Paper Citation Record · LEDGER

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models

As of 9 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2607.14194.

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

pith.paper-citation-record.v1
2607.14194 v1

Coverage vector

measured 46 of 46 reference resolution

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measured 46 of 46 standing notices

One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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Outbound references

Observation d298be65-a13e-43c5-a721-1c117fbe1a22 · outbound

This paper cites an unresolved cited work.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Unresolved cited work

Reference 1

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This paper cites Pappas, Florian Tramèr, Hamed Hassani, and Eric Wong.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Pappas, Florian Tramèr, Hamed Hassani, and Eric Wong

Reference 3

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This paper cites Video unlearn- ing via low-rank refusal vector.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Video unlearn- ing via low-rank refusal vector

Reference 4

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Reference 5

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Observation f8985bde-55b8-4e35-a6be-e5793d88e36a · outbound

This paper cites Unified concept editing in diffusion models.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Unified concept editing in diffusion models

Reference 7

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This paper cites Reliable and efficient concept erasure of text-to-image diffusion models.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Reliable and efficient concept erasure of text-to-image diffusion models

Reference 8

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Observation a3f0b53d-fb6c-46b1-ac21-7b84c8ca06fe · outbound

This paper cites AnimateDiff: Animate your personalized text-to-image diffu- sion models without specific tuning.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models AnimateDiff: Animate your personalized text-to-image diffu- sion models without specific tuning

Reference 9

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Observation f3e7ea34-0f0c-4d22-aff6-32d796139b28 · outbound

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

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models CLIPScore: A reference-free evaluation metric for image captioning

Reference 10

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Observation 8c4d10aa-9546-4262-8202-4e05bc54300f · outbound

This paper cites GANs trained by a two time-scale update rule converge to a local nash equilibrium.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models GANs trained by a two time-scale update rule converge to a local nash equilibrium

Reference 11

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Observation a70bd5b5-6697-400b-a3c1-b897df24fe1b · outbound

This paper cites Classifier-Free Diffusion Guidance.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Classifier-Free Diffusion Guidance

Reference 12

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Observation ca2290e7-b3a6-4719-8a24-77073e7ad763 · outbound

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

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Imagen Video: High Definition Video Generation with Diffusion Models

Reference 13

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Observation 39bbfba2-597d-4e54-b625-3dd543074ff6 · outbound

This paper cites ConceptVoid: Precision multi- concept erasure in generative video diffusion.Mathematics, 13(16):2652, 2025.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models ConceptVoid: Precision multi- concept erasure in generative video diffusion.Mathematics, 13(16):2652, 2025

Reference 14

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This paper cites Ultralytics YOLOv8.https://github.com/ ultralytics/ultralytics, 2023.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Ultralytics YOLOv8.https://github.com/ ultralytics/ultralytics, 2023

Reference 16

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

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 17

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This paper cites Ablating concepts in text-to-image diffusion models.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Ablating concepts in text-to-image diffusion models

Reference 18

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Observation 4c34a8d0-f4b6-47c7-9f19-031f9a5f4801 · outbound

This paper cites Learning blind video temporal consistency.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Learning blind video temporal consistency

Reference 19

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Observation d8402b28-62ae-4308-9578-0597e1638f05 · outbound

This paper cites Fr\'echet Video Motion Distance: A Metric for Evaluating Motion Consistency in Videos.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Fr\'echet Video Motion Distance: A Metric for Evaluating Motion Consistency in Videos

Reference 20

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Observation 496eb3d4-253d-433e-9b80-8ad9b34f199f · outbound

This paper cites Rethinking machine unlearning in image generation models.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Rethinking machine unlearning in image generation models

Reference 21

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Observation 614eefaa-da8f-4f41-a2fb-a1ebe897e20a · outbound

This paper cites AutoDAN: Generating stealthy jailbreak prompts on aligned large language models.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models AutoDAN: Generating stealthy jailbreak prompts on aligned large language models

Reference 22

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This paper cites FETV: A benchmark for fine-grained evaluation of open-domain text-to-video generation.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models FETV: A benchmark for fine-grained evaluation of open-domain text-to-video generation

Reference 24

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models MACE: Mass concept erasure in diffusion models

Reference 25

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This paper cites T2VSafetyBench: Evaluating the safety of text-to-video generative models.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models T2VSafetyBench: Evaluating the safety of text-to-video generative models

Reference 26

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Observation dac78df0-a9db-42d3-85d7-b438db03ab18 · outbound

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

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Learning transferable visual models from natural language supervision

Reference 27

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Girshick, and Ali Farhadi

Reference 28

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Progressive distillation for fast sampling of diffusion models

Reference 29

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Safe latent diffusion: Mitigating inappropriate degeneration in diffusion models

Reference 30

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Multi-task learning as multi-objective opti- mization

Reference 31

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Make-A-Video: Text-to-video generation without text-video data

Reference 32

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Wan: Open and Advanced Large-Scale Video Generative Models

Reference 34

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 35

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Erasing undesirable influence in diffusion models

Reference 36

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Unlearning concepts in diffusion model via concept domain correction and concept preserving gradient

Reference 37

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models VideoEraser: Concept erasure in text-to-video diffusion models

Reference 38

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models CogVideoX: Text-to-video diffusion models with an expert transformer

Reference 39

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This paper cites T2VUnlearning: A concept erasing method for text-to-video diffusion models.arXiv preprint arXiv:2505.17550,.

Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models T2VUnlearning: A concept erasing method for text-to-video diffusion models.arXiv preprint arXiv:2505.17550,

Reference 40

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models SAFREE: Training- free and adaptive guard for safe text-to-image and video generation

Reference 41

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Forget-me- not: Learning to forget in text-to-image diffusion models

Reference 42

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Efros, Eli Shechtman, and Oliver Wang

Reference 43

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models To generate or not? safety-driven unlearned diffusion models are still easy to generate unsafe images

Reference 44

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness

Reference 45

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k

Reference 46

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k

Reference 51

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Imagen Video: High Definition Video Generation with Diffusion Models

Reference 2022

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models URL https://doi.org/10.1109/CVPR52729

Reference 2023

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models Fr\'echet Video Motion Distance: A Metric for Evaluating Motion Consistency in Videos

Reference 2024

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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models URLhttps://arxiv.org/abs/2505.17550

Reference 2025

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