dbee8dd3f5d53757aa48709f08f194e4c37381419209b138c38c73c612f3f5

Observation 8b32dd3e-5116-4066-aa54-064ff8ce043c · outbound

This paper cites Long-Context Autoregressive Video Modeling with Next-Frame Prediction.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Long-Context Autoregressive Video Modeling with Next-Frame Prediction

Reference 20

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verified exact
arxiv_id, observed 2026-05-16T23:05:17.562899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:28479bf74396d59aa4beacc984a34dc80cef3691ed7d682fd4e4ed71ff08e683

Observation a1b3dfd5-29ca-42fd-a9ab-c236b201591a · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 21

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local_arxiv, observed 2026-05-11T01:36:53.314593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:7019f9cb6fef8c7883c09d439de4a4c746b1fb9bc95421c5036aba85e7db4cf4

Observation 6c0d6521-52c3-41c3-ad36-e9ab732fda96 · outbound

This paper cites Long Context Tuning for Video Generation.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Long Context Tuning for Video Generation

Reference 22

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arxiv_id, observed 2026-05-11T01:36:53.332342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:39dfd142a30ee69bad4a33c2e92626fac2f528320e9fe0d669d09ba13038447b

Observation fc71d48b-529b-4e83-9108-e61b9287e9e6 · outbound

This paper cites Photorealistic video generation with diffusion models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Photorealistic video generation with diffusion models

Reference 23

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raw_fallback, observed 2026-05-11T01:36:53.692750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:8b60c3c7d72536d29ae65a9877b2eedac19fa033c648e6da72952812eecde45c

Observation b8bff021-56ef-4dd3-b0e8-76c5d9f66940 · outbound

This paper cites LTX-Video: Realtime Video Latent Diffusion.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion LTX-Video: Realtime Video Latent Diffusion

Reference 24

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verified exact
arxiv_id, observed 2026-05-11T10:36:12.849504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:510c66d2f75b68e8b15cfbb6c141346a9254d9318644bf219c949c3c960f26f3

Observation 9d2c2196-c7dd-43dd-bfa6-2c64d12c5592 · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Imagen Video: High Definition Video Generation with Diffusion Models

Reference 25

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arxiv_id, observed 2026-05-11T03:31:08.340948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:75dfd752886893db8cf5ab7c8744eff7622444db3c59f6bc3c4adfd4fd7cdfa7

Observation 1e071fa1-718f-4ae8-87de-ecb8e19fba9c · outbound

This paper cites Video diffusion models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Video diffusion models

Reference 26

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verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.695525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:8627870a18cb5d0b633eb0b62af2974f2204047da8400f420c8f6ff56298695a

Observation 399a6983-41fe-4dc7-8b94-b4972a0c692a · outbound

This paper cites Cogvideo: Large-scale pretraining for text-to-video generation via transformers.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Cogvideo: Large-scale pretraining for text-to-video generation via transformers

Reference 27

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verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.698270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:ae1f0b905564a8b679dc048dfdde6db5edf9d86d0f5246131a68811c728acfab

Observation 101f224b-4c8b-4309-9077-2086249465a7 · outbound

This paper cites Acdit: Interpolating autoregressive conditional modeling and diffusion transformer.arXiv preprint arXiv:2412.07720.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Acdit: Interpolating autoregressive conditional modeling and diffusion transformer.arXiv preprint arXiv:2412.07720

Reference 28

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arxiv_id, observed 2026-05-11T01:36:53.163071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:0609d8839584764d33238d83d17163e3423508576b7d8a2914120fb37875a941

Observation 38929b41-e337-4160-b77a-e0cf3fea77c6 · outbound

This paper cites The gan is dead; long live the gan! a modern gan baseline.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion The gan is dead; long live the gan! a modern gan baseline

Reference 29

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raw_fallback, observed 2026-05-11T01:36:53.704912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:76ec1922996535b49e5c7c6344c14e4ab7ed576a1f17ec2982661ca0b4cb669b

Observation d642d901-edfb-4a69-a41a-431413feaaba · outbound

This paper cites Flow Generator Matching.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Flow Generator Matching

Reference 30

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verified exact
arxiv_id, observed 2026-05-11T01:36:53.229361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:2e158f3193753de89d301667ab8a2f76c0a7b12f8d4de433d3337ca5f466b63e

Observation a8fb6ddb-650c-4056-8a61-6eed348891db · outbound

This paper cites VBench: Comprehensive benchmark suite for video generative models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion VBench: Comprehensive benchmark suite for video generative models

Reference 31

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verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.710816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:119e41f5770320df6bbeee51c17e937c28205cc35b291fc1a9c9e5dcd7fdb9e3

Observation 7a79aa20-bc9e-42da-bb74-fec635a824c5 · outbound

This paper cites On stabilizing generative adversarial training with noise.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion On stabilizing generative adversarial training with noise

Reference 32

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raw_fallback, observed 2026-05-11T01:36:53.713738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:ff0d37445dc2e6a6c79a47d7978a77a6742a4110b780eaeaa1b1285ac426567c

Observation 8172f34b-87f5-4ef5-a3b3-1ac7f0c75876 · outbound

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

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Pyramidal flow matching for efficient video generative modeling

Reference 33

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verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.720216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:0a2166ca70d9f8f7396fc8c7ec2f74c3aac6c2a189736f0d8c973be10763941e

Observation b21af946-7b2f-479d-9ed1-e7f30fb733fc · outbound

This paper cites The relativistic discriminator: a key element missing from standard gan.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion The relativistic discriminator: a key element missing from standard gan

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.727807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:b435c78cbb8a3c32a1f2b3220317184bae202d4f1609f2a8935472dc49e7d7f0

Observation 2e23d623-1742-462e-b251-c5a4cc82fcd0 · outbound

This paper cites Fifo-diffusion: Generating infinite videos from text without training.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Fifo-diffusion: Generating infinite videos from text without training

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.731088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:31d1fc0b6f2ab4f4ab81bdbd046bdd4be27105ebab871b1c8ead084d9ebd6b8b

Observation 554f1112-236e-474d-a27b-6b1bdce732cd · outbound

This paper cites Variational diffusion models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Variational diffusion models

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.734189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:d8d1c420f85a3d12478615e586b17f90d7c786ca4230bb3e3d29781cee2951c7

Observation 5cf920f1-7420-40fc-a61c-805c3bbe564c · outbound

This paper cites Auto-encoding variational bayes.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Auto-encoding variational bayes

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.742529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:94772293ccfbc26b65a5e96cb3cd0f29777e7719567dbfd66d87f3e91f378775

Observation b12621ff-9b6e-4066-ab1d-45a2831bb9f5 · outbound

This paper cites Videopoet: A large language model for zero-shot video generation.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Videopoet: A large language model for zero-shot video generation

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.751295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:c1875ae3e2f23b169638c2fdf8a054abaf6d2af2847cc270b6e0600348de6c07

Observation 611dfa89-06ed-4ec1-ab3c-c1103e286331 · outbound

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

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-05-11T01:36:53.103420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:1885171fa086056098e9a04f653c1ba480c2d5bf72a4c75b876e8030ffc29fdd

Observation c9dee08a-e030-46d0-a0aa-8421be56bfcc · outbound

This paper cites Professor forcing: A new algorithm for training recurrent networks.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Professor forcing: A new algorithm for training recurrent networks

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.758248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:07638696069721a278054b5d6783a7131c9a7ff6f58d81495bff8c0e34993da9

Observation dadca4ad-3945-49c3-a53b-abc40088c4e0 · outbound

This paper cites Latency reducing in real-time internet video transport: A survey.SSRN 4654242.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Latency reducing in real-time internet video transport: A survey.SSRN 4654242

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.761842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:a6600b0674cf73f63803a5e839521f9bf9025d6c9f033b65427fe23b140d69a2

Observation 8659c518-883f-4b35-b9e0-95f9366fb765 · outbound

This paper cites Unified Video Action Model.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Unified Video Action Model

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:50:29.857677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:942cc54fbb30fec660c669254e0418f6be6b409402043619c9a9eb4955e9ce12

Observation ce8d7df8-0424-4072-a141-ba903e5fbc4c · outbound

This paper cites Autoregressive image generation without vector quantization.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Autoregressive image generation without vector quantization

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.767027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:c508369b69399697d9b998fed585a4053eb5382045f92c58744368cccb719de0

Observation 33810364-874c-4383-9762-f9f767abcb9d · outbound

This paper cites Infinitenature-zero: Learning perpetual view generation of natural scenes from single images.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Infinitenature-zero: Learning perpetual view generation of natural scenes from single images

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.773986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:d7264d944bc4f94280658aa31594262bbd7076c9d413f5d0262df39356f9e326

