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Paper Citation Record · LEDGER

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation

As of 18 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2607.16947.

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

pith.paper-citation-record.v1
2607.16947 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T19:33:06.822584Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:36:01.036574Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T00:36:01.306938Z

Reference resolution

52 of 52 outbound references displayed

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Outbound references

Observation a6a3fe1b-436b-4008-8b80-11e41939d3f9 · outbound

This paper cites Videophy: Evaluating physical commonsense for video generation.ICLR, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Videophy: Evaluating physical commonsense for video generation.ICLR, 2025

Reference 1

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source=pdf_text observed=2026-08-01T19:33:03.470997Z digest=sha256:1281e3cf7fea0fffcfb5bfeda435c2a565631762dc0f64899b5a56bf918776a9

Observation 087d6028-ce69-4bf7-bf1d-e1f662b0f4e2 · outbound

This paper cites VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation

Reference 2

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source=pdf_text observed=2026-08-01T19:33:03.502183Z digest=sha256:99d1f34e2bfbf821796ba16f9df1176cd4adefcf969d1a6f05d74470a4728b42

Observation 71184ea0-57c8-477a-a13c-bcbfe7ab3962 · outbound

This paper cites A Note on the Inception Score.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation A Note on the Inception Score

Reference 3

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source=pdf_text observed=2026-08-01T19:33:03.605167Z digest=sha256:c754503a9d1517e8afee742dac0ff2ec9a6f0ce79443b875f6f9047a71cf7461

Observation edd02ddc-c2b2-4663-87b4-25e00586eeb6 · outbound

This paper cites Curricu- lum learning.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Curricu- lum learning

Reference 4

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source=pdf_text observed=2026-08-01T19:33:03.667148Z digest=sha256:212036cf06e84c8cd56d66296cacbb14cfda138d14c8ba8660042808f4d7b422

Observation 8a238d4f-ba5d-4100-83cf-6539782b6a8f · outbound

This paper cites Hierarchical fine-grained preference optimization for physically plausible video generation.NeurIPS, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Hierarchical fine-grained preference optimization for physically plausible video generation.NeurIPS, 2025

Reference 5

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source=pdf_text observed=2026-08-01T19:33:03.719052Z digest=sha256:3c3ecb097519c4e18ff39dddc8cbd3f922ee9ee842c4a397febb13e45bc1c643

Observation 7fda2ce6-4840-46ff-80ad-b5fa2a3d8a07 · outbound

This paper cites Deep reinforcement learning from human preferences.NeurIPS, 2017.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Deep reinforcement learning from human preferences.NeurIPS, 2017

Reference 6

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source=pdf_text observed=2026-08-01T19:33:03.781879Z digest=sha256:0e63ac9ac3d6544a32ee71669440807109950bceace5de556c9bb6abce1907d7

Observation 887b8781-bf4b-4b97-82d6-9b45a1f262db · outbound

This paper cites Understanding world or predicting future? a comprehensive survey of world models.ACM Computing Surveys, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Understanding world or predicting future? a comprehensive survey of world models.ACM Computing Surveys, 2025

Reference 7

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source=pdf_text observed=2026-08-01T19:33:03.837295Z digest=sha256:f1986978b56510c913b2e9650d7381ac30bf7e09dbc9c4d35157d4772799e2b1

Observation 9871ad53-b8de-4fc1-8411-92e610c07b23 · outbound

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

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation LTX-Video: Realtime Video Latent Diffusion

Reference 8

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source=pdf_text observed=2026-08-01T19:33:03.905908Z digest=sha256:763ac0d7f248b67e0170e7855632d068137cb536326144baea73c37c20f15f36

Observation 95015b73-23a5-49aa-9da1-bc1296c846df · outbound

This paper cites Co-teaching: Robust training of deep neural networks with extremely noisy labels.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Co-teaching: Robust training of deep neural networks with extremely noisy labels

