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Paper Citation Record · LEDGER

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

As of 9 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 16 inbound Pith citation observations for arXiv:2505.24873.

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

pith.paper-citation-record.v1
2505.24873 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:21:42.065655Z

measured 77 of 77 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:27:35.548130Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T02:16:26.810645Z

Reference resolution

61 of 61 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved44
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4e9e34b4-b847-4492-ab9e-b57e798236d0 · outbound

This paper cites Frozen in time: A joint video and image encoder for end-to-end retrieval.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Frozen in time: A joint video and image encoder for end-to-end retrieval

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:46.487994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:37.718449Z digest=sha256:50d18a52dafdb0817c87aa4fe1e0d1ecb6a3ddbb22002e5e2a1d21c885e51d1e

Observation 49e7dcae-35a7-4f6b-a7e6-111ea4f5f256 · outbound

This paper cites VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Control.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Control

Reference 2

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no resolver link, observed 2026-08-07T12:21:37.764238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:37.764238Z digest=sha256:cd1c5d092e7c8e9f1f664a87d4d15db9e0306ba3c2d2a92b021c8b34675c781d

Observation 07aff419-c706-453a-ad96-669c93ed7a3d · outbound

This paper cites Black forest labs.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Black forest labs

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:46.264439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:37.869257Z digest=sha256:4cb76e09907f0abc6c208bd79d569190cb56d469a5c102fd7742e43bc431f095

Observation 1fc82f3b-25a4-4c42-93aa-5169019cb866 · outbound

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

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Align your latents: High-resolution video synthesis with latent diffusion models

Reference 4

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no resolver link, observed 2026-08-07T12:21:37.960876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:37.960876Z digest=sha256:a2f58acce6641b58b8cf3ce5e1cd6cd380ac4e05a62a67697e8801b2c7503793

Observation 59d9e455-8c3b-46fe-b7e2-e006cb564c31 · outbound

This paper cites Cambridge university press, 2004.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Cambridge university press, 2004

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.042874Z digest=sha256:9141d67fa4524620955189520734bc0a2c960a5fb62c714e50bfc11fc9c97178

Observation cc3dd790-9fe7-4165-9dd0-fe9440429e34 · outbound

This paper cites Instructpix2pix: Learning to follow image editing instructions.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Instructpix2pix: Learning to follow image editing instructions

Reference 6

Resolution
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no resolver link, observed 2026-08-07T12:21:38.073840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.073840Z digest=sha256:c28f5a5c19299985b4adc15037f558303d4bb327d07d46cb0d8995af60460109

Observation 1e4c4e0b-cd52-4c54-aba1-45371a13100c · outbound

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

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Videocrafter2: Overcoming data limitations for high-quality video diffusion models

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:46.049250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:38.103657Z digest=sha256:fedac26bb730da3892e69c78edb2962548a4a4042628f830b064bbacbfdcc404

Observation 423e3c65-1f93-4358-a577-eb83da28a07e · outbound

This paper cites Consistent video-to-video transfer using synthetic dataset.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Consistent video-to-video transfer using synthetic dataset

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:45.858156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:38.131143Z digest=sha256:196cc427f016089d6a097c9b57f2bcd0296b053ec403e8e67f12d93c1bf84673

Observation 5be7086f-d596-46e8-a9ca-1160bf28d963 · outbound

This paper cites FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing

Reference 9

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no resolver link, observed 2026-08-07T12:21:38.134031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.134031Z digest=sha256:458c923d7a1784f87e80c5d1afa597c60f7c772ee7be1d61607604506953f119

Observation 4fa23242-a513-421e-8823-c7bdd4f1fb6a · outbound

This paper cites Introducing gen-3 alpha: A new frontier for video generation.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Introducing gen-3 alpha: A new frontier for video generation

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:45.670165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:38.139830Z digest=sha256:a1badf33509c6be89519e94ac290e72b289a6ef78ce24c0450eb53fc5936aa3b