Observation 37a04a05-ab1a-47d3-bbe3-ccc29c05950a · outbound

This paper cites Arlon: Boosting diffusion transformers with autoregressive models for long video generation.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Arlon: Boosting diffusion transformers with autoregressive models for long video generation

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.778153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:604fe3f4c98d4fcc715ca05730bfde3aefc5ec98e1de0ee8c0eccf896d4918ba

Observation b2c22b4f-9df7-4a7d-83ba-66674e8f3bc7 · outbound

This paper cites Looking backward: Streaming video-to-video translation with feature banks.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Looking backward: Streaming video-to-video translation with feature banks

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.782926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:e2144260619cf2e994e9a3a9cbb04425dad1189e4b2ecdcdd99e9174a87f3dce

Observation abc0b03f-aaba-4b43-98d5-5c975cdfacd3 · outbound

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

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Diffusion adversarial post-training for one-step video generation

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.244388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:d447dc2ea4ae70fbf30fac981b37dab701318302fca979b85d1c4b7d25726329

Observation 117e8110-0349-427e-9dd7-8484d5aaa26f · outbound

This paper cites Flow matching for generative modeling.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Flow matching for generative modeling

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.789043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:423f42c4a9e735289451cc1f1b8683750ac328a46acaef57c22a5e0c052ca85c

Observation b218aaf5-5fde-473e-bd0e-fbf63e0b5bd0 · outbound

This paper cites Infinite nature: Perpetual view generation of natural scenes from a single image.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Infinite nature: Perpetual view generation of natural scenes from a single image

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.798208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:b3780c9f3ff1c13b9263ea84d3233e8928a4488c8f0ae2fb2ff7b765d5195e4d

Observation 2338f9ea-a91d-416f-9df8-7d2b94a55ea3 · outbound

This paper cites MarDini: Masked Autoregressive Diffusion for Video Generation at Scale.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion MarDini: Masked Autoregressive Diffusion for Video Generation at Scale

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.310698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:21db4bcc78cca5ed1f187611721a923244b824e54c2c17e283e4584a0e8d7d20

Observation a3ae60f9-d43b-4366-9343-ca4f327a1397 · outbound

This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Flow straight and fast: Learning to generate and transfer data with rectified flow

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.808377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:6aff72ceda17e66fe5e33a49fc172f7a0e6823c89025e16a916810f5b57334d6

Observation 292f8333-52fc-4a42-b2fb-25b1522f83a3 · outbound

This paper cites Redefining Temporal Modeling in Video Diffusion: The Vectorized Timestep Approach.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Redefining Temporal Modeling in Video Diffusion: The Vectorized Timestep Approach

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.322526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:359157c94fbcf3ddf398d7c5186426ba8444f7bae9c87f0ff253685d98003727

Observation cda5b317-bf10-4a5b-9491-bd3be58499d9 · outbound

This paper cites Autoregressive Diffusion Transformer for Text-to-Speech Synthesis.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Autoregressive Diffusion Transformer for Text-to-Speech Synthesis

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.326258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:7464f6ff7fa65249dd72be9e469d950b494f98efe6e0e8a3ebf3eb6e0634427c

Observation b7037612-5123-46bb-a9fb-9c4cf779d2ec · outbound

This paper cites Diff-instruct: A universal approach for transferring knowledge from pre-trained diffusion models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Diff-instruct: A universal approach for transferring knowledge from pre-trained diffusion models

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.349945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:aaf8bce59587aa5b83f2cacf8c0d4ed1b121c54ac9b5e27207c27a45dd95e645

Observation 983eb2a2-275c-4d1e-ab60-57ab3f01dfa6 · outbound

This paper cites One-step diffusion distillation through score implicit matching.NeurIPS.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion One-step diffusion distillation through score implicit matching.NeurIPS

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.359229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:9aa841e7ac7c243bce89020e35c6b6c1735266e9721bd02e2986631b8954766b

Observation 3f7af2ee-2f59-4648-b7ed-d2dcae36eb1b · outbound

This paper cites Osv: One step is enough for high-quality image to video generation.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Osv: One step is enough for high-quality image to video generation

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.363130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:b0b8297b0a8c623de85acd988ebb5ead3f4ae70ba18237467d34e1b57c65ca9b

Observation d8465a89-4596-4f38-a887-e8364e504d10 · outbound

This paper cites The parallelism tradeoff: Limitations of log-precision transformers.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion The parallelism tradeoff: Limitations of log-precision transformers

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.368181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:f494f72f3c1c4935392f5efe01fbc030f3d591efe5ddd5d8587d42c9d993fa4f

Observation 83bcb66f-9bcb-40fa-9157-d651503fca81 · outbound

This paper cites Which training methods for gans do actually converge? InICML.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Which training methods for gans do actually converge? InICML

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.379636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:d53bfeb4727d360dbeab4aeb8db6c335d32fef77e1f82ccd8fb878fbc7917d55

Observation 03b976e2-9cc8-4901-bbb0-4a0dfa934104 · outbound

This paper cites X-Fusion: Introducing New Modality to Frozen Large Language Models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion X-Fusion: Introducing New Modality to Frozen Large Language Models

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.126525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:bee2a88e8628b44f0a6b712d7bd6937982806805c74c421cce8fc42669eec90a

Observation 220e4f4e-c64e-415d-b524-c4d9be409050 · outbound

This paper cites Elucidating the exposure bias in diffusion models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Elucidating the exposure bias in diffusion models

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.383705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:e64b9e42bc4b7a3b640fb657ab2b5017babea5cca0840ca09f36ac794db8edfe

Observation 2d5885e6-95a0-44e4-a7b4-dd2b6534ac10 · outbound

This paper cites Genie 2: A large-scale foundation world model.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Genie 2: A large-scale foundation world model

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.391660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:9c7d970e90d019f735d94fce58e7e8e490a1ab62be3e69c61158cdeaee731e28

Observation 651630fb-a745-42f4-a81e-da46e64fd150 · outbound

This paper cites Scalable diffusion models with transformers.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Scalable diffusion models with transformers

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.395586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:1dfe8cda65deb16a729eb806b9946d3ce129cc18c15db5626be9a9e3f4745a4e

Observation 1773a11a-af1e-4a1a-bcd0-d78ee8101786 · outbound

This paper cites Long-Context State-Space Video World Models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Long-Context State-Space Video World Models

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.152030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:d1bb03d144afda38ccfb8273ed1900324548c65edc8e6f3ebdcfcd641c7e3fa6

Observation 9ef452e8-00bb-4656-8cfa-3fb41a957153 · outbound

This paper cites Movie Gen: A Cast of Media Foundation Models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Movie Gen: A Cast of Media Foundation Models

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:16:26.778393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:71101f2a32869e927fef2d32fa03c2178ee8c1e66613d48878eff3a7e103c4aa

Observation 916f331a-be55-4cc5-819c-3341c42ac6a2 · outbound

This paper cites Sequence level training with recurrent neural networks.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Sequence level training with recurrent neural networks

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.399414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:edd1f5c4eeed35385f08ed934de39bacb3e0242244b68ea33ba5018064b13a0a

Observation 299005e7-5dae-43e3-a942-e23d7afb4a41 · outbound

This paper cites Next Block Prediction: Video Generation via Semi-Autoregressive Modeling.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Next Block Prediction: Video Generation via Semi-Autoregressive Modeling

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.205091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:64b22f142f0ba0564561dd5975eb2c3cbfa64831bbacfa879fa7ba6563b4a3ca

Observation 98cd7701-8b35-48a6-9df4-a52742177621 · outbound

This paper cites Rolling diffusion models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Rolling diffusion models

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.404530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:2cbd85823149083da3ab8cd1e3b2c8d03592a3c6c216c7cd79bbfc03220e74bf

Observation 5b63dcc8-4c1e-4621-8adc-2bde9313c94a · outbound

This paper cites Temporal generative adversarial nets with singular value clipping.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Temporal generative adversarial nets with singular value clipping

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.413171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:8e34e7e233805c18b837951394a2cc4c0903e8defac3767bc3ce86e53167e809

Observation 1947f5b0-f4f9-45ea-a750-4f59853e09a4 · outbound

This paper cites Magi-1: Autoregressive video generation at scale.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Magi-1: Autoregressive video generation at scale

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.417632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:40afe2fbc62d3d48d51cb8fe0ccf8dbea57e9a20376500fe379cdfbb71cd7a2d

Observation 68d7fe07-af11-469b-ab76-228fe8095649 · outbound

This paper cites Fast high-resolution image synthesis with latent adversarial diffusion distillation.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Fast high-resolution image synthesis with latent adversarial diffusion distillation