Reference 9

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source=pdf_text observed=2026-08-01T19:33:03.952423Z digest=sha256:677a9968567d86449231fcabac903d4128fdadc025e1e46ef572dabbe83b4689

Observation d567dd91-b786-48dc-b649-aa0fb1935cd4 · outbound

This paper cites Enhancing Physical Plausibility in Video Generation by Reasoning the Implausibility.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Enhancing Physical Plausibility in Video Generation by Reasoning the Implausibility

Reference 10

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source=pdf_text observed=2026-08-01T19:33:04.023158Z digest=sha256:5a381f36b9192227a560b94c09bac40e59b747f75394b96e49fcbaf25ecda63e

Observation 8158d4b9-be0e-4c0e-aef9-63ccc13b59e9 · outbound

This paper cites Clipscore: A reference-free evaluation metric for image captioning.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Clipscore: A reference-free evaluation metric for image captioning

Reference 11

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source=pdf_text observed=2026-08-01T19:33:04.076136Z digest=sha256:25402d639c3276c51a21660b833af06ddad066594e1d39fed7644f6b11886e77

Observation 6e05dc66-9fa9-4401-a48c-0b677fecd963 · outbound

This paper cites Lora: Low-rank adaptation of large language models.ICLR, 2022.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Lora: Low-rank adaptation of large language models.ICLR, 2022

Reference 12

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source=pdf_text observed=2026-08-01T19:33:04.150711Z digest=sha256:b0f42222b80ab49536ed6a6f886238fb6844e370ca4f68ed22167f0ee0a5897a

Observation 0f900c9b-332d-43c3-8b0d-3508cb32beae · outbound

This paper cites Vistadpo: Video hierarchical spatial-temporal direct preference optimization for large video models.ICML, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Vistadpo: Video hierarchical spatial-temporal direct preference optimization for large video models.ICML, 2025

Reference 13

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source=pdf_text observed=2026-08-01T19:33:04.203949Z digest=sha256:345890cb3f113cc4724e8e2db569e1bccad098ac0d2c1f03017c6ae2d491021f

Observation a5320cdd-73f7-4f7d-aebd-51616e968083 · outbound

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

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Vbench: Comprehensive benchmark suite for video generative models

Reference 14

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source=pdf_text observed=2026-08-01T19:33:04.254901Z digest=sha256:6e7fce76868cc261d530c512e250748441eb158ddbb6de18e4c56a51386882a9

Observation 2b247ab9-0498-4b4d-a3a3-7a0971cdf8df · outbound

This paper cites Physmas- ter: Mastering physical representation for video generation via reinforcement learning.arXiv preprint arXiv:2510.13809, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Physmas- ter: Mastering physical representation for video generation via reinforcement learning.arXiv preprint arXiv:2510.13809, 2025

Reference 15

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source=pdf_text observed=2026-08-01T19:33:04.306812Z digest=sha256:2f1483102d8ca681006607650f413096ccf34521ff60b41b49fbf19639ba123d

Observation a1242d1d-aad2-49d6-bc33-af5269cbdd60 · outbound

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

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation HuViDPO:Enhancing Video Generation through Direct Preference Optimization for Human-Centric Alignment

Reference 16

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source=pdf_text observed=2026-08-01T19:33:04.356173Z digest=sha256:57a9969fa2e4a51a26f1c467a9f08b0fb9df6df19a961f0f5014fb29a04c663a

Observation 3a0372bd-fc77-4664-bfff-66054f3c706c · outbound

This paper cites How far is video generation from world model: A physical law perspective.ICML, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation How far is video generation from world model: A physical law perspective.ICML, 2025

Reference 17

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source=pdf_text observed=2026-08-01T19:33:04.405951Z digest=sha256:77f0ea5dfc8e448cb912f4a90d112d670b82e94c34c937b374e3a7e2358fa1e4

Observation 6773beee-a219-4286-b493-11ed4e38bd8d · outbound

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

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Musiq: Multi-scale image quality transformer

