Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation | Paper Citation Record

Observation abf23093-d4ad-4e32-b2da-982c4241e377 · outbound

This paper cites SemDeDup: Data-efficient learning at web-scale through semantic deduplication.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation SemDeDup: Data-efficient learning at web-scale through semantic deduplication

Reference 1

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Observation d64476b5-49d1-42ef-9c3f-9cfe5d576912 · outbound

This paper cites Cosmos World Foundation Model Platform for Physical AI.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Cosmos World Foundation Model Platform for Physical AI

Reference 2

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Observation 5ddcda5b-52a2-4b74-8e88-2511b99e865b · outbound

This paper cites A Survey on Data Selection for Language Models.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation A Survey on Data Selection for Language Models

Reference 3

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This paper cites Qwen2.5-VL Technical Report.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Qwen2.5-VL Technical Report

Reference 4

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This paper cites Impossible Videos.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Impossible Videos

Reference 5

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This paper cites VideoPhy: Evaluating Physical Commonsense for Video Generation.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation VideoPhy: Evaluating Physical Commonsense for Video Generation

Reference 6

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This paper cites Color-filter: Conditional loss reduction filtering for targeted language model pre- training.Advances in Neural Information Processing Systems, 37:97618–97649, 2024.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Color-filter: Conditional loss reduction filtering for targeted language model pre- training.Advances in Neural Information Processing Systems, 37:97618–97649, 2024

Reference 7

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Observation 008d113b-95d1-4954-891b-a06c1ddb3524 · outbound

This paper cites Video generation models as world simulators.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Video generation models as world simulators

Reference 8

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Observation 1c1915f3-c09b-4849-b363-339011c6d4c7 · outbound

This paper cites DSPO: Direct Semantic Preference Optimization for Real-World Image Super-Resolution.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation DSPO: Direct Semantic Preference Optimization for Real-World Image Super-Resolution

Reference 9

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Observation 360f1a25-5f17-431b-bfa1-3e0ac64e5df7 · outbound

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

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation SkyReels-V2: Infinite-length Film Generative Model

Reference 10

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Observation a7cab711-dbdb-42d1-b728-89ee17489c6d · outbound

This paper cites Beyond Generation: Unlocking Universal Editing via Self-Supervised Fine-Tuning.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Beyond Generation: Unlocking Universal Editing via Self-Supervised Fine-Tuning

Reference 12

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Observation eb9cf167-802a-404d-8273-687f51135387 · outbound

This paper cites Temporal Regularization Makes Your Video Generator Stronger.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Temporal Regularization Makes Your Video Generator Stronger

Reference 13

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Observation 2702ef9f-e525-4f6d-a4a5-6c44f15edbf0 · outbound

This paper cites AlpaGasus: Training A Better Alpaca with Fewer Data.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation AlpaGasus: Training A Better Alpaca with Fewer Data

Reference 14

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Observation da65e6d6-5bcd-40e6-9e80-76ea5c5d9830 · outbound

This paper cites Goku: Flow Based Video Generative Foundation Models.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Goku: Flow Based Video Generative Foundation Models

Reference 15

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Observation fc531090-7222-4546-8570-8544b1a865ac · outbound

This paper cites Discriminator-Free Direct Preference Optimization for Video Diffusion.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Discriminator-Free Direct Preference Optimization for Video Diffusion

Reference 16

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Observation e660235b-2a14-4d3d-b5fb-254abd944c28 · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality.See https://vicuna.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality.See https://vicuna

Reference 17

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Observation 4feab0fe-0d78-4c9b-8026-51ffc2d90a3b · outbound

This paper cites UltraFeedback: Boosting Language Models with Scaled AI Feedback.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation UltraFeedback: Boosting Language Models with Scaled AI Feedback

Reference 18

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Observation 35289050-813a-4314-9f89-d981b3262802 · outbound

This paper cites One-Minute Video Generation with Test-Time Training.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation One-Minute Video Generation with Test-Time Training

Reference 19

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Observation aceb8c06-4215-4d64-92c6-4254da7e712b · outbound

This paper cites Enhancing Chat Language Models by Scaling High-quality Instructional Conversations.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Enhancing Chat Language Models by Scaling High-quality Instructional Conversations

Reference 20

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Observation 7ff24b6c-da73-41cd-aa42-6b7c0ba0c349 · outbound

This paper cites What's In My Big Data?.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation What's In My Big Data?

