Paper Citation Record · LEDGER

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers

As of 11 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 8 inbound Pith citation observations for arXiv:2505.22167.

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

pith.paper-citation-record.v1
2505.22167 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

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measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:57:21.407355Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T09:45:40.325116Z

Reference resolution

52 of 52 outbound references displayed

verified exact1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 42d44208-69e9-4fcc-9441-8c13ebb60427 · outbound

This paper cites QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs

Reference 1

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Observation 40c4f2ad-234e-4d18-8350-a871dd7ea002 · outbound

This paper cites Flux.1, 2024.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Flux.1, 2024

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:24.533266Z

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Observation 225abec8-677d-4cbd-9e17-2370230b5db9 · outbound

This paper cites W., Fidler, S., and Kreis, K.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers W., Fidler, S., and Kreis, K

Reference 3

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Observation 90373be9-13dd-4fbe-aeaf-99e779030ca8 · outbound

This paper cites Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers

Reference 4

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Observation 99e10386-786a-42a3-bc20-fa9ac6979d47 · outbound

This paper cites T., Mittal, S., Emani, M., Vishwanath, V., and Somani, A.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers T., Mittal, S., Emani, M., Vishwanath, V., and Somani, A

Reference 5

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Observation 8b92dc1c-2ac6-4c30-98ef-1d7928aa49b8 · outbound

This paper cites and Nichol, A.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers and Nichol, A

Reference 6

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Observation 73e66e29-b3e5-4e4a-8028-ce67f7e2491f · outbound

This paper cites Reg-ptq: Regression-specialized post-training quantization for fully quantized object detector.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Reg-ptq: Regression-specialized post-training quantization for fully quantized object detector

Reference 7

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Observation 9efc581a-8040-4922-967a-61e21c4e9258 · outbound

This paper cites Perceptual quality assessment of smartphone photography.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Perceptual quality assessment of smartphone photography

Reference 8

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Observation f7efd17d-7b02-4aca-85f0-c890982605ed · outbound

This paper cites Relational diffusion distillation for efficient image generation.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Relational diffusion distillation for efficient image generation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:23.769463Z

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Observation 90bfd641-b19e-4967-94b9-43bd724397d4 · outbound

This paper cites Mpq-dm: Mixed precision quantization for extremely low bit diffusion models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Mpq-dm: Mixed precision quantization for extremely low bit diffusion models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:23.620119Z

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Observation d3258729-ce03-4162-9886-8b38b4d43b53 · outbound

This paper cites W., and Keutzer, K.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers W., and Keutzer, K

Reference 11

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Observation 6d9e08ff-bd26-4e8e-ab81-cfdec2384fd8 · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Delving deep into rectifiers: Surpassing human-level performance on imagenet classification

Reference 12

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Observation 52e4babf-c224-4b40-9737-37d8f88dc76d · outbound

This paper cites EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models

Reference 13

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Observation eae52490-2fda-4090-9e12-7bfd982d02ef · outbound

This paper cites Ptqd: Accurate post-training quantization for diffusion models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Ptqd: Accurate post-training quantization for diffusion models

Reference 14

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Observation b3a443b6-5165-4796-855c-53475dda801e · outbound

This paper cites Denoising diffusion probabilistic models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Denoising diffusion probabilistic models

Reference 15

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Observation 323a40c9-3090-4006-b106-74b51a9da9b4 · outbound

This paper cites Open-sora, 2024.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Open-sora, 2024

Reference 16

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Observation 2d97c5c7-ea68-43b1-be7e-0f6ed0eed961 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers LoRA: Low-Rank Adaptation of Large Language Models

Reference 17

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Observation 6d543b78-e708-4246-8000-54d87bda162f · outbound

This paper cites Tfmq-dm: Temporal feature maintenance quantization for diffusion models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Tfmq-dm: Temporal feature maintenance quantization for diffusion models

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:22.952337Z

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Observation aab944f5-3a73-49af-b2da-dd4fbd82466a · outbound

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

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Vbench: Comprehensive benchmark suite for video generative models

Reference 19

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Observation a1a72d73-8869-4817-90fd-b8f191d0d3f1 · outbound

