Paper Citation Record · LEDGER

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models

As of 8 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2508.00289.

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

pith.paper-citation-record.v1
2508.00289 v1

Coverage vector

measured 44 of 44 reference resolution

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44 of 44 outbound references displayed

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External citation measurements

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Outbound references

Observation 61f32914-3bf4-4ef5-99a5-9ed11e27bdd0 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 1

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Observation 97ff0b24-2483-4afe-b4c9-ff89109da48c · outbound

This paper cites Universal guidance for diffusion models.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Universal guidance for diffusion models

Reference 2

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Observation 65cb2da8-1ade-4ef7-9343-8835e291098a · outbound

This paper cites Gradients without Backpropagation.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Gradients without Backpropagation

Reference 3

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This paper cites Vggsound: A large-scale audio-visual dataset.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Vggsound: A large-scale audio-visual dataset

Reference 4

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Observation 85c9296b-5c14-4974-a0a9-539afb891a64 · outbound

This paper cites Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models

Reference 5

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Observation 6613ac4e-a0ee-4d69-888d-5f7d6afcd8a9 · outbound

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

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing

Reference 6

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This paper cites Tweedie’s formula and selection bias.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Tweedie’s formula and selection bias

Reference 7

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Observation e045067b-375a-4c81-9083-815f84451c25 · outbound

This paper cites Douceur, Jon Howell, and Jared Saul.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Douceur, Jon Howell, and Jared Saul

Reference 8

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Observation e1f4623e-a616-43d3-b1b2-ef71f27d9dbc · outbound

This paper cites Can forward gra- dient match backpropagation? In International Conference on Machine Learning, pages 10249–10264.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Can forward gra- dient match backpropagation? In International Conference on Machine Learning, pages 10249–10264

Reference 9

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Observation 780e7832-8161-4df9-8f09-8a3602faf2b3 · outbound

This paper cites Imagebind: One embedding space to bind them all.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Imagebind: One embedding space to bind them all

Reference 10

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Observation 353fe7c7-d430-439c-a0c6-2b15c9063727 · outbound

This paper cites Animatediff: Animate your personalized text-to- image diffusion models without specific tuning.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Animatediff: Animate your personalized text-to- image diffusion models without specific tuning

Reference 11

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Observation 0c7c502e-e2ee-4244-aa30-ef2f52fa8d91 · outbound

This paper cites Manifold preserving guided diffusion.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Manifold preserving guided diffusion

Reference 12

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Observation e5f97f8a-a3fc-42d4-af10-67abb484eccc · outbound

This paper cites Denoising dif- fusion probabilistic models.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Denoising dif- fusion probabilistic models

Reference 13

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This paper cites Deep learning face attributes in the wild.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Deep learning face attributes in the wild

Reference 14

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Observation 109e8f0a-ab82-41a2-97a5-9426a5050ddd · outbound

This paper cites SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations

Reference 15

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This paper cites T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models

Reference 16

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This paper cites Patel, and Tim K.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Patel, and Tim K

Reference 17

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This paper cites Steered diffusion: A generalized framework for plug- and-play conditional image synthesis.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Steered diffusion: A generalized framework for plug- and-play conditional image synthesis

Reference 18

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This paper cites Ditto: Diffusion inference-time t- optimization for music generation.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Ditto: Diffusion inference-time t- optimization for music generation

Reference 19

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Observation e8293c18-bbc8-4b46-83b0-03320f0856f9 · outbound

This paper cites Automatic differentiation in pytorch.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Automatic differentiation in pytorch

Reference 20

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Observation 6f0f0cf5-2519-4903-bfe6-a7ba4f508d54 · outbound

This paper cites Styleclip: Text-driven manipulation of stylegan imagery.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Styleclip: Text-driven manipulation of stylegan imagery

Reference 21

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Observation f431413d-636f-4661-9c85-40a0ccca9d2d · outbound

This paper cites Scaling Forward Gradient With Local Losses.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Scaling Forward Gradient With Local Losses

Reference 22

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This paper cites Denoising Diffusion Implicit Models.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Denoising Diffusion Implicit Models

Reference 23

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This paper cites Loss-guided diffusion models for plug-and-play controllable generation.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Loss-guided diffusion models for plug-and-play controllable generation

Reference 24

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This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Score-Based Generative Modeling through Stochastic Differential Equations

Reference 25

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This paper cites Towards Accurate Generative Models of Video: A New Metric & Challenges.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 26

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This paper cites EDICT: Exact Diffusion Inversion via Coupled Transformations.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models EDICT: Exact Diffusion Inversion via Coupled Transformations

Reference 27

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This paper cites End-to-end diffusion latent optimization improves classifier guidance.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models End-to-end diffusion latent optimization improves classifier guidance

Reference 28

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Observation 99ed74fa-e27b-4e31-a287-b25c27dc2ee7 · outbound

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

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Exploring video quality assessment on user generated contents from aesthetic and technical perspectives

Reference 29

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

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation

Reference 30

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This paper cites Cvpr 2023 text guided video editing competition, 2023.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Cvpr 2023 text guided video editing competition, 2023

Reference 31

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This paper cites Seeing and hearing: Open-domain visual- audio generation with diffusion latent aligners.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Seeing and hearing: Open-domain visual- audio generation with diffusion latent aligners

Reference 32

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

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 33

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This paper cites Diverse and aligned audio-to-video genera- tion via text-to-video model adaptation, 2023.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Diverse and aligned audio-to-video genera- tion via text-to-video model adaptation, 2023

Reference 34

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This paper cites Tfg: Unified training-free guidance for diffusion models.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Tfg: Unified training-free guidance for diffusion models

Reference 35

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This paper cites Freedom: Training-free energy-guided condi- tional diffusion model.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Freedom: Training-free energy-guided condi- tional diffusion model

Reference 36

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Observation 536b11ec-c3a9-494b-b212-70f0c23e8c2f · outbound

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

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Adding conditional control to text-to-image diffusion models

Reference 37

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This paper cites Let f : Rm − →Rn.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Let f : Rm − →Rn

Reference 40

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This paper cites In all experiments, we em- ploy AnimateDiff [11] with epiCRealism 2 as the base text- to-image model to generate 16 frames 8fps.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models In all experiments, we em- ploy AnimateDiff [11] with epiCRealism 2 as the base text- to-image model to generate 16 frames 8fps

Reference 41

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TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models A bird in a forest

Reference 42

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This paper cites However, since our primary focus is text- to-video tasks, we do not explore this aspect in depth but provide evidence of its applicability.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models However, since our primary focus is text- to-video tasks, we do not explore this aspect in depth but provide evidence of its applicability

Reference 43

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Observation 9cc8f007-c6f9-46bb-bc68-7ac05ac747c9 · outbound

This paper cites Following [35], for super resolution, and deblurring tasks, we use the CAT-DDPM diffusion model trained on the CAT dataset [8].

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Following [35], for super resolution, and deblurring tasks, we use the CAT-DDPM diffusion model trained on the CAT dataset [8]

Reference 44

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Reference 2023

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Pith citing papers

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