Reference 21

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Observation 4f34db5d-18fe-44c1-83d7-8721d6c9753c · outbound

This paper cites Wave: Warping ddim inversion features for zero-shot text-to-video editing.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Wave: Warping ddim inversion features for zero-shot text-to-video editing

Reference 22

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Observation 8e721712-d8a3-424e-ba03-a7f8b3724e2c · outbound

This paper cites CHip: Cross-modal hierarchical direct preference optimization for multimodal LLMs.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation CHip: Cross-modal hierarchical direct preference optimization for multimodal LLMs

Reference 23

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Observation d83a193b-9e33-4b12-a773-3bf547b306cb · outbound

This paper cites Clustering and Ranking: Diversity-preserved Instruction Selection through Expert-aligned Quality Estimation.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Clustering and Ranking: Diversity-preserved Instruction Selection through Expert-aligned Quality Estimation

Reference 24

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Observation 0713bf26-92b0-47a8-97f6-9f0379df09f7 · outbound

This paper cites Task-adaptive pretrained lan- guage models via clustered-importance sampling.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Task-adaptive pretrained lan- guage models via clustered-importance sampling

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Observation bd0002af-fcb6-4af4-85e7-8b2896b7531d · outbound

This paper cites A Survey on LLM-as-a-Judge.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation A Survey on LLM-as-a-Judge

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Observation da01cf88-ec14-453b-aa55-1de806c1a4b1 · outbound

This paper cites Detecting and preventing hallucinations in large vision language models.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Detecting and preventing hallucinations in large vision language models

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Observation 1cc8a74b-56f0-4691-af30-bc092bd97b36 · outbound

This paper cites Long Context Tuning for Video Generation.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Long Context Tuning for Video Generation

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Observation 520bed0c-b3f4-4081-93d4-56cc2b83e60a · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

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Observation 466cf268-80ba-4380-b297-27deda305d82 · outbound

This paper cites Animate anyone: Consistent and controllable image-to-video synthesis for character animation.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Animate anyone: Consistent and controllable image-to-video synthesis for character animation

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Observation da0bf6ba-2227-4950-a54e-0e4d03af8456 · outbound

This paper cites VistaDPO: Video Hierarchical Spatial-Temporal Direct Preference Optimization for Large Video Models.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation VistaDPO: Video Hierarchical Spatial-Temporal Direct Preference Optimization for Large Video Models

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Observation 1187b530-f1d1-4485-9edf-5c0cc2d7d5ac · outbound

This paper cites A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.ACM Transactions on Information Systems, 43(2):1–55, 2025.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.ACM Transactions on Information Systems, 43(2):1–55, 2025

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Observation 01466845-10fd-4bbc-add5-daa1763e6c93 · outbound

This paper cites ConceptMaster: Multi-Concept Video Customization on Diffusion Transformer Models Without Test-Time Tuning.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation ConceptMaster: Multi-Concept Video Customization on Diffusion Transformer Models Without Test-Time Tuning

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

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation VBench: Comprehensive benchmark suite for video generative models

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Observation ac2b474c-0bc4-4d32-95cf-174ee9080b64 · outbound

This paper cites Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2

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Observation 7cb2e6fd-bab4-49c8-9373-17dc1e3b5506 · outbound

This paper cites HuViDPO:Enhancing Video Generation through Direct Preference Optimization for Human-Centric Alignment.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation HuViDPO:Enhancing Video Generation through Direct Preference Optimization for Human-Centric Alignment

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Observation af17686a-932f-4e0e-9f69-247ef1f6758b · outbound

This paper cites Miradata: A large-scale video dataset with long durations and structured captions.Advances in Neural Information Processing Systems, 37:48955–48970, 2024.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Miradata: A large-scale video dataset with long durations and structured captions.Advances in Neural Information Processing Systems, 37:48955–48970, 2024

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Observation d4405d33-50e3-4729-bde0-a99f6cd52645 · outbound

This paper cites How Far is Video Generation from World Model: A Physical Law Perspective.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation How Far is Video Generation from World Model: A Physical Law Perspective

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Observation 5b0cdf9a-c003-4143-94df-a6798363e951 · outbound

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

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation HunyuanVideo: A Systematic Framework For Large Video Generative Models

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Observation f8879f6b-f98e-403d-ae76-26c11288dd3d · outbound

This paper cites Differentiable physics simulation of dynamics- augmented neural objects.IEEE Robotics and Automation Letters, 8(5):2780–2787, 2023.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Differentiable physics simulation of dynamics- augmented neural objects.IEEE Robotics and Automation Letters, 8(5):2780–2787, 2023

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Observation 3d95949e-f262-4622-9a1a-f1a603c5a664 · outbound