This paper cites Musiq: Multi-scale image quality transformer.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Musiq: Multi-scale image quality transformer

Reference 20

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Observation 7bd28cb6-65a6-43ee-8f50-7c8d2285d6c6 · outbound

This paper cites Aesthetic-predictor, 2022.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Aesthetic-predictor, 2022

Reference 21

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Observation 92e45033-8877-45b2-ad9a-d33be3e662cc · outbound

This paper cites Svdqunat: Absorbing outliers by low-rank components for 4-bit diffusion models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Svdqunat: Absorbing outliers by low-rank components for 4-bit diffusion models

Reference 22

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Observation 408c8b91-7402-41b8-bae1-7f2d1ac272ae · outbound

This paper cites Q-diffusion: Quantizing diffusion models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Q-diffusion: Quantizing diffusion models

Reference 23

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Observation a05a1368-8788-4dd2-b4a5-4ae7cbfc5ad1 · outbound

This paper cites Q-dm: An efficient low-bit quantized diffusion model.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Q-dm: An efficient low-bit quantized diffusion model

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:22.065546Z

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Observation 72106f91-22a9-43b2-8c18-76f86e94a4b2 · outbound

This paper cites Diffbir: Toward blind image restoration with generative diffusion prior.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Diffbir: Toward blind image restoration with generative diffusion prior

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:21.826663Z

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Observation d0f5f311-aa17-428b-b22d-c72ae042fd5d · outbound

This paper cites Evalcrafter: Benchmarking and evaluating large video generation models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Evalcrafter: Benchmarking and evaluating large video generation models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:21.555393Z

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Observation 37d4edee-b4ad-4b64-9c50-f5b904eff26e · outbound

This paper cites Reactnet: Towards precise binary neural network with generalized activation functions.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Reactnet: Towards precise binary neural network with generalized activation functions

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:21.299496Z

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Observation 15fca04d-d514-431a-b9d1-c6a51528e5d3 · outbound

This paper cites TerDiT: Ternary Diffusion Models with Transformers.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers TerDiT: Ternary Diffusion Models with Transformers

Reference 28

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Observation cbdb5888-dff9-421e-be28-64ef064057a5 · outbound

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

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Latte: Latent Diffusion Transformer for Video Generation

Reference 29

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Observation 4c4a7afb-cf45-486d-b404-0b2e52be06df · outbound

This paper cites and Xie, S.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers and Xie, S

Reference 30

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Observation d142ae07-177d-4d20-be8e-4e839ce5207a · outbound

This paper cites Compression of convolutional neural networks: A short survey.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Compression of convolutional neural networks: A short survey

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:21.007247Z

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Observation ad7da9c4-8d16-4dfc-b56b-cbed9b599890 · outbound

This paper cites Forward and backward information retention for accurate binary neural networks.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Forward and backward information retention for accurate binary neural networks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:20.831361Z

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Observation 20986bf5-0d0c-4d9a-acb2-97619d7785a8 · outbound

This paper cites W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 33

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

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers High-resolution image synthesis with latent diffusion models

Reference 34

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Observation 9dfc85ce-922a-48ab-aaa9-327edbf0e9ef · outbound

This paper cites Post-training quantization on diffusion models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Post-training quantization on diffusion models

Reference 35

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Observation f2e6ac20-41a5-46cd-87d4-a3c0bb051fe5 · outbound

This paper cites Denoising Diffusion Implicit Models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Denoising Diffusion Implicit Models

Reference 36

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Observation 0dc5d63a-890d-4b28-815d-add6d080260c · outbound

This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 37

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Observation dbfd2305-85e4-402a-8188-a3b9bcdc8462 · outbound

This paper cites and Deng, J.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers and Deng, J

Reference 38

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Observation 3f693415-93eb-4e22-8899-e416ba6e79aa · outbound

This paper cites QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning

Reference 39

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Observation 5f5434b8-0cf7-4697-ba23-6297227cb4bd · outbound

This paper cites C., and Loy, C.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers C., and Loy, C

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:20.556048Z

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Observation 7d3d1fc9-29a7-43ef-ba22-2208dff8b6e8 · outbound

This paper cites InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation

Reference 41

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Observation 4e226ceb-9057-44eb-9210-88343ad97e01 · outbound

