{"total":125,"rows":[{"id":"2311.12092","title":"Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models","created":"2023-11-20","cited_by_count":153,"area":"diffusion"},{"id":"2501.18052","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","created":"2025-01-29","cited_by_count":80,"area":"diffusion"},{"id":"2311.17216","title":"Self-Discovering Interpretable Diffusion Latent Directions for Responsible Text-to-Image Generation","created":"2023-11-28","cited_by_count":69,"area":"diffusion"},{"id":"2408.00760","title":"Smoothed Energy Guidance: Guiding Diffusion Models with Reduced Energy Curvature of Attention","created":"2024-08-01","cited_by_count":59,"area":"diffusion"},{"id":"2312.05390","title":"NoiseCLR: A Contrastive Learning Approach for Unsupervised Discovery of Interpretable Directions in Diffusion Models","created":"2023-12-08","cited_by_count":47,"area":"diffusion"},{"id":"2406.09413","title":"Interpreting the Weight Space of Customized Diffusion Models","created":"2024-06-13","cited_by_count":36,"area":"diffusion"},{"id":"2403.14291","title":"Open-Vocabulary Attention Maps with Token Optimization for Semantic Segmentation in Diffusion Models","created":"2024-03-21","cited_by_count":29,"area":"diffusion"},{"id":"2602.05993","title":"Diamond Maps: Efficient Reward Alignment via Stochastic Flow Maps","created":"2026-02-05","cited_by_count":29,"area":"diffusion"},{"id":"2407.11451","title":"Isometric Representation Learning for Disentangled Latent Space of Diffusion Models","created":"2024-07-16","cited_by_count":22,"area":"diffusion"},{"id":"2501.18672","title":"Drag Your Gaussian: Effective Drag-Based Editing with Score Distillation for 3D Gaussian Splatting","created":"2025-01-30","cited_by_count":22,"area":null},{"id":"2504.15473","title":"Emergence and Evolution of Interpretable Concepts in Diffusion Models","created":"2025-04-21","cited_by_count":22,"area":"diffusion"},{"id":"2407.12173","title":"Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise Spectral Analysis","created":"2024-07-16","cited_by_count":19,"area":"diffusion"},{"id":"2406.00519","title":"Learning Discrete Concepts in Latent Hierarchical Models","created":"2024-06-01","cited_by_count":17,"area":null},{"id":"2406.05191","title":"DiffusionPID: Interpreting Diffusion via Partial Information Decomposition","created":"2024-06-07","cited_by_count":16,"area":"diffusion"},{"id":"2503.07050","title":"TIDE : Temporal-Aware Sparse Autoencoders for Interpretable Diffusion Transformers in Image Generation","created":"2025-03-10","cited_by_count":16,"area":"diffusion"},{"id":"2404.12488","title":"Global Counterfactual Directions","created":"2024-04-18","cited_by_count":15,"area":"diffusion"},{"id":"2409.02374","title":"Exploring Low-Dimensional Subspaces in Diffusion Models for Controllable Image Editing","created":"2024-09-04","cited_by_count":15,"area":"diffusion"},{"id":"2409.16535","title":"Prompt Sliders for Fine-Grained Control, Editing and Erasing of Concepts in Diffusion Models","created":"2024-09-25","cited_by_count":15,"area":"diffusion"},{"id":"2506.07883","title":"Diffusion Counterfactual Generation with Semantic Abduction","created":"2025-06-09","cited_by_count":10,"area":"diffusion"},{"id":"2509.21379","title":"SAEmnesia: Erasing Concepts in Diffusion Models with Supervised Sparse Autoencoders","created":"2025-09-23","cited_by_count":10,"area":"diffusion"},{"id":"2411.02259","title":"Counterfactual Explanations via Riemannian Latent Space Traversal","created":"2024-11-04","cited_by_count":9,"area":null},{"id":"2506.10632","title":"Hessian Geometry of Latent Space in Generative Models","created":"2025-06-12","cited_by_count":9,"area":"diffusion"},{"id":"2506.14020","title":"Bures-Wasserstein Flow Matching for Graph Generation","created":"2025-06-16","cited_by_count":9,"area":"diffusion"},{"id":"2408.08558","title":"Linear combinations of latents in generative models: subspaces and beyond","created":"2024-08-16","cited_by_count":8,"area":null},{"id":"2410.07763","title":"HARIVO: Harnessing Text-to-Image Models for Video Generation","created":"2024-10-10","cited_by_count":8,"area":"diffusion"},{"id":"2502.02513","title":"Diffusion