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.422328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:4b720c4d5eb9e30afc7a7386ec2df83a7c20f988666d4ee657ec4ca1d4f6fd62

Observation 1d02ec0b-3299-48dd-ab03-8fc7d3e483ac · outbound

This paper cites Generalization in generation: A closer look at exposure bias.EMNLP-IJCNLP 2019, page 157.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Generalization in generation: A closer look at exposure bias.EMNLP-IJCNLP 2019, page 157

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.445009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:870fda70ea008c85e4dc1e709d99eaf7d8ca2e42b636b0bd91019770155ea559

Observation f3c4ddbf-60ee-4b7e-8bca-fe0a1dade102 · outbound

This paper cites Flashattention-3: Fast and accurate attention with asynchrony and low-precision.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Flashattention-3: Fast and accurate attention with asynchrony and low-precision

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.449731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:bc8b88351ca3159166ec1065096d431b9e5db8e044837e8f74a01d8b740b8150

Observation 1777d8df-4bcd-49fc-a8af-bb5eacbbf7a3 · outbound

This paper cites History-Guided Video Diffusion.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion History-Guided Video Diffusion

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-05-16T12:00:14.880011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:1947b637311e6267eb065bbd5a6e1b59d6187dd67f123d41a12e06a0f961c1f0

Observation 3e98f328-1a98-4216-b28a-6815cceb434c · outbound

This paper cites Consistency models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Consistency models

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.457805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:d797a3c7b4bdd82eb9f30a03d339417b312d13f89bbfd64ad9853ed0c03bc839

Observation ee582ce0-91b3-46f8-bb0f-c66d3250575e · outbound

This paper cites Maximum likelihood training of score-based diffusion models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Maximum likelihood training of score-based diffusion models

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.461420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:078c6aad04b94b50f0819a3507e2a7941a29733d4fcd4d9d5636ab04d3f38916

Observation ca27b528-d215-4009-80b1-4922d894c60b · outbound

This paper cites Ar-diffusion: Asynchronous video generation with auto-regressive diffusion.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Ar-diffusion: Asynchronous video generation with auto-regressive diffusion

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.468571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:0f72819d1454b827693244bb08bf60aff881f00b0318800709c0c6a9a8355c8a

Observation 0bd09ef1-6f36-417b-884c-0158f601fb02 · outbound

This paper cites Mocogan: Decomposing motion and content for video generation.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Mocogan: Decomposing motion and content for video generation

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.472596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:fc5286cde82eb7baee23b3e246d51ca8111d75bc2a40f542ec7d74bd76ce03fc

Observation 55d1d800-fc8a-4dc1-a84c-7fa6ccaaeb2a · outbound

This paper cites Diffusion models are real-time game engines.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Diffusion models are real-time game engines

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.476168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:5c523a87c3bcea7c32812ea23803fbde3f766321f26e64e94f244ce334dffc90

Observation 56d7bea6-d033-49e2-a94f-98d43347a0d9 · outbound

This paper cites Neural discrete representation learning.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Neural discrete representation learning

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.480270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:0038948e3eda464439c67ed7a525479763a31ad0ed2fdefd479f6c8e2c4e53d4

Observation 4455c6c9-c8c0-43c3-8a74-dd695ee4d22b · outbound

This paper cites Phenaki: Variable length video generation from open domain textual descriptions.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Phenaki: Variable length video generation from open domain textual descriptions

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.484200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:74902b56bf0d1c380efd506e0789f4ede4508b1bd081229c2a0cedb46062ed89

Observation b1e4912e-2f5c-4ee9-bd7d-f14b4d0df936 · outbound

This paper cites Decomposing motion and content for natural video sequence prediction.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Decomposing motion and content for natural video sequence prediction

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.489761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:d68370beea74886dfae309beb87388f3842f9ecf67816c53d3015f42cb77aad5

Observation 685f6623-835b-49fb-a1e5-5b86b80d4eb3 · outbound

This paper cites Generating videos with scene dynamics.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Generating videos with scene dynamics

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.493857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:c2cd359656eef60d1df17601d758a73924f129a63a31c6a4905a8d01035707f9

Observation 4de981b9-8abe-4236-8e5c-d11887423ac7 · outbound

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

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Wan: Open and Advanced Large-Scale Video Generative Models

Reference 83

Resolution
verified exact
local_arxiv, observed 2026-05-11T01:36:53.111849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:9d24ebf7419a33a92e4f997c52afcd5d2c5aacbe568c3df1effad13cd0bdac72

Observation 60d57355-b178-4658-abad-247a631237e4 · outbound

This paper cites Error analyses of auto-regressive video diffusion models: A unified framework.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Error analyses of auto-regressive video diffusion models: A unified framework

Reference 84

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.120113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:1c8d6923a1e6c9b61a31f2c6b77605e1f8cb2babf23c13198f4082ba1ad8bbc5

Observation 7737c95b-35ad-4a98-93be-f369df4416a4 · outbound

This paper cites Vidprom: A million-scale real prompt-gallery dataset for text-to-video diffusion models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Vidprom: A million-scale real prompt-gallery dataset for text-to-video diffusion models

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.497778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:7895afd7ad49800ddc4da0e8913285523ca4e9c71373c70b7f91747d0b9b5313

Observation 4dad1b58-0de1-4a3d-a9d1-2327fcd5b564 · outbound

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

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Loong: Generating Minute-level Long Videos with Autoregressive Language Models

Reference 86

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.131734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:9997f891eb847b3bdedd77f30e812cbe252662dbd57c1c355e21fba51dc89802

Observation ef434170-3596-45f4-8e82-cfa23c33adb9 · outbound

This paper cites Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation.NeurIPS.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation.NeurIPS

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.509725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:e2b85381c35418c95d74bb6988d039dde6d46eba63a80dcbda54e1751b6a1dee

Observation 3248f5ef-1dfa-4a65-9ec5-bafca809dabe · outbound

This paper cites Scaling autoregressive video models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Scaling autoregressive video models

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.513910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:4d2c81713fd6308f749e907b1707233c6527fb55c800f7776c5299768c93d2f8

Observation 69c18a36-2a55-4cd2-9266-4e300e9b039a · outbound

This paper cites Art-v: Auto-regressive text-to-video generation with diffusion models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Art-v: Auto-regressive text-to-video generation with diffusion models

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.517718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:ba6a52da0993a0078099a126663136b639f93d377a0537bbd9a15658a146eb60

Observation 8e4c3dc0-b0b4-49cd-b975-d52a80857da8 · outbound

This paper cites Ar-diffusion: Auto-regressive diffusion model for text generation.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Ar-diffusion: Auto-regressive diffusion model for text generation

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.522615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:c5a269e7ec7db4c73843996b4675019d06f39a7ef2eed57d9d5a7841c91acd53

Observation f786153b-a237-454b-95bf-7deba8ddc8c9 · outbound

This paper cites Snapgen-v: Generating a five-second video within five seconds on a mobile device.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Snapgen-v: Generating a five-second video within five seconds on a mobile device

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.526953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:b539dce03d33c56b3d3ed485936e0208c2eb0cf8c4a1df6771a04c79530a9402

Observation 5420f233-904a-4f68-9178-aa32c62964c2 · outbound

This paper cites Efficient streaming language models with attention sinks.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Efficient streaming language models with attention sinks

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.536419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:beaf1d515b1e98c5119208c826c9f320ed20f2e5893e6b9170f3eb8ee610a6cf

Observation d325a6a4-0c08-4fc1-a512-a76d20bc2f51 · outbound

This paper cites Progressive Autoregressive Video Diffusion Models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Progressive Autoregressive Video Diffusion Models

Reference 93

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.167878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:2934dbb27e4a3c665029d744c83bc93885470dc6a8d56b1fe2bd8d18adf086d6

Observation 299e0be9-4709-4616-915b-6c0875ffcf4d · outbound

This paper cites VideoGPT: Video Generation using VQ-VAE and Transformers.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion VideoGPT: Video Generation using VQ-VAE and Transformers

Reference 94

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:24:33.857072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:5352cf5ad2fcaa68d39b80df80332398b4183f0c0c1078cbff5d5723f646f1fa

Observation c6de5ddb-aaaf-4b27-9d49-93d8baaf8f71 · outbound

This paper cites Qwen2.5 Technical Report.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Qwen2.5 Technical Report

Reference 95

Resolution
verified exact
local_arxiv, observed 2026-05-11T01:36:53.192810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:aa75fda46c56870da31a977b429e2763a12e6d993d30ca6cd2d34879cf6d18bc

Observation 4666ea00-a484-401c-9d8b-f11ee11cff2d · outbound

This paper cites Learning interactive real-world simulators.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Learning interactive real-world simulators

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.539935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:1240021f8324881e53db6e959c2cc61ca5623ff2d2b25eb98900bc72183069d0

Observation 4ec8584c-f7a4-4a12-9425-39dbb2c54a0c · outbound

This paper cites Cogvideox: Text-to-video diffusion models with an expert transformer.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Cogvideox: Text-to-video diffusion models with an expert transformer

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.543112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:b73a8358dead97a81f3931398be2d4c322169e11af7b0c57036e98dee6ac3353

Observation f0a305a6-890c-4c82-84cc-2202cb18daf5 · outbound

This paper cites Improved distribution matching distillation for fast image synthesis.NeurIPS.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion Improved distribution matching distillation for fast image synthesis.NeurIPS

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.546280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:5f04a02079a221f8547c6c804a5c7add681250caf103fae96185d645c23a565e

Observation 463b37c1-a6ae-40c8-9478-409b3bb78dac · outbound

This paper cites One-step diffusion with distribution matching distillation.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion One-step diffusion with distribution matching distillation

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.550824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:c1b2d05d6cc1b5a84b5e1f2d6d3e5898aaa01702b34fd6c47c9dbd28e4a0ab4c

Observation c711562d-03a8-44db-8caa-ead485d0be32 · outbound

This paper cites From slow bidirectional to fast autoregressive video diffusion models.

