{"total":130,"rows":[{"id":"2306.03341","title":"Inference-Time Intervention: Eliciting Truthful Answers from a Language Model","created":"2023-06-06","cited_by_count":1302,"area":null},{"id":"2306.01708","title":"TIES-Merging: Resolving Interference When Merging Models","created":"2023-06-02","cited_by_count":818,"area":null},{"id":"2308.14761","title":"Unified Concept Editing in Diffusion Models","created":"2023-08-25","cited_by_count":388,"area":"diffusion"},{"id":"2303.11305","title":"SVDiff: Compact Parameter Space for Diffusion Fine-Tuning","created":"2023-03-20","cited_by_count":338,"area":"diffusion"},{"id":"2403.06135","title":"MACE: Mass Concept Erasure in Diffusion Models","created":"2024-03-10","cited_by_count":307,"area":"diffusion"},{"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":"2407.12383","title":"Reliable and Efficient Concept Erasure of Text-to-Image Diffusion Models","created":"2024-07-17","cited_by_count":133,"area":"diffusion"},{"id":"2410.12761","title":"SAFREE: Training-Free and Adaptive Guard for Safe Text-to-Image And Video Generation","created":"2024-10-16","cited_by_count":133,"area":"diffusion"},{"id":"2311.07604","title":"Finetuning Text-to-Image Diffusion Models for Fairness","created":"2023-11-11","cited_by_count":92,"area":"diffusion"},{"id":"2306.05414","title":"Improving Tuning-Free Real Image Editing with Proximal Guidance","created":"2023-06-08","cited_by_count":87,"area":"diffusion"},{"id":"2308.01508","title":"Circumventing Concept Erasure Methods For Text-to-Image Generative Models","created":"2023-08-03","cited_by_count":85,"area":null},{"id":"2410.02396","title":"Parameter Competition Balancing for Model Merging","created":"2024-10-03","cited_by_count":72,"area":null},{"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":"2404.01030","title":"Survey of Bias In Text-to-Image Generation: Definition, Evaluation, and Mitigation","created":"2024-04-01","cited_by_count":66,"area":null},{"id":"2405.19237","title":"ConceptPrune: Concept Editing in Diffusion Models via Skilled Neuron Pruning","created":"2024-05-29","cited_by_count":55,"area":"diffusion"},{"id":"2407.21035","title":"Direct Unlearning Optimization for Robust and Safe Text-to-Image Models","created":"2024-07-17","cited_by_count":50,"area":"safety"},{"id":"2410.15618","title":"Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation","created":"2024-10-21","cited_by_count":50,"area":"diffusion"},{"id":"2305.14330","title":"DirecT2V: Large Language Models are Frame-Level Directors for Zero-Shot Text-to-Video Generation","created":"2023-05-23","cited_by_count":49,"area":null},{"id":"2501.18950","title":"Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them","created":"2025-01-31","cited_by_count":37,"area":"diffusion"},{"id":"2503.07392","title":"SPEED: Scalable, Precise, and Efficient Concept Erasure for Diffusion Models","created":"2025-03-10","cited_by_count":36,"area":"diffusion"},{"id":"2407.15861","title":"Adversarial Attacks and Defenses on Text-to-Image Diffusion Models: A Survey","created":"2024-07-10","cited_by_count":35,"area":"diffusion"},{"id":"2503.12356","title":"Localized Concept Erasure for Text-to-Image Diffusion Models Using Training-Free Gated Low-Rank Adaptation","created":"2025-03-16","cited_by_count":33,"area":"diffusion"},{"id":"2306.00738","title":"ReFACT: Updating Text-to-Image Models by Editing the Text Encoder","created":"2023-06-01","cited_by_count":32,"area":null},{"id":"2311.17695","title":"Fair Text-to-Image Diffusion via Fair Mapping","created":"2023-11-29","cited_by_count":31,"area":"diffusion"},{"id":"2312.03849","title":"LEGO: Learning EGOcentric Action Frame Generation via Visual Instruction Tuning","created":"2023-12-06","cited_by_count":28,"area":"diffusion"},{"id":"2405.01008","title":"On