Generative Modeling on Lie Group Representations","created":"2025-02-04","cited_by_count":8,"area":"diffusion"},{"id":"2505.15427","title":"Responsible Diffusion Models via Constraining Text Embeddings within Safe Regions","created":"2025-05-21","cited_by_count":8,"area":"diffusion"},{"id":"2509.20091","title":"Unleashing the Potential of the Semantic Latent Space in Diffusion Models for Image Dehazing","created":"2025-09-24","cited_by_count":8,"area":"diffusion"},{"id":"2403.19645","title":"Learn Once, Edit Anywhere: Visual Direction Transfer for Diffusion Models","created":"2024-03-28","cited_by_count":6,"area":"diffusion"},{"id":"2411.08224","title":"Joint Diffusion models in Continual Learning","created":"2024-11-12","cited_by_count":6,"area":"diffusion"},{"id":"2503.05540","title":"Riemann$^2$: Learning Riemannian Submanifolds from Riemannian Data","created":"2025-03-07","cited_by_count":6,"area":null},{"id":"2505.11128","title":"What's Inside Your Diffusion Model? A Score-Based Riemannian Metric to Explore the Data Manifold","created":"2025-05-16","cited_by_count":6,"area":"diffusion"},{"id":"2505.17517","title":"The Spacetime of Diffusion Models: An Information Geometry Perspective","created":"2025-05-23","cited_by_count":6,"area":"diffusion"},{"id":"2506.14404","title":"Causally Steered Diffusion for Automated Video Counterfactual Generation","created":"2025-06-17","cited_by_count":6,"area":"diffusion"},{"id":"2509.18831","title":"Text Slider: Efficient and Plug-and-Play Continuous Concept Control for Image/Video Synthesis via LoRA Adapters","created":"2025-09-23","cited_by_count":6,"area":"diffusion"},{"id":"2510.06827","title":"StyleKeeper: Prevent Content Leakage using Negative Visual Query Guidance","created":"2025-10-08","cited_by_count":6,"area":"diffusion"},{"id":"2410.03368","title":"Latent Abstractions in Generative Diffusion Models","created":"2024-10-04","cited_by_count":4,"area":"diffusion"},{"id":"2502.00382","title":"Masked Generative Nested Transformers with Decode Time Scaling","created":"2025-02-01","cited_by_count":4,"area":null},{"id":"2503.17794","title":"Progressive Prompt Detailing for Improved Alignment in Text-to-Image Generative Models","created":"2025-03-22","cited_by_count":4,"area":null},{"id":"2504.20288","title":"Image Interpolation with Score-based Riemannian Metrics of Diffusion Models","created":"2025-04-28","cited_by_count":4,"area":"diffusion"},{"id":"2505.17560","title":"Deeper Diffusion Models Amplify Bias","created":"2025-05-23","cited_by_count":4,"area":"diffusion"},{"id":"2510.14269","title":"Nonparametric Data Attribution for Diffusion Models","created":"2025-10-16","cited_by_count":4,"area":"diffusion"},{"id":"2512.08505","title":"Early Estimation of Language to Latent Alignment in Diffusion Models","created":"2025-12-09","cited_by_count":4,"area":"diffusion"},{"id":"2406.17462","title":"EvolvED: Evolutionary Embeddings to Understand the Generation Process of Diffusion Models","created":"2024-06-25","cited_by_count":3,"area":"diffusion"},{"id":"2408.16845","title":"Enabling Local Editing in Diffusion Models by Joint and Individual Component Analysis","created":"2024-08-29","cited_by_count":3,"area":"diffusion"},{"id":"2502.02225","title":"Exploring the latent space of diffusion models directly through singular value decomposition","created":"2025-02-04","cited_by_count":3,"area":"diffusion"},{"id":"2503.06698","title":"What's in a Latent? Leveraging Diffusion Latent Space for Domain Generalization","created":"2025-03-09","cited_by_count":3,"area":null},{"id":"2506.00771","title":"Manipulating 3D Molecules in a Fixed-Dimensional E(3)-Equivariant Latent Space","created":"2025-06-01","cited_by_count":3,"area":null},{"id":"2506.20977","title":"From Cradle to Cane: A Two-Pass Framework for High-Fidelity Lifespan Face Aging","created":"2025-06-26","cited_by_count":3,"area":null},{"id":"2507.06547","title":"Concept-TRAK: Understanding how diffusion models learn concepts through concept-level attribution","created":"2025-07-09","cited_by_count":3,"area":"diffusion"},{"id":"2510.04504","title":"Asynchronous