Observation dc8b2f51-a8d1-4acd-9728-938995b94697 · outbound

This paper cites Instructdiffusion: A generalist modeling interface for vision tasks.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Instructdiffusion: A generalist modeling interface for vision tasks

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:45.475675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:38.179653Z digest=sha256:b3d34ddb2ae73e3d8d417f23727ac47ef263cd9b2f0b810894e33d0bbfc32078

Observation 52880996-4c1f-46e8-af12-b882e0e02b0b · outbound

This paper cites TokenFlow: Consistent Diffusion Features for Consistent Video Editing.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal TokenFlow: Consistent Diffusion Features for Consistent Video Editing

Reference 12

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no resolver link, observed 2026-08-07T12:21:38.265921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.265921Z digest=sha256:82966b6f2b091cfa2f6518d3b94f10bcd9f10115b385cfc0dbd670bdb00c6989

Observation dd3b525a-f6e4-486b-874c-a6ad09011c8f · outbound

This paper cites Generative adversarial nets.Advances in neural information processing systems, 27, 2014.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Generative adversarial nets.Advances in neural information processing systems, 27, 2014

Reference 13

Resolution
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no resolver link, observed 2026-08-07T12:21:38.401315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.401315Z digest=sha256:a4db3f4e391cb03ac30969e7c5645b5d74000e5f165c751f847d3ab2555c1e32

Observation 9428ab5e-af03-4300-a832-a926ccf0ad14 · outbound

This paper cites Coherent Video Inpainting Using Optical Flow-Guided Efficient Diffusion.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Coherent Video Inpainting Using Optical Flow-Guided Efficient Diffusion

Reference 14

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unresolved
no resolver link, observed 2026-08-07T12:21:38.498549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.498549Z digest=sha256:10fee47c36840a288f68fc49165e0b6df9d7a2613df7ea4fbfa55e40c9385ff1

Observation e361fae5-cd09-410c-8fef-78d0190959c2 · outbound

This paper cites AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

Reference 15

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no resolver link, observed 2026-08-07T12:21:38.598679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.598679Z digest=sha256:973a0e291766eb0bcb0ba42636ebec15bfd3c374b3e60f0a57389fd620fe1f62

Observation 132db5f5-a773-40bb-af61-462f7d6c577c · outbound

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

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal LTX-Video: Realtime Video Latent Diffusion

Reference 16

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unresolved
no resolver link, observed 2026-08-07T12:21:38.733783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.733783Z digest=sha256:f9e2ab8e6ee1cd9458dcb8c1da82899dce4d863c5bee49b4a95f4a09c75fe744

Observation 0d9922c7-62b2-43ca-80f8-40dd80126095 · outbound

This paper cites Classifier-Free Diffusion Guidance.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Classifier-Free Diffusion Guidance

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.803360Z digest=sha256:550257ae6946509a1b01543bfd8ab29319be68cfa0dd9b77ca3e52add9f49dfc

Observation f617f3a5-e179-45cd-86e8-ac1931bcd33a · outbound

This paper cites CogVLM2: Visual Language Models for Image and Video Understanding.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal CogVLM2: Visual Language Models for Image and Video Understanding

Reference 18

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no resolver link, observed 2026-08-07T12:21:38.829107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.829107Z digest=sha256:c1d3e68d8863cbcebef38a2a0c4fc27d71d452b28bdc7b9e2bc7b7ec11ac2aa8

Observation 2a3962f7-d4c2-454d-ae84-c82e39445a20 · outbound

This paper cites VIVID-10M: A Dataset and Baseline for Versatile and Interactive Video Local Editing.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal VIVID-10M: A Dataset and Baseline for Versatile and Interactive Video Local Editing

Reference 19

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no resolver link, observed 2026-08-07T12:21:38.845137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.845137Z digest=sha256:1b02f599fe74b78eab1bda0c2b32a2eb9c31e9d5123cf06c599bd8eed5816c20

Observation 52eb0af1-eac9-491c-a441-8f69e0e1a4ef · outbound

This paper cites VACE: All-in-One Video Creation and Editing.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal VACE: All-in-One Video Creation and Editing