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion From slow bidirectional to fast autoregressive video diffusion models

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-05-11T01:36:53.553842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:36:53.029590Z digest=sha256:8700c6337df87811f5383cf7d143b6c04582465356dfbad606e67e04a4148ef7

Pith citing papers

Observation 54c4999a-b2e9-4b94-8672-a54342520c57 · inbound

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

Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-05-19T05:17:06.744739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-19T05:13:28.767788Z digest=sha256:9bc4f708831862ded4b025d6557f70d90d1c1117df7612f80fd08e0892a49cce

Observation 0fd06437-33d2-472f-b709-377e3c43767c · inbound

Hybrid Autoregressive-Diffusion Model for Real-Time Sign Language Production cites this paper.

Hybrid Autoregressive-Diffusion Model for Real-Time Sign Language Production Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-06T18:09:13.645793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:09:13.645793Z digest=sha256:0c2d0183430bab7e5d912608115cef1b81c1fc191eabeb6367185ff3e69644fd

Observation 0d9c8bfd-9578-4c35-ad8f-a267699440f4 · inbound

LoViC: Efficient Long Video Generation with Context Compression cites this paper.

LoViC: Efficient Long Video Generation with Context Compression Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T16:39:24.508909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:39:24.508909Z digest=sha256:b8a2e945687778f65330454593d1391254d89a0607412d5d573fd5c06f65201e

Observation 3549a2f9-caa9-48b2-966b-6d7b27cc6f5d · inbound

Pusa V1.0: Unlocking Temporal Control in Pretrained Video Diffusion Models via Vectorized Timestep Adaptation cites this paper.

Pusa V1.0: Unlocking Temporal Control in Pretrained Video Diffusion Models via Vectorized Timestep Adaptation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T15:24:25.841740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:24:25.841740Z digest=sha256:6cf7668061c825da71732d58eed3d75ef6f051ccf98f42658acee9db8c42dd3d

Observation 2b1d41bd-ba2d-4e04-802a-1fcb01ba7dbf · inbound

Matrix-game 2.0: An open-source real-time and streaming interactive world model cites this paper.

Matrix-game 2.0: An open-source real-time and streaming interactive world model Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 18

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verified exact
local_arxiv, observed 2026-05-18T22:36:53.239922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T22:36:31.044743Z digest=sha256:dbda8a6f25333ca736ad22aaac444c68274400ad7950cb0823b7326445a451f6

Observation ba5f92c1-72e2-4b84-bedc-659cd488f886 · inbound

Flow marching for a generative PDE foundation model cites this paper.

Flow marching for a generative PDE foundation model Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 27

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verified exact
local_arxiv, observed 2026-05-18T13:51:25.513569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-18T13:48:14.532529Z digest=sha256:2887b0ad870167311e999ae51f811439272397aa235dcc6d1ce744d01c02f61e

Observation 441c9f73-9846-43bc-9667-77bb96220295 · inbound

LongLive: Real-time Interactive Long Video Generation cites this paper.

LongLive: Real-time Interactive Long Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-05-15T03:52:59.462923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-15T03:52:59.287555Z digest=sha256:9050de461f668a18405cc123bd64271b19ee6396320a2c92e9b8604153418b2f

Observation 1f701f3b-434b-4010-a4c7-c7beb56e0a46 · inbound

Rolling Forcing: Autoregressive Long Video Diffusion in Real Time cites this paper.

Rolling Forcing: Autoregressive Long Video Diffusion in Real Time Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 70

Resolution
verified exact
local_arxiv, observed 2026-05-16T11:15:29.240695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-16T11:15:29.102090Z digest=sha256:5d10cf72128aa380f754d673df1ddcae63cf94c1c32f9caee4f77ebf0b43a9dc

Observation 18c1d836-f672-4126-b9ca-e7cfac754ca5 · inbound

Self-Forcing++: Towards Minute-Scale High-Quality Video Generation cites this paper.

Self-Forcing++: Towards Minute-Scale High-Quality Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-05-15T22:39:54.398645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T22:39:53.995700Z digest=sha256:bfdee84abbd666c16ca594efff74912ab5fdb23eb6cd6126ab74c7f834b87cd4

Observation b3fbeacd-022b-46e7-af9c-7e69dc82dee6 · inbound

Streaming Drag-Oriented Interactive Video Manipulation: Drag Anything, Anytime! cites this paper.

Streaming Drag-Oriented Interactive Video Manipulation: Drag Anything, Anytime! Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-04T11:42:18.300365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:42:18.300365Z digest=sha256:a330da467534f2939f505090e41559a00f6259143958466ad322e8c3b3d72796

Observation 9da87e67-4fcf-494e-96c0-f0f61b6eeb93 · inbound

Control-Augmented Autoregressive Diffusion for Data Assimilation cites this paper.

Control-Augmented Autoregressive Diffusion for Data Assimilation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-05-18T09:06:09.271234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T09:02:38.416697Z digest=sha256:a06749ee4bcf3b03c5a19ddc6e6853ac51687028d2e9f192d9e04c22b8628cd3

Observation 2a330b6f-a18b-4580-adc2-ad69dd53a828 · inbound

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

Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-05-18T08:51:09.198378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T08:46:16.541104Z digest=sha256:29dad2a9364bd4b20d97d945abe7fe0137becd1bd99bc200965aa0230d9efb62

Observation 513b40a9-42de-4561-9786-3ab5d6693b6b · inbound

Cloning Deterministic Worlds: The Critical Role of Latent Geometry in Long-Horizon World Models cites this paper.

Cloning Deterministic Worlds: The Critical Role of Latent Geometry in Long-Horizon World Models Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-05-18T02:50:48.262123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T02:50:32.870296Z digest=sha256:a4eea9aff0734f2606671bf627b2f133e9188b2897f524dcf39d17003a958edf

Observation d9f66215-8139-4c13-9f9d-4de44b3a0649 · inbound

Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation cites this paper.

Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-17T05:19:05.033997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T05:14:36.280155Z digest=sha256:5b2e22a40b8f73862da4413e1947a560945c330347b14413d2857c1385453835

Observation 8b72514e-b85a-4576-a79e-d343757eee97 · inbound

BIFE: Better Interaction, Fewer Errors for Minute-Long Video Generation cites this paper.

BIFE: Better Interaction, Fewer Errors for Minute-Long Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-03T19:41:56.848609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T19:41:56.848609Z digest=sha256:540670e98008687cf798c37366d425b802f1d61bb37d410da1493c8ae8324109

Observation 4bbd5641-707d-4e84-9ae0-8f849cf8d0bb · inbound

Live Avatar: Streaming Real-time Audio-Driven Avatar Generation with Infinite Length cites this paper.

Live Avatar: Streaming Real-time Audio-Driven Avatar Generation with Infinite Length Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-05-17T01:58:51.363780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T01:56:44.123092Z digest=sha256:64d56a3fab83c221120e02440025018a1c410d9cb83591db3dbd5cf541aa0897

Observation cfbac149-1467-4cb7-b140-b48b69acd3e4 · inbound

Live Avatar: Streaming Real-time Audio-Driven Avatar Generation with Infinite Length cites this paper.