This paper cites Exploring video quality assessment on user generated contents from aesthetic and technical perspectives.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Exploring video quality assessment on user generated contents from aesthetic and technical perspectives

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:20.374069Z

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Observation 67ca7b77-e310-4a14-a0ef-dda0cd4b0cf3 · outbound

This paper cites PTQ4DiT: Post-training Quantization for Diffusion Transformers.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers PTQ4DiT: Post-training Quantization for Diffusion Transformers

Reference 43

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Observation 9be99d43-2628-4b21-87e9-ee4b8becf7bf · outbound

This paper cites Seesr: Towards semantics-aware real-world image super-resolution.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Seesr: Towards semantics-aware real-world image super-resolution

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:20.257269Z

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Observation 319346f7-cb07-4548-961e-a5ac96d4e5cc · outbound

This paper cites Smoothquant: Accurate and efficient post-training quantization for large language models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Smoothquant: Accurate and efficient post-training quantization for large language models

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:20.070306Z

Source-reported events for the cited work

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Observation e4478665-50af-4895-a7bc-93f0e3507d7b · outbound

This paper cites Cross-image relational knowledge distillation for semantic segmentation.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Cross-image relational knowledge distillation for semantic segmentation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:19.915750Z

Source-reported events for the cited work

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Observation 8647242a-2de7-427f-9024-6d18698c105e · outbound

This paper cites Multi-party Collaborative Attention Control for Image Customization.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Multi-party Collaborative Attention Control for Image Customization

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:22:19.445271Z

Source-reported events for the cited work

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Observation 2d4d10d1-c9d0-4362-90da-73bc24428fa1 · outbound

This paper cites ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation

Reference 48

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Source-reported events for the cited work

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Observation fc47f83c-143d-43d3-941e-21785bf0e418 · outbound

This paper cites Mixdq: Memory-efficient few-step text-to-image diffusion models with metric-decoupled mixed precision quantization.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers Mixdq: Memory-efficient few-step text-to-image diffusion models with metric-decoupled mixed precision quantization

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:22:19.779782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 001445c0-a054-4550-9768-f08cd23d8106 · outbound

This paper cites BiDM: Pushing the Limit of Quantization for Diffusion Models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers BiDM: Pushing the Limit of Quantization for Diffusion Models

Reference 50

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This paper cites BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models

Reference 51

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This paper cites write newline.

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers write newline

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T13:22:19.245131Z

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Pith citing papers

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MPQ-DMv2: Flexible Residual Mixed Precision Quantization for Low-Bit Diffusion Models with Temporal Distillation cites this paper.

MPQ-DMv2: Flexible Residual Mixed Precision Quantization for Low-Bit Diffusion Models with Temporal Distillation Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers

Reference 45

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Charting the Future of Scholarly Knowledge with AI: A Community Perspective cites this paper.

Charting the Future of Scholarly Knowledge with AI: A Community Perspective Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers

Reference 45

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

Efficient Video Diffusion Models: Advancements and Challenges Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers

Reference 268

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

Motion-Aware Caching for Efficient Autoregressive Video Generation Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:06:01.664270Z

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

Motion-Aware Caching for Efficient Autoregressive Video Generation Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-15T07:19:49.953112Z

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Observation 96c9f718-ccb3-4199-a61b-182df46185dc · inbound

GaitProtector: Impersonation-Driven Gait De-Identification via Training-Free Diffusion Latent Optimization cites this paper.

GaitProtector: Impersonation-Driven Gait De-Identification via Training-Free Diffusion Latent Optimization Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-13T06:42:26.399267Z

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Echo-Forcing: A Scene Memory Framework for Interactive Long Video Generation cites this paper.

Echo-Forcing: A Scene Memory Framework for Interactive Long Video Generation Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-20T20:03:43.577064Z

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Observation d33759d6-44da-41f4-aa79-f6fde75df3c1 · inbound

SyncCache: Exploiting Asymmetric Dynamics for Fast Audio-Driven Portrait Animation cites this paper.

SyncCache: Exploiting Asymmetric Dynamics for Fast Audio-Driven Portrait Animation Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers

Reference 10

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