Reference 20

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no resolver link, observed 2026-08-07T12:21:38.858951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.858951Z digest=sha256:652703b6c4d13b5feb71580d942f925943cbdc400dc2de886179c0e5359fc459

Observation 9700408a-a9a2-4b60-959a-c3d628c14380 · outbound

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

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 21

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no resolver link, observed 2026-08-07T12:21:38.878426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.878426Z digest=sha256:e5325154941ac93477c5677a9a0b91539e7bc8b1cfac1656de8ce2f6b852cbfb

Observation 6c689d82-3206-4d09-ad4a-bde261937c91 · outbound

This paper cites AnyV2V: A Tuning-Free Framework For Any Video-to-Video Editing Tasks.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal AnyV2V: A Tuning-Free Framework For Any Video-to-Video Editing Tasks

Reference 22

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no resolver link, observed 2026-08-07T12:21:38.894445Z

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source=pdf_text observed=2026-08-07T12:21:38.894445Z digest=sha256:889d0c0a60fe3329d31c65037429df3cb8dc67706467ecdeeb9ad948de7bd77a

Observation cd76d8d2-67d3-41f1-a0c8-aaa8baf42a7d · outbound

This paper cites Video diffusion models are strong video inpainter.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Video diffusion models are strong video inpainter

Reference 23

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no resolver link, observed 2026-08-07T12:21:38.922498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.922498Z digest=sha256:b8ca47f6c9d71c8ea4de9bceb5dfbce807bfd7389956bb4e636894cc6cf9560d

Observation e8d183c1-4c2d-4405-893d-34c7a5baf3e6 · outbound

This paper cites DiffuEraser: A Diffusion Model for Video Inpainting.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal DiffuEraser: A Diffusion Model for Video Inpainting

Reference 24

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no resolver link, observed 2026-08-07T12:21:38.948092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.948092Z digest=sha256:dd153eab0f8d4648961a61b59b32c27b6eb6f175a8cefbc7ecf0a92aee5ae82a

Observation 87663c37-c561-4174-82e0-302fdd0b8aba · outbound

This paper cites Stablev2v: Stablizing shape consistency in video-to-video editing.arXiv preprint arXiv:2411.11045, 2024.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Stablev2v: Stablizing shape consistency in video-to-video editing.arXiv preprint arXiv:2411.11045, 2024

Reference 25

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no resolver link, observed 2026-08-07T12:21:38.982889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:38.982889Z digest=sha256:9befe9fe091dbaabfc35e20581a7bfb39b5c5407618b9d2c88fea8586306ed34

Observation cc018715-0fd9-4de2-86f7-81a964e45b56 · outbound

This paper cites Generative Video Propagation.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Generative Video Propagation

Reference 26

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no resolver link, observed 2026-08-07T12:21:39.009460Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:39.009460Z digest=sha256:646a8ee1e9b1a69841b9e0b9f2cfd82534fcdf9403e60cd603758b9cdb85ce80

Observation 05e0f5de-50cc-4d55-a6a9-0bc7e558a946 · outbound

This paper cites Video-p2p: Video editing with cross-attention control.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Video-p2p: Video editing with cross-attention control

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:45.291025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:39.039999Z digest=sha256:d17664b97149bef1529a86d439298c76c5823eb2827ddcb6e58fd5657f705b64

Observation d79d7a62-a57e-4b25-8f27-0f206f83aed5 · outbound

This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 28

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no resolver link, observed 2026-08-07T12:21:39.075125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:39.075125Z digest=sha256:097b697fe9babf004b48ed13df838f7400e48c314300568921bde7075f203b0a

Observation 67dc751d-7ca8-41a2-a1e0-9c2f7250d3bf · outbound

This paper cites Step1X-Edit: A Practical Framework for General Image Editing.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Step1X-Edit: A Practical Framework for General Image Editing