This paper cites PISA Experiments: Exploring Physics Post-Training for Video Diffusion Models by Watching Stuff Drop.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation PISA Experiments: Exploring Physics Post-Training for Video Diffusion Models by Watching Stuff Drop

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Observation 944ebd82-9e66-4707-8ce6-2fd22fdaa43f · outbound

This paper cites WorldModelBench: Judging Video Generation Models As World Models.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation WorldModelBench: Judging Video Generation Models As World Models

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Observation 10d5fa82-edcb-4837-8e3c-9b681172311d · outbound

This paper cites MagicID: Hybrid Preference Optimization for ID-Consistent and Dynamic-Preserved Video Customization.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation MagicID: Hybrid Preference Optimization for ID-Consistent and Dynamic-Preserved Video Customization

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Observation 190e7bf0-694b-4ae6-8619-5dd8486a2610 · outbound

This paper cites Science-t2i: Addressing scientific illusions in image synthesis.arXiv preprint arXiv:2504.13129, 2025.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Science-t2i: Addressing scientific illusions in image synthesis.arXiv preprint arXiv:2504.13129, 2025

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Observation 20b8d4f3-aa50-4441-930d-1de62a6c5da9 · outbound

This paper cites From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning

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Observation 60fd8e12-1717-477e-adc8-a456d0c4366a · outbound

This paper cites Selective reflection-tuning: Student-selected data recycling for llm instruction-tuning.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Selective reflection-tuning: Student-selected data recycling for llm instruction-tuning

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Observation e025c603-835d-4347-b7e3-f1551c58d54e · outbound

This paper cites Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning

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Observation 51874436-f855-475c-bd13-030ec8abd31e · outbound

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Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Open-Sora Plan: Open-Source Large Video Generation Model

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Observation 184ef0c6-6137-4bfb-8bab-8d669f992ca6 · outbound

This paper cites Yu, and Meng Cao.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Yu, and Meng Cao

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Observation 5cabad66-aa5d-4a44-982d-aa5b481def45 · outbound

This paper cites AlignGuard: Scalable Safety Alignment for Text-to-Image Generation.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation AlignGuard: Scalable Safety Alignment for Text-to-Image Generation

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Observation ec73463d-1051-4d07-a729-7fcf599b405e · outbound

This paper cites VideoDPO: Omni-Preference Alignment for Video Diffusion Generation.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation VideoDPO: Omni-Preference Alignment for Video Diffusion Generation

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Observation 28a6f193-cd6e-484d-be30-095404c0cbd3 · outbound

This paper cites Physgen: Rigid-body physics-grounded image-to-video generation.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Physgen: Rigid-body physics-grounded image-to-video generation

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Observation 4ccbe447-d961-45bb-9576-ae086fb134eb · outbound

This paper cites What makes good data for alignment? a comprehensive study of automatic data selection in instruction tuning.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation What makes good data for alignment? a comprehensive study of automatic data selection in instruction tuning

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Observation 688f7ec0-68dc-4c27-9285-6256e8b5d541 · outbound

This paper cites Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation

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Observation 120fdf91-fe6c-4f69-92f8-3312b3d1ed70 · outbound

This paper cites Motioncraft: Physics-based zero-shot video generation.Advances in Neural Information Processing Systems, 37:123155–123181, 2024.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Motioncraft: Physics-based zero-shot video generation.Advances in Neural Information Processing Systems, 37:123155–123181, 2024

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Observation 021a286a-9255-4536-9f95-7a9c32ceb515 · outbound

This paper cites Do generative video models understand physical principles?.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Do generative video models understand physical principles?

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:23.148950Z

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Observation fd7ec827-d3d9-4081-998c-6d329554d3b2 · outbound

This paper cites OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:23.216728Z

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Observation e57bbf06-a529-4a4c-9de1-ba4d8a329310 · outbound

This paper cites Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:23.295361Z

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Observation b037cf95-413f-4476-b9e1-49f4121dbd6e · outbound

This paper cites G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine Translation.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine Translation

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:23.343005Z

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Observation 34663629-1456-48f5-baac-7c804ec7bd97 · outbound

This paper cites FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:23.423843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 049af62a-a3b5-44cd-b1ac-10c70d1491c7 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Direct preference optimization: Your language model is secretly a reward model

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:23.500580Z

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Observation 1a8c6334-89a6-4460-b5ee-524cb29461cb · outbound

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

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation High-resolution image synthesis with latent diffusion models

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:23.588669Z

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Observation 1bac3b26-74f5-4098-9ea2-7d330c95100f · outbound