Reference 18

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source=pdf_text observed=2026-08-01T19:33:04.473609Z digest=sha256:ba1c7a604957efb775f2908f2444e3c864869cb24c1789d15b942f70c41775db

Observation ebabb428-24b8-4dd2-9c60-190dd4e7069a · outbound

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

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 19

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source=pdf_text observed=2026-08-01T19:33:04.553310Z digest=sha256:ec84694c19ceb6636aa717b394dbbd8a0c75e614cfb87eec573e761e6cd07295

Observation bf4e3443-4391-4c56-88da-44e702ee31dd · outbound

This paper cites What about gravity in video generation? post-training newton’s laws with verifiable rewards.arXiv preprint arXiv:2512.00425, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation What about gravity in video generation? post-training newton’s laws with verifiable rewards.arXiv preprint arXiv:2512.00425, 2025

Reference 20

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source=pdf_text observed=2026-08-01T19:33:04.628070Z digest=sha256:8638632ab14b73e62bdc18a696ed2d6eb2fd323ea4cd1ddeec644e1b576b6e6b

Observation a8d3f609-32ef-4574-b824-891e9147078f · outbound

This paper cites Videodpo: Omni-preference alignment for video diffusion generation.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Videodpo: Omni-preference alignment for video diffusion generation

Reference 21

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source=pdf_text observed=2026-08-01T19:33:04.730904Z digest=sha256:8410f18dfff0f9555438ea20b76b3ba228b650191f50eb63f6a4e985c8eabaea

Observation 6c4b76e3-e405-4e19-a9b4-4d48688ca2a5 · outbound

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

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Physgen: Rigid-body physics-grounded image-to-video generation

Reference 22

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source=pdf_text observed=2026-08-01T19:33:04.809123Z digest=sha256:c7b420e035e07109ac2bffe8b7c7d476a285c4caa2d1581de9a39d39a72ef0a9

Observation a62b74b1-2aee-4071-882d-6fb82191a20b · outbound

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

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Evalcrafter: Benchmarking and evaluating large video generation models

Reference 23

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source=pdf_text observed=2026-08-01T19:33:04.890848Z digest=sha256:fc238c34fd58844ae0f5b6bc16ad3cda41efa970eedde8ca07ca4a0586b6a2bd

Observation ea3bf93e-939d-4aea-8145-326054c90500 · outbound

This paper cites Decoupled weight decay regularization.ICLR, 2019.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Decoupled weight decay regularization.ICLR, 2019

Reference 24

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source=pdf_text observed=2026-08-01T19:33:04.942221Z digest=sha256:7c5932b80a35ae2767098995514b377c546cee03577252c40e5d53330cabc32c

Observation cbc9f32b-4f2b-4a59-8690-85a7c285c599 · outbound

This paper cites Contextanyone: Context-aware diffusion for character-consistent text-to-video generation.arXiv preprint arXiv:2512.07328, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Contextanyone: Context-aware diffusion for character-consistent text-to-video generation.arXiv preprint arXiv:2512.07328, 2025

Reference 25

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source=pdf_text observed=2026-08-01T19:33:04.999366Z digest=sha256:59a1b482fc576aacb8ef76090c360dbc88072e7846b7fb66b3e30b8e7b1f181c

Observation 3fc6f76b-4a0b-4b80-b235-5728e2041b1f · outbound

This paper cites Towards world simulator: Crafting physical commonsense-based benchmark for video generation.ICML, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Towards world simulator: Crafting physical commonsense-based benchmark for video generation.ICML, 2025

Reference 26

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source=pdf_text observed=2026-08-01T19:33:05.094341Z digest=sha256:7318a8e25949caf15866d7d60ee2946209ef5d757a18e507c19048428ce7ba96

Observation d0be5d56-1ad8-4e9f-920a-4dd982c307a1 · outbound

This paper cites Grounding creativity in physics: A brief survey of physical priors in aigc.IJCAI, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Grounding creativity in physics: A brief survey of physical priors in aigc.IJCAI, 2025