Live Avatar: Streaming Real-time Audio-Driven Avatar Generation with Infinite Length Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-03T18:39:41.344768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T18:39:41.344768Z digest=sha256:fc37913b87805089231ab71a4ce22836c75490f64d3cf8a6c7eab69a546ed0a4

Observation 0e4ec63e-f914-4354-80d3-2a61eb037f1f · 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 Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 30

Resolution
verified exact
local_arxiv, observed 2026-05-16T18:17:55.169775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T18:17:54.943863Z digest=sha256:5b2466e5b2013e5e68ed0a56cee7c90c4291c95d2b2d539171c9f3395465b751

Observation 3a6ea606-cd11-4f47-b833-e4eb3313b7c3 · inbound

Distribution Matching Variational AutoEncoder cites this paper.

Distribution Matching Variational AutoEncoder Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 12

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unresolved
no resolver link, observed 2026-08-03T17:55:06.649101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:55:06.649101Z digest=sha256:b300976b6b687213ed26580f78387765c4b6bc81a625a7a00587a595e9643d07

Observation d06dde71-6ff5-44d4-a0cd-c9768ce582bc · inbound

WorldLens: Full-Spectrum Evaluations of Driving World Models in Real World cites this paper.

WorldLens: Full-Spectrum Evaluations of Driving World Models in Real World Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-03T17:02:35.320248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:02:35.320248Z digest=sha256:f92318bfbdc2200fcf01be52910d6452e01a244c6b9671735f99341ab5fca227

Observation 3defc845-6b14-46a8-af97-b4b7b2ac0b2a · inbound

STARCaster: Spatio-Temporal AutoRegressive Video Diffusion for Identity- and View-Aware Talking Portraits cites this paper.

STARCaster: Spatio-Temporal AutoRegressive Video Diffusion for Identity- and View-Aware Talking Portraits Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-03T16:30:34.497342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:30:34.497342Z digest=sha256:ba6857c51228f09112d53ff9a92d0115ceb84d7f3725695ebd136ecd06b5a45c

Observation e0024932-e629-4f7a-8fc3-7123fb162a36 · 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 Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-05-15T14:29:56.455588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T14:29:56.348733Z digest=sha256:47af913d6cae81cf7fc5a074933e12b459769557db4cd630e2ebc4563c13011a

Observation b79fb749-b6f3-4e83-8ba4-393e169ba84c · 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 Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-03T16:11:12.262538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:11:12.262538Z digest=sha256:9543b2c2bbc1f71bc5166a563eff0dc7520583e84074c0f217d6e01ed28e1348

Observation 61111f2f-fc98-4202-8e54-689eeb1f8696 · 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 Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-03T15:46:08.258198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:46:08.258198Z digest=sha256:25986fdfe9c567dfbfdff539fa76a674f90e4a6c754f96e637fd9da26d9a313f

Observation 0b095d61-5880-4d6c-9a71-6f08c31b7a3c · inbound

Large Video Planner Enables Generalizable Robot Control cites this paper.

Large Video Planner Enables Generalizable Robot Control Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-05-16T21:28:33.888020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T21:26:32.048309Z digest=sha256:f86365ebf653508e50914e5da0261304735fa73fd1e4c623ab8f010a3c8ce8fd

Observation 930e776f-fb83-4eca-88aa-fb1a9ed46c67 · inbound

Flow Equivariant World Models: Memory for Partially Observed Dynamic Environments cites this paper.

Flow Equivariant World Models: Memory for Partially Observed Dynamic Environments Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-03T13:00:54.589266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T13:00:54.589266Z digest=sha256:0ba3607d3a87b6881a67b7797f876b8ff1f4a1e37f67343de46ef0a3fcef4147

Observation 8bf95d7f-8626-4faf-9050-0149749af736 · inbound

SnapGen++: Unleashing Diffusion Transformers for Efficient High-Fidelity Image Generation on Edge Devices cites this paper.

SnapGen++: Unleashing Diffusion Transformers for Efficient High-Fidelity Image Generation on Edge Devices Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-03T10:56:12.818493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:56:12.818493Z digest=sha256:0a4760ed936cf9b7839ea95080a2ef1fd45da409cb29c4140207db83c878ade6

Observation f8da3fbd-8283-4042-895a-d9c6577377e3 · inbound

Transition Matching Distillation for Fast Video Generation cites this paper.

Transition Matching Distillation for Fast Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-03T10:35:06.513455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:35:06.513455Z digest=sha256:39aad16702a77f9aaa0df9921094915678d4c8346ac8ca83a86d2a835090bd16

Observation cfb10b01-e54a-432c-93df-13319eb5ab9f · inbound

Advancing Open-source World Models cites this paper.

Advancing Open-source World Models Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 30

Resolution
verified exact
local_arxiv, observed 2026-05-16T09:07:00.976125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T09:07:00.904794Z digest=sha256:fd031e4b0d120c1ff54a9fef90faffcb1d5add8c5d83ca87e5124881a773c2cc

Observation 3b606d9d-06d7-43d0-8c47-f44da136f992 · inbound

Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation cites this paper.

Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-05-21T17:32:01.742199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T17:32:01.642256Z digest=sha256:97902c38434b4269a246ebcc500cc9bfdcba3c9637bbdca0b53f217b88ba0060

Observation c9da6182-d1dd-44c2-b84e-c6c1e16e5992 · inbound

Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation cites this paper.

Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-05-22T11:51:29.796382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-22T11:48:00.633421Z digest=sha256:496361a36ff7cf95b35a3c9dde80238e1c1014f6f94eef1e26e70b71752e9ed6

Observation 28dd4b54-ef7d-4bad-9e1a-941f5f5ac44a · inbound

Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation cites this paper.

Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-03T05:30:25.808940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:30:25.808940Z digest=sha256:2a42899b8e366ed0e52c38ec976ddc08373d29961ff4134b823557003ff57534

Observation 344d57a0-3b84-445f-b9f4-d73cb2e147a9 · inbound

Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization cites this paper.

Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-05-16T08:00:44.680734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T07:58:24.456859Z digest=sha256:332d3ce8d2da3270ffc77beee22f83bd5197f8fa6777eb098a0d38f2c7bc8a11

Observation 00870348-5122-4d80-9a2b-13afb686843c · inbound

Light Forcing: Accelerating Autoregressive Video Diffusion via Sparse Attention cites this paper.

Light Forcing: Accelerating Autoregressive Video Diffusion via Sparse Attention Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-03T04:33:10.902627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T04:33:10.902627Z digest=sha256:5365a3d63d4b3e86c0bd4be963c31fdfcde040e4464bbb4697a6cab7a2e4d63a

Observation 2126c9aa-8825-4e67-91a7-ad84018ea083 · inbound

Light Forcing: Accelerating Autoregressive Video Diffusion via Sparse Attention cites this paper.

Light Forcing: Accelerating Autoregressive Video Diffusion via Sparse Attention Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T00:38:16.756350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:38:16.756350Z digest=sha256:fa7da5f6d4e808415c984331dfc55b8bbcf20b81c5827dd995fe0c997b2d0e27

Observation b7656c70-6a2a-4a09-8c50-63ae29857d0e · inbound

SynthForensics: Benchmarking and Evaluating People-Centric Synthetic Video Deepfakes cites this paper.

SynthForensics: Benchmarking and Evaluating People-Centric Synthetic Video Deepfakes Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-05-16T07:37:33.004272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T07:32:30.580643Z digest=sha256:74a1058206543d87ecac2cd88c6ced4e72d207835cd8426777700dfa26d545e9

Observation 0e62bd52-2d15-480a-bbfb-50601633d2a4 · inbound

Rolling Sink: Bridging Limited-Horizon Training and Open-Ended Testing in Autoregressive Video Diffusion cites this paper.

Rolling Sink: Bridging Limited-Horizon Training and Open-Ended Testing in Autoregressive Video Diffusion Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 39

Resolution
metadata mismatch
local_arxiv, observed 2026-05-16T07:07:29.936372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T07:02:38.876518Z digest=sha256:62c2789a2f1694ad01a6381b5e0ce39f7db8eb259f72268f24579e33e4eca65b

Observation 83cdffda-753c-467b-85c2-6817a9d57bf5 · inbound

RISE: Self-Improving Robot Policy with Compositional World Model cites this paper.

RISE: Self-Improving Robot Policy with Compositional World Model Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-05-16T02:30:32.150300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T02:28:37.997148Z digest=sha256:0689046151bcccf8dbf98d337df257ed30435898ff38dce89019e21d1bd3d3da

Observation cb43ca7b-8642-4ed0-b9d1-39661d434e96 · inbound

Latent Generative Solvers for Generalizable Long-Term Physics Simulation cites this paper.

Latent Generative Solvers for Generalizable Long-Term Physics Simulation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-05-16T05:22:22.587775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T05:21:13.280286Z digest=sha256:7f0f4e5bda9b0b7fe84c19b732e4df4dd6f70e2b19ab568464b7475d0c979951

Observation 32cf6f5a-9fd5-4e50-9be7-f15357e5127a · inbound

EchoTorrent: Towards Swift, Sustained, and Streaming Multi-Modal Video Generation cites this paper.