Denoising Diffusion Models for Aligning Text-to-Image Generation","created":"2025-10-06","cited_by_count":3,"area":"diffusion"},{"id":"2510.05509","title":"Be Tangential to Manifold: Discovering Riemannian Metric for Diffusion Models","created":"2025-10-07","cited_by_count":3,"area":"diffusion"},{"id":"2510.08062","title":"Attribution-by-design: Ensuring Inference-Time Provenance in Generative Music Systems","created":"2025-10-09","cited_by_count":3,"area":null},{"id":"2512.00196","title":"Emergent Riemannian geometry over learning discrete computations on continuous manifolds","created":"2025-11-28","cited_by_count":3,"area":null},{"id":"2512.14884","title":"Vibe Spaces for Creatively Connecting and Expressing Visual Concepts","created":"2025-12-16","cited_by_count":3,"area":null},{"id":"2603.28764","title":"Geometry-aware similarity metrics for neural representations on Riemannian and statistical manifolds","created":"2026-03-30","cited_by_count":3,"area":null},{"id":"2606.15796","title":"DifFRACT: Diffusion Feature Reconstruction and Attribution for Circuit Tracing","created":"2026-06-14","cited_by_count":3,"area":"diffusion"},{"id":"2401.10247","title":"Resolution Chromatography of Diffusion Models","created":"2023-12-07","cited_by_count":2,"area":"diffusion"},{"id":"2406.18588","title":"Varying Manifolds in Diffusion: From Time-varying Geometries to Visual Saliency","created":"2024-06-07","cited_by_count":2,"area":null},{"id":"2409.01138","title":"Generating Synthetic Satellite Imagery for Rare Objects: An Empirical Comparison of Models and Metrics","created":"2024-09-02","cited_by_count":2,"area":null},{"id":"2410.05564","title":"Unsupervised Representation Learning from Sparse Transformation Analysis","created":"2024-10-07","cited_by_count":2,"area":null},{"id":"2412.05003","title":"SLayR: Scene Layout Generation with Rectified Flow","created":"2024-12-06","cited_by_count":2,"area":"diffusion"},{"id":"2501.00873","title":"Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time Adaptation","created":"2025-01-01","cited_by_count":2,"area":"diffusion"},{"id":"2503.06637","title":"CLAD: Constrained Latent Action Diffusion for Vision-Language Procedure Planning","created":"2025-03-09","cited_by_count":2,"area":"diffusion"},{"id":"2504.21307","title":"The Linear Geometry of Interpretable Tokens: Jailbreaking Attacks and Defenses for Unlearned Diffusion Models","created":"2025-04-30","cited_by_count":2,"area":"diffusion"},{"id":"2506.00327","title":"Latent Guidance in Diffusion Models for Perceptual Evaluations","created":"2025-05-31","cited_by_count":2,"area":"diffusion"},{"id":"2508.13866","title":"SAGA: Learning Signal-Aligned Distributions for Improved Text-to-Image Generation","created":"2025-08-19","cited_by_count":2,"area":null},{"id":"2509.08908","title":"Diffusion-Based Action Recognition Generalizes to Untrained Domains","created":"2025-09-10","cited_by_count":2,"area":null},{"id":"2511.11253","title":"CountSteer: Steering Attention for Object Counting in Diffusion Models","created":"2025-11-14","cited_by_count":2,"area":"diffusion"},{"id":"2404.03145","title":"DreamWalk: Style Space Exploration using Diffusion Guidance","created":"2024-04-04","cited_by_count":1,"area":"diffusion"},{"id":"2404.18252","title":"Improving Training-free Conditional Diffusion Model via Fisher Information","created":"2024-04-28","cited_by_count":1,"area":"diffusion"},{"id":"2406.14862","title":"LatentExplainer: Explaining Latent Representations in Deep Generative Models with Multimodal Large Language Models","created":"2024-06-21","cited_by_count":1,"area":"mllm"},{"id":"2407.11244","title":"(Deep) Generative Geodesics","created":"2024-07-15","cited_by_count":1,"area":null},{"id":"2412.12912","title":"Unsupervised Region-Based Image Editing of Denoising Diffusion Models","created":"2024-12-17","cited_by_count":1,"area":"diffusion"},{"id":"2504.17525","title":"Text-to-Image Alignment in Denoising-Based Models through Step Selection","created":"2025-04-24","cited_by_count":1,"area":null},{"id":"2511.12757","title":"Which Way from B to A: The role of embedding geometry in