Reference 29

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no resolver link, observed 2026-08-07T12:21:39.132228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:39.132228Z digest=sha256:72615a3f67f7cfd3da80c8534930a46c2dc185a2461bc14e59678b2fffe8fae8

Observation 535e463e-81a2-4225-bd44-9f9598390408 · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 30

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no resolver link, observed 2026-08-07T12:21:39.177072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:39.177072Z digest=sha256:1aade9838f393d20b772d418caea5b5e78caa3cadb4a8b95641a10dbbcb15990

Observation 5251326d-adc9-44f7-a91c-78452d6ee451 · outbound

This paper cites Decoupled Weight Decay Regularization.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Decoupled Weight Decay Regularization

Reference 31

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no resolver link, observed 2026-08-07T12:21:39.282106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:39.282106Z digest=sha256:189ba31db8ed7bffee403df6fe87749b49f47d2ef7c4fb9058a70dcd08704355

Observation 65c575a6-9743-4384-9449-b491be54e467 · outbound

This paper cites Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model

Reference 32

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no resolver link, observed 2026-08-07T12:21:39.350783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:39.350783Z digest=sha256:3233c15b41cf86fa06bd5394d9c4522c7f95776a73b1a78b67d3235c9d85cab8

Observation 1ce46552-a6c1-4735-af9f-c7b18b6d0195 · outbound

This paper cites Mochi-1.https://www.genmo.ai/blog, 2024.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Mochi-1.https://www.genmo.ai/blog, 2024

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-07T12:21:45.097503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:39.465623Z digest=sha256:d723901a95c261cb07d909146597ac5c402478be991ac52a0f1622203e893808

Observation d8363427-91bd-4082-a434-949d14218f09 · outbound

This paper cites ReVideo: Remake a Video with Motion and Content Control.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal ReVideo: Remake a Video with Motion and Content Control

Reference 34

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no resolver link, observed 2026-08-07T12:21:39.585512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:39.585512Z digest=sha256:5a29cc713af4e2495b2d1b083ccd8821ff3c58dbba390b0c800405ebff48a0f3

Observation ade1ccb2-3d72-4e96-bc62-1b1c08e65de5 · outbound

This paper cites https://openai.com/index/introducing-o3-and-o4-mini/, 2025.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal https://openai.com/index/introducing-o3-and-o4-mini/, 2025

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-07T12:21:44.938346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:39.671101Z digest=sha256:90b1a021f3a9c6ab72f7fefcc6d0f29b2da40525d6a6a98fd678e6105e3631a3

Observation 35b6b192-a666-4c87-b233-5d028fa12f5d · outbound

This paper cites Sora: Creating video from text.https://openai.com/index/sora/, 2024.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Sora: Creating video from text.https://openai.com/index/sora/, 2024

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:44.798920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:39.744323Z digest=sha256:bd8e1180e2ba709f818327abb0ed5380084d8598f73b291edaf2a9b594340a7e

Observation 8b9ce8e6-590e-4f86-8b56-ddb7d2e01711 · outbound

This paper cites Scalable Diffusion Models with Transformers.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Scalable Diffusion Models with Transformers

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:39.852461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:39.852461Z digest=sha256:0660fb2714b7c4b01867ee6c589c1104d238f4c1efe10346236422234bade18d

Observation 8dcb2cb5-722c-4556-8ade-ae6ae773786c · outbound

This paper cites https://www.pexels.com/, 2024.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal https://www.pexels.com/, 2024

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:44.643576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:39.951412Z digest=sha256:9302484814e6a433224377f2073137dafeea83f9597616aa72093d6d7eb83cb1

Observation 71eb043c-59eb-4924-8b47-f427f746e20f · outbound

This paper cites The 2017 DAVIS Challenge on Video Object Segmentation.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal The 2017 DAVIS Challenge on Video Object Segmentation

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:40.037381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:40.037381Z digest=sha256:b6cfc000642c36745592eef74bbde1153130cf1cf7b545f84a6b18e25aa8cd2c