EchoTorrent: Towards Swift, Sustained, and Streaming Multi-Modal Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 17

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verified exact
local_arxiv, observed 2026-05-15T22:20:22.360865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T22:20:16.320171Z digest=sha256:b5446adbd58d63bed9b694ad4aae5d74887596e44dc9998f028c7e99ff70c163

Observation 51656547-767d-408f-8411-4c131d1cd1a8 · inbound

WoVR: World Models as Reliable Simulators for Post-Training VLA Policies with RL cites this paper.

WoVR: World Models as Reliable Simulators for Post-Training VLA Policies with RL Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-02T23:23:53.847694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:23:53.847694Z digest=sha256:5d617b21f4640c0db7c482c341a5348fd3a3e930fbeab27cd79362f1b48bb888

Observation a11e67e2-907b-4cdf-893e-6c169d6b9f97 · inbound

World Action Models are Zero-shot Policies cites this paper.

World Action Models are Zero-shot Policies Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-05-11T16:18:15.290841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T16:18:15.003371Z digest=sha256:bc9227e46728d7b3676077dc55bdfa0d2fa4d9b3aa565a425374b6b8b92adc3a

Observation 3ecd02e1-5725-4e8f-b0f5-e458e778e781 · 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 Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-02T20:36:10.350756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T20:36:10.350756Z digest=sha256:0739c24e4e2ef385bf41cf9dbdce7678256453acbae093eb76d1656685ddb232

Observation 34df3ac6-001d-4bfe-b725-74839451b061 · inbound

GeoWorld: Geometric World Models cites this paper.

GeoWorld: Geometric World Models Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-05-21T11:40:03.277250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T11:39:15.308355Z digest=sha256:6c0c15f16dfcf819fbe26c84a882a40fa6c9933eba3f420359f349792e60c00a

Observation a3f216af-b4b9-4324-a2f6-64810069be24 · inbound

ShareVerse: Multi-Agent Consistent Video Generation for Shared World Modeling cites this paper.

ShareVerse: Multi-Agent Consistent Video Generation for Shared World Modeling Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-02T19:20:40.047678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T19:20:40.047678Z digest=sha256:b1bd9f9674dafc9a2335ef977ab8e0b8736f379334b06c4415d8f6779b0eafb2

Observation 08b39d50-d12d-4255-ae7b-04dcc988592b · inbound

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

VIGOR: VIdeo Geometry-Oriented Reward for Temporal Generative Alignment Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 22

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:dee7ba21c652af1ae517393e99981b4c63914b6b239e6f15523fbcc882d76052

Observation 12879bd4-a172-43d0-9b92-4658eab2ce44 · inbound

AR-CoPO: Align Autoregressive Video Generation with Contrastive Policy Optimization cites this paper.

AR-CoPO: Align Autoregressive Video Generation with Contrastive Policy Optimization Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 4

Resolution
unresolved
no resolver link, observed 2026-07-13T23:09:50.674516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T23:09:50.674516Z digest=sha256:73d84cc3535cd967d18cde924443d6f30e5cec42a339e2cc5fc283cfe20ab766

Observation 4b1f0287-47c8-460d-b0b4-3aa35361f9b8 · inbound

ChopGrad: Pixel-Wise Losses for Latent Video Diffusion via Truncated Backpropagation cites this paper.

ChopGrad: Pixel-Wise Losses for Latent Video Diffusion via Truncated Backpropagation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 26

Resolution
metadata mismatch
local_arxiv, observed 2026-05-15T09:45:23.223991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T09:42:26.074609Z digest=sha256:db97e1bf6f1a75ce8e34a06312db14bbf9319d4edb98d6e35aff709929794b3c

Observation 75102867-81bb-447d-940e-4d724eac8954 · inbound

MuSteerNet: Human Reaction Generation from Videos via Observation-Reaction Mutual Steering cites this paper.

MuSteerNet: Human Reaction Generation from Videos via Observation-Reaction Mutual Steering Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 18

Resolution
metadata mismatch
local_arxiv, observed 2026-05-15T08:19:52.531626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T08:17:00.580559Z digest=sha256:71845ab04623a366194620eb7052e768ab8a0d177e46287a07b3cdb83fa94964

Observation a423a6e7-f48a-4c20-a9b6-83c9e2bff728 · inbound

I3DM: Implicit 3D-aware Memory Retrieval and Injection for Consistent Video Scene Generation cites this paper.

I3DM: Implicit 3D-aware Memory Retrieval and Injection for Consistent Video Scene Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-03T02:30:19.287583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T02:30:19.287583Z digest=sha256:5269973b1f71ae743ee57194cfb0c5932a865fe504750c917157682f3e358b59

Observation 1cdc0ceb-0d57-49a2-8e89-8598b6527a75 · inbound

Salt: Self-Consistent Distribution Matching with Cache-Aware Training for Fast Video Generation cites this paper.

Salt: Self-Consistent Distribution Matching with Cache-Aware Training for Fast Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 13

Resolution
metadata mismatch
local_arxiv, observed 2026-05-13T19:43:11.451956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-13T19:38:54.942114Z digest=sha256:60fa5291dacc0c1de687c03c235ca4e0fa0898c227b41e46e2bb10722b7d9b45

Observation 21cfc8df-0d6a-40dc-8f2c-615a7029aa4d · inbound

Evolution of Video Generative Foundations cites this paper.

Evolution of Video Generative Foundations Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 92

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T18:41:38.616611Z digest=sha256:b384044ddd81fffda03d0cdd8f0be1d1338484118ca2f9c6250e8d9e96819317

Observation 8d778f67-cedf-479b-a24b-8193469cee74 · inbound

Grounded Forcing: Bridging Time-Independent Semantics and Proximal Dynamics in Autoregressive Video Synthesis cites this paper.

Grounded Forcing: Bridging Time-Independent Semantics and Proximal Dynamics in Autoregressive Video Synthesis Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 10

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T18:32:01.665435Z digest=sha256:a3271fc15c3db00801d0df5c6763eee7a3311a4ceb99c69f486a2efd3b400a8d

Observation b832f390-1a62-491a-b268-798f8a467844 · inbound

INSPATIO-WORLD: A Real-Time 4D World Simulator via Spatiotemporal Autoregressive Modeling cites this paper.

INSPATIO-WORLD: A Real-Time 4D World Simulator via Spatiotemporal Autoregressive Modeling Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T19:08:56.588282Z digest=sha256:4ee98e14b2ce59323f0297b14b3d4ea3f5f258b9f637231865c4fe2afbe4d336

Observation 99f41c3e-a70a-448e-b9b1-936e18295cd7 · inbound

LPM 1.0: Video-based Character Performance Model cites this paper.

LPM 1.0: Video-based Character Performance Model Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 69

Resolution
verified exact
local_arxiv, observed 2026-05-11T07:30:59.878767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:09:17.360697Z digest=sha256:1681a895c5b4e66822dc44a9b38d0f9f675f2b242f4a0e3491a31f13a4a215d8

Observation 66d3b328-18d6-41f6-bcaf-a0c28c9a973d · inbound

ReconPhys: Reconstruct Appearance and Physical Attributes from Single Video cites this paper.

ReconPhys: Reconstruct Appearance and Physical Attributes from Single Video Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-05-11T07:50:57.805240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T16:57:29.556084Z digest=sha256:533d11a36d4e955e7f417e012df22439e0c46c6ef4784d2689a962c031ab027e

Observation cbaa8a7f-c5f3-45df-bd3b-886ed8f2df7e · inbound

Lighting-grounded Video Generation with Renderer-based Agent Reasoning cites this paper.

Lighting-grounded Video Generation with Renderer-based Agent Reasoning Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-05-11T06:36:01.742328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:34:39.848940Z digest=sha256:93d3353f264a530ed01f2221c53f6dccceab23b63896a3237b793a089eb84475

Observation 357e4927-7a2e-4e73-ade0-63a223780f9e · inbound

Multi-Modal Learning meets Genetic Programming: Analyzing Alignment in Latent Space Optimization cites this paper.

Multi-Modal Learning meets Genetic Programming: Analyzing Alignment in Latent Space Optimization Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 17

Resolution
unresolved
no resolver link, observed 2026-07-12T23:58:40.131335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T23:58:40.131335Z digest=sha256:918f9e506807fed193fcd1d51bb3e3c7179946f264eab113b210168b95208b94

Observation 83fbd391-dc06-4c2e-994a-4cbf3871dbf0 · inbound

DiV-INR: Extreme Low-Bitrate Diffusion Video Compression with INR Conditioning cites this paper.