image interpolation for Stable Diffusion","created":"2025-11-16","cited_by_count":1,"area":"diffusion"},{"id":"2511.20295","title":"Back to the Feature: Explaining Video Classifiers with Video Counterfactual Explanations","created":"2025-11-25","cited_by_count":1,"area":null},{"id":"2512.08125","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","created":"2025-12-09","cited_by_count":1,"area":null},{"id":"2602.20951","title":"See and Fix the Flaws: Enabling VLMs and Diffusion Models to Comprehend Visual Artifacts via Agentic Data Synthesis","created":"2026-02-24","cited_by_count":1,"area":"diffusion"},{"id":"2603.00140","title":"Steering Away from Memorization: Reachability-Constrained Reinforcement Learning for Text-to-Image Diffusion","created":"2026-02-24","cited_by_count":1,"area":"diffusion"},{"id":"2603.02919","title":"Interpretable Motion-Attentive Maps: Spatio-Temporally Localizing Concepts in Video Diffusion Transformers","created":"2026-03-03","cited_by_count":1,"area":"diffusion"},{"id":"2603.22041","title":"DTVI: Dual-Stage Textual and Visual Intervention for Safe Text-to-Image Generation","created":"2026-03-23","cited_by_count":1,"area":"diffusion"},{"id":"2605.05026","title":"Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models","created":"2026-05-06","cited_by_count":1,"area":"diffusion"},{"id":"2606.06120","title":"Diff-CA: Separating Common and Salient Factors with Diffusion Models","created":"2026-06-04","cited_by_count":1,"area":"diffusion"},{"id":"2608.01624","title":"Not the Dimension, the Norm: What Matters in Gradient-Free Weight Perturbation of Language Models","created":"2026-08-03","cited_by_count":1,"area":null},{"id":"2608.23798","title":"A Theory of Speciation in Generative Diffusion Models on Compact Riemannian Manifolds","created":"2026-08-24","cited_by_count":1,"area":"diffusion"},{"id":"2408.01553","title":"Multi-task SAR Image Processing via GAN-based Unsupervised Manipulation","created":"2024-08-02","cited_by_count":0,"area":null},{"id":"2503.22782","title":"Patronus: Interpretable Diffusion Models with Prototypes","created":"2025-03-28","cited_by_count":0,"area":"diffusion"},{"id":"2504.15145","title":"\"I Know It When I See It\": Mood Spaces for Connecting and Expressing Visual Concepts","created":"2025-04-21","cited_by_count":0,"area":null},{"id":"2506.06826","title":"Controllable Coupled Image Generation via Diffusion Models","created":"2025-06-07","cited_by_count":0,"area":"diffusion"},{"id":"2506.09955","title":"Canonical Latent Representations in Conditional Diffusion Models","created":"2025-06-11","cited_by_count":0,"area":"diffusion"},{"id":"2506.13015","title":"Geometric Embedding Alignment via Curvature Matching in Transfer Learning","created":"2025-06-16","cited_by_count":0,"area":null},{"id":"2507.11986","title":"Style Composition within Distinct LoRA modules for Traditional Art","created":"2025-07-16","cited_by_count":0,"area":"diffusion"},{"id":"2509.22414","title":"LucidFlux: Caption-Free Photo-Realistic Image Restoration via a Large-Scale Diffusion Transformer","created":"2025-09-26","cited_by_count":0,"area":"diffusion"},{"id":"2510.01988","title":"PepCompass: Navigating peptide embedding spaces using Riemannian Geometry","created":"2025-10-02","cited_by_count":0,"area":null},{"id":"2510.15141","title":"Manifold Dimension Estimation via Local Graph Structure","created":"2025-10-16","cited_by_count":0,"area":null},{"id":"2510.22650","title":"Self-Attention Decomposition For Training Free Diffusion Editing","created":"2025-10-26","cited_by_count":0,"area":"diffusion"},{"id":"2511.08075","title":"CLIP is All You Need for Human-like Semantic Representations in Stable Diffusion","created":"2025-11-11","cited_by_count":0,"area":"diffusion"},{"id":"2511.18775","title":"Rethinking Garment Conditioning in Diffusion-based Virtual Try-On: Decouple, Don't Denoise","created":"2025-11-24","cited_by_count":0,"area":null},{"id":"2512.21104","title":"FreeInpaint: Tuning-free Prompt Alignment and Visual Rationality Enhancement in Image Inpainting","created":"2025-12-24","cited_by_count":0,"area":"diffusion"}],"next_cursor":"100"}