Observation cfa281c7-0f0f-4899-b117-39d04e607332 · outbound

This paper cites Zero-shot text-to-image generation.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Zero-shot text-to-image generation

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:44.464938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:40.114557Z digest=sha256:8a4f9de85323c5f939373a3c1a4d734424c8295819dec752169ef51a88b14c31

Observation a4ac6d08-ef6a-406d-ae8e-3275b350217f · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal SAM 2: Segment Anything in Images and Videos

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:40.178621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:40.178621Z digest=sha256:b346fe2c9341e9413c1f738a4f475ba762da626c22307dd02091ba04b71106b5

Observation 1429528f-af2a-468a-b7d6-76a840148b6b · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal U-net: Convolutional networks for biomedical image segmentation

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:40.237164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:40.237164Z digest=sha256:6f967c053ffa5eb4b7544484e07b21aed44cecd3dfca9910d5179f74fb7fd235

Observation aa0b95c0-8277-4654-8afd-a1d6d2c87c7c · outbound

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

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Wan: Open and Advanced Large-Scale Video Generative Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:40.298087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:40.298087Z digest=sha256:184e73cc91f4578e5a4dcb22e43ee1884f9a06a43d5c4814c70e9566f3293bb5

Observation a0c2b062-5be5-4e5e-aff2-c9b7fc121cdd · outbound

This paper cites Modelscope text-to-video technical report, 2023.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Modelscope text-to-video technical report, 2023

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:40.366178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:40.366178Z digest=sha256:bf02397a2e2ead97e463fe28b217e82f3bca977cb3753ceae730c509fd7cb919

Observation c478aea2-4f01-4f8f-bc03-3d5620ee59ca · outbound

This paper cites Imagen editor and editbench: Advancing and evaluating text-guided image inpainting.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Imagen editor and editbench: Advancing and evaluating text-guided image inpainting

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:44.244243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:40.452953Z digest=sha256:5b06022f82a8f632a86405b99c29b24d17965a2dd7310c5f8b551a4b27bb7915

Observation 039fdf9e-1035-4463-8c96-21c11d4b8022 · outbound

This paper cites Videocomposer: Compositional video synthesis with motion controllability.Advances in Neural Information Processing Systems, 2024.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Videocomposer: Compositional video synthesis with motion controllability.Advances in Neural Information Processing Systems, 2024

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:44.022983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:40.513533Z digest=sha256:338d68dc74139c506f3f4ac7859dc910f77ca991df2722caa7f4f2830c3e97b0

Observation 4058d327-997b-4c6a-8580-a01ce42e7e78 · outbound

This paper cites Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:40.592065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:40.592065Z digest=sha256:b3ab5ba1f910aab3f4cd8cf974a635dabf484dad7f68245791f91290df8d1270

Observation ec196d75-12a0-4d09-8bcd-14dc9a00dc10 · outbound

This paper cites MTV-Inpaint: Multi-Task Long Video Inpainting.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal MTV-Inpaint: Multi-Task Long Video Inpainting

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:40.702059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:40.702059Z digest=sha256:ae579b1c78da88a9a9fd111ac743b1df47248631da086674f14a887129586387

Observation e55a3fc2-87e7-4f5d-b8e6-d876a48dc3fa · outbound

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

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Cogvideox: Text-to-video diffusion models with an expert transformer

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:43.793555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:40.773133Z digest=sha256:b7ecac3af3e4ec38ae0c9ecce2163a527cec93db0d2d10b113a9ec1abe9aa7ba

Observation 9039e777-5a0b-4284-9e85-493e24a74a55 · outbound

This paper cites Magicbrush: A manually annotated dataset for instruction-guided image editing.Advances in Neural Information Processing Systems, 36, 2024.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Magicbrush: A manually annotated dataset for instruction-guided image editing.Advances in Neural Information Processing Systems, 36, 2024

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:40.882845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:40.882845Z digest=sha256:a22fee4ac4667f1172322f9cf123b53f998049c233eebc163ac884bb76ff69de