DiV-INR: Extreme Low-Bitrate Diffusion Video Compression with INR Conditioning Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:21:16.076729Z digest=sha256:1af52a6b92cb9b54798059e5bebf78076855d2fbe0cd592fdfd5c5521ea822f6

Observation 53b60662-929e-4b12-bc56-29732c98dda7 · inbound

Matrix-Game 3.0: Real-Time and Streaming Interactive World Model with Long-Horizon Memory cites this paper.

Matrix-Game 3.0: Real-Time and Streaming Interactive World Model with Long-Horizon Memory Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T18:24:14.349469Z digest=sha256:90312ccc8638eca406ce58d689f544e4aa11aa3b1224ce301b3c646cad1a3556

Observation 2a1491a6-ed61-42e0-942a-78a47701fb9d · 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 Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 15

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T09:11:10.156812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T16:10:54.363560Z digest=sha256:2a237dbea2a0b4d1fe0893c8c23a46ecf11069ea839a5fda83e833382b22d6e6

Observation bf83eb8c-ca66-440f-8a53-5685ac55a413 · inbound

Lyra 2.0: Explorable Generative 3D Worlds cites this paper.

Lyra 2.0: Explorable Generative 3D Worlds Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-05-11T10:25:59.730325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T15:30:57.712342Z digest=sha256:efb803adf3f3d063ddf3719cd0091d7fbce6d2260570c78cc147e1340f4f51b6

Observation 8eb0e04e-c812-4373-adfc-e026746e6d05 · inbound

DiT as Real-Time Rerenderer: Streaming Video Stylization with Autoregressive Diffusion Transformer cites this paper.

DiT as Real-Time Rerenderer: Streaming Video Stylization with Autoregressive Diffusion Transformer Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T14:19:55.598710Z digest=sha256:badc1dc5f33f39bd7bafae54c472e82647d3c14a5372fcc098aac08446da59bd

Observation 1c62217c-2e22-4ff5-b158-714a72d3e312 · inbound

From Synchrony to Sequence: Exo-to-Ego Generation via Interpolation cites this paper.

From Synchrony to Sequence: Exo-to-Ego Generation via Interpolation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T13:23:35.738229Z digest=sha256:f85f6fd27282f34fb30dbd650ed6897a19af438ba8b06a492a2abd4c8660acb4

Observation caa3b6ee-941c-421b-a5b9-7535765fe2d3 · inbound

From Synchrony to Sequence: Exo-to-Ego Generation via Interpolation cites this paper.

From Synchrony to Sequence: Exo-to-Ego Generation via Interpolation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 18

Resolution
unresolved
no resolver link, observed 2026-07-12T20:34:35.048469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T20:34:35.048469Z digest=sha256:0763519d5c14135c149511334cf0c05aaa9d483deb6228c6d5d76ca48c76629b

Observation b93cd7fa-d3b0-4901-94b3-81c7add578a8 · inbound

HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds cites this paper.

HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T13:45:24.961208Z digest=sha256:4627c6b55eaf83623dec2bcde6d107509b4742f83e091880abf7e14824c1f511

Observation b37966fc-e6c7-44f0-9909-c4b307c00b10 · inbound

TurboTalk: Progressive Distillation for One-Step Audio-Driven Talking Avatar Generation cites this paper.

TurboTalk: Progressive Distillation for One-Step Audio-Driven Talking Avatar Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T11:13:27.689539Z digest=sha256:1b1ac25294bd861cb54bc503890f8f8535a80246f4d90f4f2c7dae72f120ed0d

Observation 32019b4a-72f4-4457-8982-91b7bf59a90f · inbound

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

Efficient Video Diffusion Models: Advancements and Challenges Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 297

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T08:28:29.706249Z digest=sha256:67c3da2e413ec4211f06c239d4033d7d5aa9e5788a92a67dc89a665d4566a753

Observation 0f447374-8d99-4fb6-9616-90fc977ac98b · inbound

Repurposing 3D Generative Model for Autoregressive Layout Generation cites this paper.

Repurposing 3D Generative Model for Autoregressive Layout Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T08:09:00.779456Z digest=sha256:f88ad13a81f63939df9f945dd4801b8029e993b05d08abac340d8e3128f2059f

Observation a67ce22a-459d-4326-a356-923c0e085dc4 · inbound

Human Cognition in Machines: A Unified Perspective of World Models cites this paper.

Human Cognition in Machines: A Unified Perspective of World Models Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T08:12:15.663761Z digest=sha256:1713dbe2b9e7859c0dcefb73f562a0b4f70a8b4189e0f92bfa6c82bba54814a8

Observation f1aae549-6382-4a31-8eec-c09459df0f6f · inbound

Speculative Decoding for Autoregressive Video Generation cites this paper.

Speculative Decoding for Autoregressive Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T06:10:41.082951Z digest=sha256:eb71ce28b49dd75a671a354091988dc8584ba7fca56a3e4ba52016209ec418b7

Observation 8844f294-d861-4043-aadb-5c4bb320bed4 · 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 Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T04:49:44.525757Z digest=sha256:6444222a30b96dffda07e6f30683aed6caf6f4fdaaac42c3e028c710655ee480

Observation 152fc266-e4a2-4b25-ac6a-109ddffa4dec · inbound

MultiWorld: Scalable Multi-Agent Multi-View Video World Models cites this paper.

MultiWorld: Scalable Multi-Agent Multi-View Video World Models Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T05:06:11.514186Z digest=sha256:5a7aee429ae7bb301f777806ab9dd851d75e0cec4816ea211a8d2cb8ff287488

Observation 3fccc004-b223-446e-b585-879e26e18665 · inbound

PortraitDirector: A Hierarchical Disentanglement Framework for Controllable and Real-time Facial Reenactment cites this paper.

PortraitDirector: A Hierarchical Disentanglement Framework for Controllable and Real-time Facial Reenactment Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-11T12:31:04.317303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T03:30:18.645845Z digest=sha256:b9a515280d8dfd11f5a6d77c3b80413d21fcb042aeececa3ff420ff902e559f9

Observation 0692e593-6002-4dfe-841f-c907c9d10e36 · inbound

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

CityRAG: Stepping Into a City via Spatially-Grounded Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 27

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T13:11:23.974996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T02:10:54.935053Z digest=sha256:aef6315ca85f6b816b508dd6559ad2736a4e92639480e1a136eff2ad7669050c

Observation 166990e0-61ce-4b93-a422-f010cbaed368 · inbound

X-Cache: Cross-Chunk Block Caching for Few-Step Autoregressive World Models Inference cites this paper.

X-Cache: Cross-Chunk Block Caching for Few-Step Autoregressive World Models Inference Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T00:19:58.480655Z digest=sha256:6be8eb105b22db9f724ce88c120d2db85029d617b7dcf644c0e043c615e603a1

Observation 9069cd3b-5865-4702-bcb0-7128b31aaff7 · inbound

Sparse Forcing: Native Trainable Sparse Attention for Real-time Autoregressive Diffusion Video Generation cites this paper.

Sparse Forcing: Native Trainable Sparse Attention for Real-time Autoregressive Diffusion Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-09T22:42:49.286967Z digest=sha256:d410f3e16f8908a82fa4210e0b75c5aa7cb202e5958a3df8562765511fe9a8b6

Observation 21241ca2-7b16-48ae-97d7-2da3470ee5b6 · inbound

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond cites this paper.

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 155

Resolution
verified exact
local_arxiv, observed 2026-05-11T19:26:08.245613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-08T12:02:07.027775Z digest=sha256:e450d948b4175155725870216603866c23a2a49b7e1ca14421fbb213fb1e645c

Observation be963475-1a69-4c46-bcb0-a0b6561be7d3 · inbound

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond cites this paper.

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 155

Resolution
verified exact
local_arxiv, observed 2026-07-04T17:29:59.589414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-04T17:29:43.764085Z digest=sha256:778b8e2c70caab9ac21db0933a724e03216e17f1348ea28fd42ccf11f3f6a43d

Observation 0d1901f3-6911-45e9-a7ce-09e36467ce6c · inbound

Hallo-Live: Real-Time Streaming Joint Audio-Video Avatar Generation with Asynchronous Dual-Stream and Human-Centric Preference Distillation cites this paper.

Hallo-Live: Real-Time Streaming Joint Audio-Video Avatar Generation with Asynchronous Dual-Stream and Human-Centric Preference Distillation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-11T21:06:12.912952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T06:56:19.795651Z digest=sha256:9af7d6ea9c427ff407dde12ebd42fc4cbb1ac1052e4778d55cc523e5fa3ecf6b

Observation 89be9538-ebd0-4085-9823-8a620f7ee2e8 · inbound

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

A Systematic Post-Train Framework for Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-05-11T23:26:19.855952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-07T16:58:33.014401Z digest=sha256:439c180ed932de45fdcc258deb52ee721262cffbfbb0cee4d6e9355d57dc5104

Observation ee8c4a9c-1b08-4428-9553-2b28688cab89 · inbound

Mutual Forcing: Dual-Mode Self-Evolution for Fast Autoregressive Audio-Video Character Generation cites this paper.

