Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T17:10:17.266445Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 4 inbound Pith citation observations for arXiv:2502.00968.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T17:10:17.266445Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:49:47.281070Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T21:37:25.369183Z
74 of 74 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 5dba87c9-3495-44e0-be1a-9201a128c4ab · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Cold diffusion: Inverting arbitrary image transforms without noise
Reference 1
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CoDe: Blockwise Control for Denoising Diffusion Models Universal Guidance for Diffusion Models
Reference 2
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Observation 5b2c2b57-e5a0-426c-b683-452ff8c54a30 · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Lumiere: A Space-Time Diffusion Model for Video Generation
Reference 3
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Observation e6a383f7-0768-4419-be70-6b7ae2bfa043 · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Theoretical guarantees on the best-of-n alignment policy
Reference 4
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CoDe: Blockwise Control for Denoising Diffusion Models Training Diffusion Models with Reinforcement Learning
Reference 5
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CoDe: Blockwise Control for Denoising Diffusion Models Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
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CoDe: Blockwise Control for Denoising Diffusion Models Monte Carlo guided Diffusion for Bayesian linear inverse problems
Reference 7
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CoDe: Blockwise Control for Denoising Diffusion Models Adaptively-realistic image generation from stroke and sketch with diffusion model
Reference 8
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CoDe: Blockwise Control for Denoising Diffusion Models Improving diffusion models for inverse problems using manifold constraints
Reference 9
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CoDe: Blockwise Control for Denoising Diffusion Models Diffusion Posterior Sampling for General Noisy Inverse Problems
Reference 10
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CoDe: Blockwise Control for Denoising Diffusion Models Unresolved cited work
Reference 11
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CoDe: Blockwise Control for Denoising Diffusion Models Diffusion Models Beat GANs on Image Synthesis
Reference 12
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CoDe: Blockwise Control for Denoising Diffusion Models Tweedie’s formula and selection bias
Reference 13
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CoDe: Blockwise Control for Denoising Diffusion Models DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models
Reference 14
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CoDe: Blockwise Control for Denoising Diffusion Models Scaling Laws for Reward Model Overoptimization
Reference 15
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CoDe: Blockwise Control for Denoising Diffusion Models Image style transfer using convolutional neural networks
Reference 16
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CoDe: Blockwise Control for Denoising Diffusion Models Diffusion-rpo: Aligning diffusion models through relative preference optimization, 2024
Reference 17
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CoDe: Blockwise Control for Denoising Diffusion Models BoNBoN Alignment for Large Language Models and the Sweetness of Best-of-n Sampling
Reference 18
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Observation 116fd617-db5a-4984-a7d9-6de48041da5e · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Gradient Guidance for Diffusion Models: An Optimization Perspective
Reference 19
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Observation 46cbc6b0-375e-4a44-9e4c-4adfea94b0f2 · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Manifold preserving guided diffusion
Reference 20
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Observation 896c5801-6dd3-4ac5-9dd9-77bbf37ba285 · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Clipscore: A reference-free evaluation metric for image captioning
Reference 21
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Observation 696fc201-a7b1-4881-a56d-ebd677345cc8 · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Gans trained by a two time-scale update rule converge to a local nash equilibrium, 2017
Reference 22
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CoDe: Blockwise Control for Denoising Diffusion Models Denoising Diffusion Probabilistic Models
Reference 23
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CoDe: Blockwise Control for Denoising Diffusion Models Classifier-Free Diffusion Guidance
Reference 24
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CoDe: Blockwise Control for Denoising Diffusion Models Rethinking fid: Towards a better evaluation metric for image generation
Reference 25
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Observation bae8d4a8-8726-4e68-82af-3e6af9e2593c · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Elucidating optimal reward-diversity tradeoffs in text-to-image diffusion models, 2024
Reference 26
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CoDe: Blockwise Control for Denoising Diffusion Models Leveraging early-stage robustness in diffusion models for efficient and high-quality image synthesis
Reference 27
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Observation 4dbca730-f1b4-4b59-aa1d-9e2ce7eeecde · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Genie: Generative hard negative images through diffusion, 2023
Reference 28
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Observation 51d2c4b0-c08c-4c05-84c8-1ee3ce9edd31 · outbound
CoDe: Blockwise Control for Denoising Diffusion Models RL with KL penalties is better viewed as Bayesian inference
Reference 29
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Observation 25fbaf86-f304-4ad6-9ac1-3e9fd3353060 · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Direct consistency optimization for compositional text-to-image personalization, 2024