Observation f90ad235-ea9b-414d-b1cb-ccdf7a7f6692 · outbound

This paper cites Packing input frame context in next-frame prediction models for video generation.arXiv preprint arXiv:2504.12626, 2025.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Packing input frame context in next-frame prediction models for video generation.arXiv preprint arXiv:2504.12626, 2025

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:40.975686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:40.975686Z digest=sha256:aa282abc4e1e8393145040a7edb91628c1a6618cbccc197816bcaacb07516905

Observation e3cce579-d776-464a-a2d4-bc1fb3e1ecb3 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Adding conditional control to text-to-image diffusion models

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:41.044326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:41.044326Z digest=sha256:237db913638227322cd93e5a24aeb7815b76a6f628835739aa5576ad310f36ff

Observation 0fe18295-7649-47c2-a48f-63266f6eeb90 · outbound

This paper cites AVID: Any-Length Video Inpainting with Diffusion Model.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal AVID: Any-Length Video Inpainting with Diffusion Model

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:41.124312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:41.124312Z digest=sha256:4b8cacfd0151320f2a366b514a173c644ac3b2a05a9e7d06f89b4185b46df755

Observation 36db8069-0777-4a61-a6c5-6a69a949d2c8 · outbound

This paper cites Propainter: Improving propagation and transformer for video inpainting.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Propainter: Improving propagation and transformer for video inpainting

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:43.572999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:41.200847Z digest=sha256:9fbf183c7108125606d436a4cdf4b0868407b4b99ae5cdb0e34bf2debb4d22b6

Observation 71e8ad13-ce70-4bc8-8281-4caf719b07be · outbound

This paper cites Se\~norita-2M: A High-Quality Instruction-based Dataset for General Video Editing by Video Specialists.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Se\~norita-2M: A High-Quality Instruction-based Dataset for General Video Editing by Video Specialists

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:41.308248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:41.308248Z digest=sha256:d94c3be07bc0be69837f212c755912870b45949c65c87ab402e2d33a1d0c898a

Observation b58e1b99-b7ca-4c32-83ff-76a646d7c3ed · outbound

This paper cites CoCoCo: Improving Text-Guided Video Inpainting for Better Consistency, Controllability and Compatibility.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal CoCoCo: Improving Text-Guided Video Inpainting for Better Consistency, Controllability and Compatibility

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:41.454119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:41.454119Z digest=sha256:6e14157c7c512b8122cd27e7629e19601fd6aeacbd48ffb55a71ab73664e3d78

Observation b3a5143e-8f7c-4866-a685-e435d0078057 · outbound

This paper cites an unresolved cited work.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:21:43.361056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:41.571431Z digest=sha256:660fcab6cc01a50c070b5f4a7d53eadc7e3f00bee168995cf0f3bbff77d2a615

Observation 5ad17d38-6abe-4a4b-9569-a563fe54fdc5 · outbound

This paper cites an unresolved cited work.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Unresolved cited work

Reference 58

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:21:43.213390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:41.671625Z digest=sha256:84cd1e2022f95c58b542c92b74939595af51e4fd88d9488084ff47946277c0e0

Observation 5df3d3aa-b691-4162-8ca7-9f6c4c2f7a58 · outbound

This paper cites an unresolved cited work.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:21:43.058811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:41.814382Z digest=sha256:82d54a0cb6db0591d7f409fba15d44d41e16645a452baa1e44034901aa9858ca

Observation 3d17ad8f-1b1c-4bf1-af79-61caa673ccd7 · outbound

This paper cites an unresolved cited work.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:21:42.872934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:41.923946Z digest=sha256:11ada743f2e006578d7254452fe49a36481e13244facd85dc87f4408b8022549

Observation ed3da41a-d34f-443f-bd81-7829e41a810e · outbound

This paper cites yes" or.