Reference 27

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source=pdf_text observed=2026-08-01T19:33:05.144544Z digest=sha256:cc9b21c87e62fe192e7f0faa62e6305664f200aa1569b3e2067b84da12c77fac

Observation 061a6a70-fa80-4978-a645-3b23ca5a9683 · outbound

This paper cites Phymagic: Physical motion-aware gener- ative inference with confidence-guided llm.ECCV, 2026.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Phymagic: Physical motion-aware gener- ative inference with confidence-guided llm.ECCV, 2026

Reference 28

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source=pdf_text observed=2026-08-01T19:33:05.207245Z digest=sha256:fb6633621525e363c4127cf7c4c14153a00f59cad09cd0565c23e624ff49e3ba

Observation 6f5ed4ad-7f61-41f2-aa0d-4671c3480759 · outbound

This paper cites Video generation models as world simulators.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Video generation models as world simulators

Reference 29

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source=pdf_text observed=2026-08-01T19:33:05.259934Z digest=sha256:228f51d40f949d10685851d262a81cb4d8ddf9e837f4457c0c12389b640eef81

Observation b9a444ed-ca7e-4b2e-ae46-f04c795ef3b3 · outbound

This paper cites RDPO: Real Data Preference Optimization for Physics Consistency Video Generation.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation RDPO: Real Data Preference Optimization for Physics Consistency Video Generation

Reference 30

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source=pdf_text observed=2026-08-01T19:33:05.318987Z digest=sha256:5924dd5553ba3ebaa84e5e0921fcaa3522852aeefff6a5835ea3b7ce1840b8a7

Observation 7e1f85aa-73b6-4f3c-8b9b-ba87f4bd5895 · outbound

This paper cites Learning transferable visual models from natural language supervision.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Learning transferable visual models from natural language supervision

Reference 31

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source=pdf_text observed=2026-08-01T19:33:05.419885Z digest=sha256:9c0a0d0dc9d78c428de0fc8c8ec13010cd4f57b1f1deec733939b93e4646827f

Observation f814d13d-cdfb-4804-8fc9-9e00e61ff88e · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.NeurIPS, 2023.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Direct preference optimization: Your language model is secretly a reward model.NeurIPS, 2023

Reference 32

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source=pdf_text observed=2026-08-01T19:33:05.500052Z digest=sha256:23e04de8e8fb4096c90ddc0e56fe4e328896256920520e100f8931f8420f6573

Observation fdcf78fb-8165-486d-a569-20becef05731 · outbound

This paper cites Learning to reweight examples for robust deep learning.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Learning to reweight examples for robust deep learning

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source=pdf_text observed=2026-08-01T19:33:05.577629Z digest=sha256:82e73d3f420a9e9d9e8ec17ddaf08ad95dc3d269a750105f305bf65c9ad7c289

Observation 04d83f26-fb5c-4d79-8d4f-f91aaca7a98c · outbound

This paper cites Physmotion: Physics-grounded dynamics from a single image.3DV, 2026.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Physmotion: Physics-grounded dynamics from a single image.3DV, 2026

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source=pdf_text observed=2026-08-01T19:33:05.604747Z digest=sha256:82e5f811336562a1bae857beb2ea06c13d122bb4b00f71e2978d97a45bf469fe

Observation 34bcc05b-1983-41c0-9d9c-6510023a03ac · outbound

This paper cites Raft: Recurrent all-pairs field transforms for optical flow.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Raft: Recurrent all-pairs field transforms for optical flow

Reference 35

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source=pdf_text observed=2026-08-01T19:33:05.684476Z digest=sha256:78ff7c4161d42f64aa6d4552bd598e6b2bd443bdda0f8577520ae784c8790feb

Observation 5fdf0ac8-a47a-47e0-a89c-bf26150a0fe8 · outbound

This paper cites Fvd: A new metric for video generation.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Fvd: A new metric for video generation

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source=pdf_text observed=2026-08-01T19:33:05.729484Z digest=sha256:ee4d440850e0107ac4e5032b7f09dee60f0e806d76c8a8ee3ba37c2a66b9c468