Mutual Forcing: Dual-Mode Self-Evolution for Fast Autoregressive Audio-Video Character Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-05-11T23:31:14.874434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-07T16:54:23.108142Z digest=sha256:effad274021baf3c6c6ad82714f7937c7954bfda75996ef5acdb5e08de3ba768

Observation 4f4ee25b-536b-491f-8b82-73a8ac3f2495 · inbound

Divide and Conquer: Decoupled Representation Alignment for Multimodal World Models cites this paper.

Divide and Conquer: Decoupled Representation Alignment for Multimodal World Models Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 18

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T09:46:02.822785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T15:51:12.604102Z digest=sha256:8a565eecd83e0489e839c8557e49ba750f2034244410c8dfefbabcf542e10102

Observation d6831395-87f5-447f-ae13-daa5a933fc9f · inbound

Divide and Conquer: Decoupled Representation Alignment for Multimodal World Models cites this paper.

Divide and Conquer: Decoupled Representation Alignment for Multimodal World Models Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 18

Resolution
metadata mismatch
local_arxiv, observed 2026-07-02T23:57:27.917885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-02T23:56:39.865433Z digest=sha256:ac0132c8e6ecc86663a956338724da76f7579b70a2a82457372cd72a6b42de08

Observation a69dbc51-67f2-4b6a-9975-3fc625b83bff · inbound

AsymTalker: Identity-Consistent Long-Term Talking Head Generation via Asymmetric Distillation cites this paper.

AsymTalker: Identity-Consistent Long-Term Talking Head Generation via Asymmetric Distillation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-05-11T15:16:11.402538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-09T20:19:39.565157Z digest=sha256:6cfa87a2f90e2a417818042bbab937f99e1d682e50814da8244a3f3eb5239f87

Observation c3d78d1d-3c7e-4c31-b38e-7203400c4b0d · inbound

AsymTalker: Identity-Consistent Long-Term Talking Head Generation via Asymmetric Distillation cites this paper.

AsymTalker: Identity-Consistent Long-Term Talking Head Generation via Asymmetric Distillation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-05-11T03:45:57.433139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T02:18:58.996355Z digest=sha256:cfa40c373d67035e2ffa44ac558cd3429811b6a1965e7e574f3698834909a154

Observation ecba1afa-6e99-4a87-b56f-9a2335b6f74d · inbound

Stream-R1: Reliability-Perplexity Aware Reward Distillation for Streaming Video Generation cites this paper.

Stream-R1: Reliability-Perplexity Aware Reward Distillation for Streaming Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-11T23:16:36.755698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-07T17:38:08.199955Z digest=sha256:7321b3698657be1a493ee6aa96efcfb83d0a46cdf95544128ef11288abec7bb0

Observation e0127b0a-35f7-4e7e-9a01-0c0503386fb4 · inbound

Stream-T1: Test-Time Scaling for Streaming Video Generation cites this paper.

Stream-T1: Test-Time Scaling for Streaming Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:36:53.812910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T18:16:14.985693Z digest=sha256:affd39eda43b3e592064c821e5c3d3112a982333c16c2fe0fa830df1c34f1aea

Observation 38ff8182-cb1a-46b5-ab65-69412d05fc42 · inbound

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models cites this paper.

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 35

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T17:36:06.014038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T17:25:26.391582Z digest=sha256:bd9f7b1f12ae2f76bfc4442d0c6164becc5fb981bbe2630a79c0ea55e66b05aa

Observation 44243efc-bede-42db-9e84-1649d295bf85 · inbound

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models cites this paper.

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 35

Resolution
metadata mismatch
local_arxiv, observed 2026-05-20T23:19:13.375952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-20T23:18:35.390642Z digest=sha256:a07feede1522f6c11065a822bb846fc5e533af8584baa874b1a9ad6a96fb78a2

Observation 305b9139-d664-40a2-a70d-565efc2005b9 · inbound

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models cites this paper.

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 35

Resolution
metadata mismatch
local_arxiv, observed 2026-06-30T23:45:07.755855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T23:44:10.302520Z digest=sha256:9640fad1ffad132f03cf8c0a1fcb4ea5f6efc314482eee6b692897a8f7be0074

Observation d33539ee-4185-4895-899a-4bf7ab8fbf27 · inbound

RealCam: Real-Time Novel-View Video Generation with Interactive Camera Control cites this paper.

RealCam: Real-Time Novel-View Video Generation with Interactive Camera Control Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 12

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T16:41:16.444350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-09T15:22:04.387900Z digest=sha256:e19db8ffcf64423f103b297afe14025b16dec573f48a7e36e18a36bc78d9ec12

Observation e2db436d-e6de-455e-98f7-65eee5e27e9e · inbound

FreeSpec: Training-Free Long Video Generation via Singular-Spectrum Reconstruction cites this paper.

FreeSpec: Training-Free Long Video Generation via Singular-Spectrum Reconstruction Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-05-11T18:56:07.736852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T13:11:46.079614Z digest=sha256:da1eb0282e49bf5e9d44db39430ea346e868ad6e52385bfe94df5e4f1ac37e47

Observation 85a5eb79-c4e9-4422-bc7a-4707e91b9caf · inbound

FlashMol: High-Quality Molecule Generation in as Few as Four Steps cites this paper.

FlashMol: High-Quality Molecule Generation in as Few as Four Steps Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-05-11T04:50:57.812713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:01:39.724352Z digest=sha256:ff9450cc79c6817e442df78a71b698119df778d87425f1f6a1795f972bd165c1

Observation 2f4720bc-1bb9-4f6f-9803-64edf7fd90b1 · inbound

Sword: Style-Robust World Models as Simulators via Dynamic Latent Bootstrapping for VLA Policy Post-Training cites this paper.

Sword: Style-Robust World Models as Simulators via Dynamic Latent Bootstrapping for VLA Policy Post-Training Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-05-11T04:40:59.040838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:10:09.166876Z digest=sha256:77e80132f76c76af4994b6921f4ee42d09c987f73b05098f3a90c8869459a19b

Observation 55e756c5-8acb-4f63-9d1a-33f93c0b7a9f · inbound

ACWM-Phys: Investigating Generalized Physical Interaction in Action-Conditioned Video World Models cites this paper.

ACWM-Phys: Investigating Generalized Physical Interaction in Action-Conditioned Video World Models Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-05-12T07:31:35.216141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-12T02:32:24.412202Z digest=sha256:309b054384ddc0393d4c21264bee69e251128f0768b07e23888265dd200e2e04

Observation 3671d792-ab5c-40a0-b0e5-8f24434c72e5 · inbound

ACWM-Phys: Investigating Generalized Physical Interaction in Action-Conditioned Video World Models cites this paper.

ACWM-Phys: Investigating Generalized Physical Interaction in Action-Conditioned Video World Models Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-05-20T23:39:13.430250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-20T23:36:21.849680Z digest=sha256:5fb3ee1671caaa8b5fe69985cc9afc04ba2207535392ad2404caf45bf69a4b02

Observation d2dd4fd6-b2d8-482a-8673-38f75d11cb1b · inbound

Unison: Harmonizing Motion, Speech, and Sound for Human-Centric Audio-Video Generation cites this paper.

Unison: Harmonizing Motion, Speech, and Sound for Human-Centric Audio-Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-05-12T07:36:44.553350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-12T02:28:14.734682Z digest=sha256:e0dd21ca8e0cdf71bdec05eaa9ec0ef865b3ba9a08560144a243d6d12e00663e

Observation a4ff9e15-f28c-4930-aec3-f6a4c4a9c6c4 · inbound

Unison: Harmonizing Motion, Speech, and Sound for Human-Centric Audio-Video Generation cites this paper.

Unison: Harmonizing Motion, Speech, and Sound for Human-Centric Audio-Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-06-30T23:35:07.809287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T23:26:46.077894Z digest=sha256:efd0341e0f4918c8a223ccf953d936b3eef3de3c38e705e3b77de43a812271df

Observation 78bff942-2c9e-4f44-8a1d-d267b3ced9ee · inbound

SWIFT: Prompt-Adaptive Memory for Efficient Interactive Long Video Generation cites this paper.

SWIFT: Prompt-Adaptive Memory for Efficient Interactive Long Video Generation Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-05-12T05:46:30.532347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-12T04:57:38.215348Z digest=sha256:d2a7f2b6f4d82904fa1b4e6e67c576b01a967aa9ae84887de97847998a30556c