MiniMax-Remover: Taming Bad Noise Helps Video Object Removal yes" or

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:21:42.659359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:21:42.065655Z digest=sha256:94b184053c5cf7157719fb585e587aa554793597464440873840a9ef0c24361b

Pith citing papers

Observation 0e8b8eeb-5639-4d11-ab49-07e08fe8f4e6 · inbound

O-DisCo-Edit: Object Distortion Control for Unified Realistic Video Editing cites this paper.

O-DisCo-Edit: Object Distortion Control for Unified Realistic Video Editing MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T12:27:35.548130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:27:35.548130Z digest=sha256:500a64971d80e38a56b8192fe7388b7286ab5ba7525983614d4250786ee612eb

Observation 6ce213fa-17fa-43a7-88b8-e1248e6da60f · inbound

VideoCoF: Unified Video Editing with Temporal Reasoner cites this paper.

VideoCoF: Unified Video Editing with Temporal Reasoner MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-17T00:08:43.159407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-17T00:08:09.479706Z digest=sha256:ae0016122f77d3c9f6cc54ad1feaeb9bb5a27db0c893ea5c8d08e6dc6df87a26

Observation d2be03b6-092d-4af4-8837-256f21d96f04 · inbound

Learning Stochastic Bridges for Video Object Removal via Video-to-Video Translation cites this paper.

Learning Stochastic Bridges for Video Object Removal via Video-to-Video Translation MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-03T10:02:42.036296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:02:42.036296Z digest=sha256:8b9e42e23e50f45982e5d0343af57b6c6f3237ac611a690b94051ebfbc7ca911

Observation 23011d8a-32ed-42d9-87ad-da41aa7ab6e8 · inbound

Under One Sun: Multi-Object Generative Perception of Materials and Illumination cites this paper.

Under One Sun: Multi-Object Generative Perception of Materials and Illumination MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 73

Resolution
unresolved
no resolver link, observed 2026-07-13T22:08:47.493022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T22:08:47.493022Z digest=sha256:ebfe6a1ca204ce7a191e0a7f8ee3ab2fe6799f8b901b8f503fd763e7a0bf3841

Observation 029ef174-19f8-4b5f-bd8c-6ddcace082a3 · inbound

CLEAR: Context-Aware Learning with End-to-End Mask-Free Inference for Adaptive Video Subtitle Removal cites this paper.

CLEAR: Context-Aware Learning with End-to-End Mask-Free Inference for Adaptive Video Subtitle Removal MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-15T00:39:35.655463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T00:39:15.790131Z digest=sha256:bc69898a66365995a91a4b6ed625624c0f12ed4f9ff9e762743119af45088f78

Observation 86a22e7e-fb2a-4a74-964b-e7fb9974e417 · inbound

LIVEditor-14B: Lightning Unified Video Editing via In-Context Sparse Attention cites this paper.

LIVEditor-14B: Lightning Unified Video Editing via In-Context Sparse Attention MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 59

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T00:25:09.305580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-07-01T00:24:30.573122Z digest=sha256:c13ae2435a195b1895fbf4ac90e3b7a10e58ff35a0bc693a96d7d90da188dbbb

Observation 23bb70b9-8266-4ab3-a520-3f6880506916 · inbound

PROVE: A Perceptual RemOVal cohErence Benchmark for Visual Media cites this paper.

PROVE: A Perceptual RemOVal cohErence Benchmark for Visual Media MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T02:13:30.457949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T02:11:20.206732Z digest=sha256:241a2514407f06c2521bd4162815ccab05377f177fe28d0b6d49a073039be655

Observation aecca054-906b-4ca2-9d4e-3b7bab3970b3 · inbound

PROVE: A Perceptual RemOVal cohErence Benchmark for Visual Media cites this paper.

PROVE: A Perceptual RemOVal cohErence Benchmark for Visual Media MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-02T14:03:34.947377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:03:34.947377Z digest=sha256:0b19b9f0fc792c253121dbf68d939dce5cd77f776cb6eac04ef2f606f554639f

Observation a53197e2-e2cd-448e-b806-1655cd2b7d2e · inbound

Tuning-free Instruction-based Video Editing Via Structural Noise Initialization and Guidance cites this paper.