Observation a41ef478-eb4d-44c5-9952-46e5f79a4a49 · outbound

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

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Wan: Open and Advanced Large-Scale Video Generative Models

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source=pdf_text observed=2026-08-01T19:33:05.808898Z digest=sha256:09cfcdaf43d682babdfc8cbec9b53461d21eede53fe9e41fc87fbe2a26cb9b9c

Observation 49383ea5-b189-426b-9a5c-f27972665d5c · outbound

This paper cites Wisa: World simulator assistant for physics-aware text-to-video generation.NeurIPS, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Wisa: World simulator assistant for physics-aware text-to-video generation.NeurIPS, 2025

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source=pdf_text observed=2026-08-01T19:33:05.873349Z digest=sha256:33f9ed4cf1911fb631b9557404763b6623ae45e92c62cfb4115284c3f4efd0a1

Observation 7391740c-f3f7-4143-94b0-1eb483431fba · outbound

This paper cites Physcorr: Dual-reward dpo for physics- constrained text-to-video generation with automated preference selection.arXiv preprint arXiv:2511.03997, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Physcorr: Dual-reward dpo for physics- constrained text-to-video generation with automated preference selection.arXiv preprint arXiv:2511.03997, 2025

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source=pdf_text observed=2026-08-01T19:33:05.930580Z digest=sha256:f2adb08a7846bcb5483908550cbed9b5ecda6a163d68289a621130e196e6999f

Observation 7ea3549c-c12a-41ff-9994-48fc6a364bf1 · outbound

This paper cites A survey on curriculum learning.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation A survey on curriculum learning

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source=pdf_text observed=2026-08-01T19:33:05.979839Z digest=sha256:b53d92d11f0c485ca45f8a0695c780c1bbf88690448f24a6d3527469fd7dcbf6

Observation 764d9002-ea7b-4914-a0f7-7f88090c6ee6 · outbound

This paper cites Internvid: A large-scale video-text dataset for multimodal understanding and generation.ICLR, 2024.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Internvid: A large-scale video-text dataset for multimodal understanding and generation.ICLR, 2024

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source=pdf_text observed=2026-08-01T19:33:06.055870Z digest=sha256:505c6a10c0650631c1990f60c55642b06b62341c22ee39ecf5c0f8e467c901d0

Observation 91402689-1297-49cb-a95f-3cdb3840b63c · outbound

This paper cites Densedpo: Fine-grained temporal preference optimization for video diffusion models.NeurIPS, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Densedpo: Fine-grained temporal preference optimization for video diffusion models.NeurIPS, 2025

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source=pdf_text observed=2026-08-01T19:33:06.139938Z digest=sha256:72aa4a526e4ffa8f1f7470176e49101968b5c6e2ac9e13dc940c525df883e9ef

Observation 88d04606-c22b-4eb3-9497-4d47ef09d980 · outbound

This paper cites Physgaussian: Physics-integrated 3d gaussians for generative dynamics.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Physgaussian: Physics-integrated 3d gaussians for generative dynamics

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source=pdf_text observed=2026-08-01T19:33:06.192730Z digest=sha256:25ca028c94a8af882f260f27baa3b7ae853ecaa173d89706acc76b4dda424df6

Observation 6d5cf34c-82be-4361-a2cc-3dc6465d72a3 · outbound

This paper cites VideoCLIP: Contrastive pre-training for zero-shot video-text understanding.EMNLP, 2021.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation VideoCLIP: Contrastive pre-training for zero-shot video-text understanding.EMNLP, 2021

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source=pdf_text observed=2026-08-01T19:33:06.267776Z digest=sha256:264b386425210b734afa0b14179a810a5c7c2a12657e9e5e0b5a5bd568c8c78d

Observation 6510dc96-b8ac-44ee-8886-146cf0835a7d · outbound

This paper cites Phyt2v: Llm-guided iterative self-refinement for physics-grounded text-to-video generation.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Phyt2v: Llm-guided iterative self-refinement for physics-grounded text-to-video generation