This paper cites Towards nsfw-free text-to-image generation via safety-constraint direct preference optimization.arXiv preprint arXiv:2504.14290, 2025.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Towards nsfw-free text-to-image generation via safety-constraint direct preference optimization.arXiv preprint arXiv:2504.14290, 2025

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:23.668075Z

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Observation 0c85decf-415d-402c-9e4e-9a7b071d41b3 · outbound

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

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Seaweed-7B: Cost-Effective Training of Video Generation Foundation Model

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:23.748468Z

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Observation 31de2f42-3116-4dd9-81f5-263f29278912 · outbound

This paper cites Finephys: Fine-grained human action generation by explicitly incorporating physical laws for effective skeletal guidance.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Finephys: Fine-grained human action generation by explicitly incorporating physical laws for effective skeletal guidance

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:23.829668Z

Source-reported events for the cited work

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Observation e4444878-f4b5-45de-99f1-2c73b4be6d5f · outbound

This paper cites Deep unsuper- vised learning using nonequilibrium thermodynamics.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Deep unsuper- vised learning using nonequilibrium thermodynamics

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:23.920281Z

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Observation e69ad3f7-4fab-4175-be85-2fd3819ccb08 · outbound

This paper cites Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language Models.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language Models

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:23.997025Z

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Observation c1d7dc81-6468-40fd-b414-f63276c780f6 · outbound

This paper cites Dsv: Exploiting dynamic sparsity to accelerate large-scale video dit training.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Dsv: Exploiting dynamic sparsity to accelerate large-scale video dit training

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.059788Z

Source-reported events for the cited work

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Observation eadfa2d2-3b99-4fe2-8e5e-e2766a7e3c46 · outbound

This paper cites Stanford alpaca: An instruction-following llama model, 2023.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Stanford alpaca: An instruction-following llama model, 2023

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.101688Z

Source-reported events for the cited work

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Observation e4b19ad2-7a43-4db2-bf6a-0b18eca2f7d3 · outbound

This paper cites D4: Improving llm pretraining via document de-duplication and diversification.Advances in Neural Information Processing Systems, 36:53983–53995, 2023.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation D4: Improving llm pretraining via document de-duplication and diversification.Advances in Neural Information Processing Systems, 36:53983–53995, 2023

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.150267Z

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Observation 06bb5adf-bd40-4529-a9d8-6da2d549d10c · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation LLaMA: Open and Efficient Foundation Language Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.231554Z

Source-reported events for the cited work

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Observation 96f28482-adbe-4037-9204-bd6d6014fa57 · outbound

This paper cites Diffusion model alignment using direct preference optimization.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Diffusion model alignment using direct preference optimization

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.309441Z

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Observation 21f3ecdf-36b9-4a04-8ada-782f40b42ad6 · outbound

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

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Wan: Open and Advanced Large-Scale Video Generative Models

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.402498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3afcc84e-8dac-4d38-8c70-2f79f03afed4 · outbound

This paper cites A Survey on Data Selection for LLM Instruction Tuning.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation A Survey on Data Selection for LLM Instruction Tuning

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.467176Z

Source-reported events for the cited work

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Observation e669cf76-5d02-4bbf-8ced-da7d2095d66a · outbound

This paper cites WISA: World Simulator Assistant for Physics-Aware Text-to-Video Generation.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation WISA: World Simulator Assistant for Physics-Aware Text-to-Video Generation

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.540226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b12fb950-5c87-4313-9cd8-23b23ac671e4 · outbound

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

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.611355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 826f0fe6-f4d1-4d59-a6e0-4a08ab5d21cc · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.687999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e70f2bde-befd-405e-bbf3-446cfb302307 · outbound

This paper cites LightGen: Efficient Image Generation through Knowledge Distillation and Direct Preference Optimization.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation LightGen: Efficient Image Generation through Knowledge Distillation and Direct Preference Optimization

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.799234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c78059b2-1a8e-49e2-bd41-b770a054e651 · outbound

This paper cites DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.847410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a34d58a-0ece-43ed-9178-65bb60bf9c10 · outbound

This paper cites LESS: Selecting influential data for targeted instruction tuning.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation LESS: Selecting influential data for targeted instruction tuning

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.914535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a85a87b-7bc1-481e-bf84-dbd83be02403 · outbound

This paper cites Data selection for language models via importance resampling.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Data selection for language models via importance resampling

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:24.992293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdb13d32-32e5-4015-a4f6-c9caac4a8a50 · outbound

This paper cites Tooncrafter: Generative cartoon interpolation.ACM Transactions on Graphics (TOG), 43(6):1–11, 2024.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Tooncrafter: Generative cartoon interpolation.ACM Transactions on Graphics (TOG), 43(6):1–11, 2024