Tuning-free Instruction-based Video Editing Via Structural Noise Initialization and Guidance MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T14:32:36.198464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T14:30:18.778618Z digest=sha256:cbb105c85c18ca56c5ac982fd6f46048f78da340ac242b4b35cbff51bf0dfa74

Observation 27923938-5156-4a6e-a877-8809dc529996 · inbound

Occlusion-Aware Physics-Semantic Keyframe Selection for Robust Video Editing cites this paper.

Occlusion-Aware Physics-Semantic Keyframe Selection for Robust Video Editing MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 95

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:06:38.684891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-25T05:00:31.868653Z digest=sha256:e16cb294807503d54bc7efd49026070d20939030b51ace4eb32cc5af4e094ea4

Observation 2b5b0f4a-6e72-49f8-b4a6-3e90073730f8 · inbound

SimInsert: Seamless Video Object Insertion via Regional Sparse Attention Fusion cites this paper.

SimInsert: Seamless Video Object Insertion via Regional Sparse Attention Fusion MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 21

Resolution
metadata mismatch
arxiv_id, observed 2026-05-25T04:50:21.412784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-25T04:46:50.749223Z digest=sha256:b00309f9f1ad1e4a9712ef2d88d1edc33c412524aa55f3ba098705c6d8ced791

Observation 38ce57cb-28e8-48ca-888d-f22857dbb240 · inbound

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

Smart-Insertion-V: Photorealistic Video Insertion via a Closed-Loop Feedback Dual-Stream Framework MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 38

Resolution
metadata mismatch
arxiv_id, observed 2026-05-25T04:35:21.946875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-25T04:30:20.593882Z digest=sha256:1f48e9eb4e89669b0e7b117d9d0070697ceef0face4b5c1d8d13103691bb19f2

Observation f3062b54-3972-4fa1-b8e2-c07b1d0ae4e2 · inbound

GenEraser: Generalizable Video Object Removal via Balanced Text-Mask Guidance and Decoupled Locator-Preserver cites this paper.

GenEraser: Generalizable Video Object Removal via Balanced Text-Mask Guidance and Decoupled Locator-Preserver MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-06-29T08:13:15.735958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T08:06:27.191812Z digest=sha256:2c0a46ce3f3fd70dcac9d32dfabb360b67bcef9bcf11cbafb3ee104779b793e9

Observation 806f97f2-d01d-4411-a459-559b7a892109 · inbound

JAVEDIT: Joint Audio-Visual Instruction-Guided Video Editing with Agentic Data Curation cites this paper.

JAVEDIT: Joint Audio-Visual Instruction-Guided Video Editing with Agentic Data Curation MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:16:26.812069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T11:04:49.366127Z digest=sha256:2411c919bf2b6aa2f30f5c9f50b4ccc16208fa01b8f13a96b2f7e4e4e34089f4

Observation ed1031e0-a8a2-4ad6-b8a9-57dcd5eeec37 · inbound

From Draft to Draft-Free: One-Step Video Object Removal via Privileged Distillation and Fast Planting cites this paper.

From Draft to Draft-Free: One-Step Video Object Removal via Privileged Distillation and Fast Planting MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-02T00:37:34.040776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T00:37:34.040776Z digest=sha256:f63933c1a8c270c02bdef7bfba791d549d0e2c432a718da335755a14786dd291

Observation 29eb4e74-d09f-4b52-99a3-bed409b09d7e · inbound

FlexComposer: Unified Video Compositing from Images to Dynamic Footage with Flexible Trajectory Control cites this paper.

FlexComposer: Unified Video Compositing from Images to Dynamic Footage with Flexible Trajectory Control MiniMax-Remover: Taming Bad Noise Helps Video Object Removal

Reference 99

Resolution
unresolved
no resolver link, observed 2026-08-03T03:18:01.427798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:18:01.427798Z digest=sha256:7889065ca878913f96468d2dfcfb9591196d488b82f9bc38e527399530b13f47