Reference 45

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source=pdf_text observed=2026-08-01T19:33:06.320683Z digest=sha256:79b383e92e91753c094c756f36eea31dd9bdf5911efe7dc3623bbdb9aafa1ba7

Observation cc196208-346e-4b50-9750-ffa52975afdf · outbound

This paper cites Qwen3 Technical Report.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Qwen3 Technical Report

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source=pdf_text observed=2026-08-01T19:33:06.400190Z digest=sha256:8b1c323ad6efac94eb139e5db80b310af93cac8be309d610e7431c45abd330c6

Observation f778a3f9-1b68-44d6-bd41-01521821c64b · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Depth anything: Unleashing the power of large-scale unlabeled data

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source=pdf_text observed=2026-08-01T19:33:06.476026Z digest=sha256:e911b4b25939be2666a8164f11eb50a829f83b9d58b47e82a82b6521898a46e9

Observation 5a910ce3-9d10-47ea-bfb0-1e119d1c9a85 · outbound

This paper cites Cogvideox: Text-to-video diffusion models with an expert transformer.ICLR, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Cogvideox: Text-to-video diffusion models with an expert transformer.ICLR, 2025

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source=pdf_text observed=2026-08-01T19:33:06.530030Z digest=sha256:b8d7ac635ee91d517fc709ce5786c2b9bbad179948ea4076350d01cd428b7d9b

Observation 97c3abd9-e377-4d8b-9f45-b991ee433ea2 · outbound

This paper cites Inference-time physics alignment of video gener- ative models with latent world models.arXiv preprint arXiv:2601.10553, 2026.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Inference-time physics alignment of video gener- ative models with latent world models.arXiv preprint arXiv:2601.10553, 2026

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source=pdf_text observed=2026-08-01T19:33:06.601813Z digest=sha256:5d0840aba71d55b302ba8909199162a5bbf81d29255d46c9e3b440e6b2a309cf

Observation 9aaa0483-d2a5-49e9-bdee-d9e04380b29d · outbound

This paper cites Think before you diffuse: Llms-guided physics-aware video generation.arXiv preprint arXiv:2505.21653, 2025.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Think before you diffuse: Llms-guided physics-aware video generation.arXiv preprint arXiv:2505.21653, 2025

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source=pdf_text observed=2026-08-01T19:33:06.688570Z digest=sha256:5357e7f29f705a427fec7d1ffa87a9331e1e05180bb37c48789c63ba54f837b5

Observation 97eadecb-6603-4cb3-aeef-ee588ca478a1 · outbound

This paper cites Physrvg: Physics- aware unified reinforcement learning for video generative models.arXiv preprint arXiv:2601.11087, 2026.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Physrvg: Physics- aware unified reinforcement learning for video generative models.arXiv preprint arXiv:2601.11087, 2026

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source=pdf_text observed=2026-08-01T19:33:06.757158Z digest=sha256:5f54054cf24c68549a383260a4d8067eec285019f9f9894cabc4090d9fc09db8

Observation ed83d256-f265-4afb-a24f-de02bf6bf18e · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.NeurIPS, 2023.

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation Judging llm-as-a-judge with mt-bench and chatbot arena.NeurIPS, 2023

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source=pdf_text observed=2026-08-01T19:33:06.822584Z digest=sha256:115cfc5f78442b7ca6e269af94c02fa2373e49a837a65c805a35302b0fde8926

Pith citing papers

Observation 1fd55159-d00a-4060-885b-2c879ece720d · inbound

Multi-Branch Policy Optimization for Multimodal Large Language Models cites this paper.

Multi-Branch Policy Optimization for Multimodal Large Language Models When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation

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local_arxiv, observed 2026-08-11T00:36:01.312293Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T00:36:01.036574Z digest=sha256:d98082fcc4b1aa86585ab0c67bbca9a1c0bc62bbf534877e13aaa24cbc55e756