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:25.095140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dba73fdd-ef53-42f0-8661-d71483d37478 · outbound

This paper cites Make-your-video: Customized video generation using textual and structural guidance.IEEE Transactions on Visualization and Computer Graphics, 2024.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Make-your-video: Customized video generation using textual and structural guidance.IEEE Transactions on Visualization and Computer Graphics, 2024

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:25.175943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2036bb0c-4685-44a2-99ea-81124d3e73ed · outbound

This paper cites WizardLM: Empowering large pre-trained language models to follow complex instructions.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation WizardLM: Empowering large pre-trained language models to follow complex instructions

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:25.284690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a83502f-e937-4cab-a414-ecd4269b0cc9 · outbound

This paper cites PhyT2V: LLM-Guided Iterative Self-Refinement for Physics-Grounded Text-to-Video Generation.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation PhyT2V: LLM-Guided Iterative Self-Refinement for Physics-Grounded Text-to-Video Generation

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:25.354451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af672e98-b20a-439a-9727-76067662cddf · outbound

This paper cites Qwen2.5 Technical Report.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Qwen2.5 Technical Report

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:25.470971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ef4f03a-0d38-4567-9a85-67f46d7ba348 · outbound

This paper cites Rethinking Video Tokenization: A Conditioned Diffusion-based Approach.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Rethinking Video Tokenization: A Conditioned Diffusion-based Approach

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:25.564162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5fdc7aa-1dad-42e8-a46c-79c7710ad291 · outbound

This paper cites Vlipp: Towards physically plausible video generation with vision and language informed physical prior.arXiv e-prints, pages arXiv–2503, 2025.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Vlipp: Towards physically plausible video generation with vision and language informed physical prior.arXiv e-prints, pages arXiv–2503, 2025

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:25.714266Z

Source-reported events for the cited work

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Observation b85b6055-590e-4ced-b5e4-cc56a6859ffe · outbound

This paper cites Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:25.803393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8713a1c7-87a2-4aa4-bec3-3cd307951862 · outbound

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

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:25.911307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea2ee177-e28c-4e6d-b998-70b6069ce1ba · outbound

This paper cites LIMO: Less is More for Reasoning.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation LIMO: Less is More for Reasoning

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:26.006631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b04a895-03f7-4390-9ecf-6177df70d104 · outbound

This paper cites Gamefactory: Creating new games with generative interactive videos.arXiv preprint arXiv:2501.08325, 2025.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Gamefactory: Creating new games with generative interactive videos.arXiv preprint arXiv:2501.08325, 2025

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:26.093846Z

Source-reported events for the cited work

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Observation d18c32c4-22ef-46ad-8e59-2a049e054efb · outbound

This paper cites Magictime: Time-lapse video generation models as metamorphic simulators.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Magictime: Time-lapse video generation models as metamorphic simulators.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:26.097826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b9afc6a-a732-4704-82eb-3a5818f75d5b · outbound

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

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Onlinevpo: Align video diffusion model with online video-centric preference optimization

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:26.147343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86953cee-2773-4711-881e-ae620e58f9d3 · outbound

This paper cites TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:26.205369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aff15324-4a8c-40bf-8369-e0a35695ded8 · outbound

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

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Packing input frame contexts in next-frame prediction models for video generation.arXiv preprint arXiv:2504.12626, 2025

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:26.289918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3b29894-f158-4794-91e6-1b2dccbd8d98 · outbound

This paper cites Fast Video Generation with Sliding Tile Attention.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Fast Video Generation with Sliding Tile Attention

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:26.373467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef7937bb-5a5c-4068-bd49-b5477674f288 · outbound

This paper cites Synthetic Video Enhances Physical Fidelity in Video Synthesis.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Synthetic Video Enhances Physical Fidelity in Video Synthesis

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:26.433306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 433b6377-20a2-40c0-80b2-edc6fe17c8fa · outbound

This paper cites Open-Sora: Democratizing Efficient Video Production for All.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Open-Sora: Democratizing Efficient Video Production for All

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:26.570925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a65f0930-7e38-428e-b35d-f8d1096be413 · outbound

This paper cites Deco: Decoupled human-centered diffusion video editing with motion consistency.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Deco: Decoupled human-centered diffusion video editing with motion consistency

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:26.671291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f43e9135-d0e3-4c05-87df-99559ab50658 · outbound

This paper cites Lima: Less is more for alignment.Advances in Neural Information Processing Systems, 36:55006–55021, 2023.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation Lima: Less is more for alignment.Advances in Neural Information Processing Systems, 36:55006–55021, 2023

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:26.816265Z

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