Reference 30
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Observation 23cf126b-4575-4066-9caa-1311f594c5e0 · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding
Reference 31
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Observation 588d12da-4667-4aea-8cb2-9d3317e3ccfe · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Gligen: Open-set grounded text-to-image generation
Reference 32
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CoDe: Blockwise Control for Denoising Diffusion Models SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
Reference 33
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Observation a58f8c90-cca4-43d0-b901-64b62377b998 · outbound
CoDe: Blockwise Control for Denoising Diffusion Models FreeControl: Training-Free Spatial Control of Any Text-to-Image Diffusion Model with Any Condition
Reference 34
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CoDe: Blockwise Control for Denoising Diffusion Models T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models
Reference 35
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Observation 8eebbac2-3bf2-4d0a-9ee8-ad36a3810b6a · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Information Theoretic Guarantees For Policy Alignment In Large Language Models
Reference 36
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Observation fe702e51-70d0-46fc-aeb8-0a48928c84b2 · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Controlled Decoding from Language Models
Reference 37
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Observation 8520fe0c-86ed-4ff2-b6e7-cb1aca61c6f4 · outbound
CoDe: Blockwise Control for Denoising Diffusion Models Improved Denoising Diffusion Probabilistic Models , 7 2021
Reference 38
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CoDe: Blockwise Control for Denoising Diffusion Models Particle Denoising Diffusion Sampler
Reference 39
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CoDe: Blockwise Control for Denoising Diffusion Models Aligning Text-to-Image Diffusion Models with Reward Backpropagation
Reference 40
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CoDe: Blockwise Control for Denoising Diffusion Models Spontaneous symmetry breaking in generative diffusion models
Reference 41
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CoDe: Blockwise Control for Denoising Diffusion Models High-Resolution Image Synthesis with Latent Diffusion Models
Reference 42
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CoDe: Blockwise Control for Denoising Diffusion Models Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Reference 43
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CoDe: Blockwise Control for Denoising Diffusion Models CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling
Reference 44
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CoDe: Blockwise Control for Denoising Diffusion Models Facenet: A unified embedding for face recognition and clustering
Reference 45
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CoDe: Blockwise Control for Denoising Diffusion Models Laion-400m: Open dataset of clip-filtered 400 million image-text pairs, 2021
Reference 46
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CoDe: Blockwise Control for Denoising Diffusion Models Laion-5b: An open large-scale dataset for training next generation image-text models
Reference 47
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CoDe: Blockwise Control for Denoising Diffusion Models A phase transition in diffusion models reveals the hierarchical nature of data
Reference 48
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Reference 49
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CoDe: Blockwise Control for Denoising Diffusion Models Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Reference 50
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CoDe: Blockwise Control for Denoising Diffusion Models Measuring Style Similarity in Diffusion Models
Reference 51
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Reference 52
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CoDe: Blockwise Control for Denoising Diffusion Models Generative Modeling by Estimating Gradients of the Data Distribution
Reference 53
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Reference 54
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Reference 55
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Reference 56
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Reference 57
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CoDe: Blockwise Control for Denoising Diffusion Models Bayesian learning via stochastic gradient Langevin dynamics
Reference 58
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Reference 59
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Reference 60
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Reference 61
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Reference 62
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Reference 63
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Reference 64
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Reference 65
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Reference 66
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Reference 67
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CoDe: Blockwise Control for Denoising Diffusion Models Joint face detection and alignment using multitask cascaded convolutional networks
Reference 68
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Reference 69
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Reference 70
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Reference 71
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CoDe: Blockwise Control for Denoising Diffusion Models Unresolved cited work
Reference 72
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Reference 73
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Scaling Image and Video Generation via Test-Time Evolutionary Search CoDe: Blockwise Control for Denoising Diffusion Models
Reference 59
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Reference 38
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Reference 28
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Reference 71
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