Mechanistic Knowledge Localization in Text-to-Image Generative Models","created":"2024-05-02","cited_by_count":28,"area":null},{"id":"2505.12677","title":"CURE: Concept Unlearning via Orthogonal Representation Editing in Diffusion Models","created":"2025-05-19","cited_by_count":27,"area":"diffusion"},{"id":"2406.04551","title":"Improving Geo-diversity of Generated Images with Contextualized Vendi Score Guidance","created":"2024-06-06","cited_by_count":24,"area":null},{"id":"2408.12692","title":"Rethinking Training for De-biasing Text-to-Image Generation: Unlocking the Potential of Stable Diffusion","created":"2024-08-22","cited_by_count":22,"area":"diffusion"},{"id":"2412.10493","title":"AlignGuard: Scalable Safety Alignment for Text-to-Image Generation","created":"2024-12-13","cited_by_count":20,"area":"alignment"},{"id":"2406.01970","title":"The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise","created":"2024-06-04","cited_by_count":19,"area":"diffusion"},{"id":"2310.01819","title":"TP2O: Creative Text Pair-to-Object Generation using Balance Swap-Sampling","created":"2023-10-03","cited_by_count":16,"area":null},{"id":"2406.05191","title":"DiffusionPID: Interpreting Diffusion via Partial Information Decomposition","created":"2024-06-07","cited_by_count":16,"area":"diffusion"},{"id":"2412.15341","title":"Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models","created":"2024-12-19","cited_by_count":16,"area":"diffusion"},{"id":"2506.22806","title":"Concept Pinpoint Eraser for Text-to-image Diffusion Models via Residual Attention Gate","created":"2025-06-28","cited_by_count":16,"area":"diffusion"},{"id":"2403.13807","title":"Editing Massive Concepts in Text-to-Image Diffusion Models","created":"2024-03-20","cited_by_count":15,"area":"diffusion"},{"id":"2503.07389","title":"TRCE: Towards Reliable Malicious Concept Erasure in Text-to-Image Diffusion Models","created":"2025-03-10","cited_by_count":15,"area":"diffusion"},{"id":"2310.16781","title":"Kiki or Bouba? Sound Symbolism in Vision-and-Language Models","created":"2023-10-25","cited_by_count":14,"area":null},{"id":"2511.06876","title":"Generating an Image From 1,000 Words: Enhancing Text-to-Image With Structured Captions","created":"2025-11-10","cited_by_count":14,"area":null},{"id":"2403.02981","title":"Doubly Abductive Counterfactual Inference for Text-based Image Editing","created":"2024-03-05","cited_by_count":13,"area":null},{"id":"2412.01027","title":"Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation","created":"2024-12-02","cited_by_count":13,"area":null},{"id":"2406.15213","title":"Backdooring Bias ($B^2$) into Stable Diffusion Models","created":"2024-06-21","cited_by_count":12,"area":"diffusion"},{"id":"2410.20823","title":"Novel Object Synthesis via Adaptive Text-Image Harmony","created":"2024-10-28","cited_by_count":12,"area":null},{"id":"2501.09833","title":"Erasing More Than Intended? How Concept Erasure Degrades the Generation of Non-Target Concepts","created":"2025-01-16","cited_by_count":12,"area":null},{"id":"2305.17423","title":"Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference","created":"2023-05-27","cited_by_count":11,"area":"diffusion"},{"id":"2408.00001","title":"Replication in Visual Diffusion Models: A Survey and Outlook","created":"2024-07-07","cited_by_count":11,"area":"diffusion"},{"id":"2412.02542","title":"Unveiling Concept Attribution in Diffusion Models","created":"2024-12-03","cited_by_count":11,"area":"diffusion"},{"id":"2511.17282","title":"Where Culture Fades: Revealing the Cultural Gap in Text-to-Image Generation","created":"2025-11-21","cited_by_count":11,"area":null},{"id":"2403.19738","title":"MIST: Mitigating Intersectional Bias with Disentangled Cross-Attention Editing in Text-to-Image Diffusion Models","created":"2024-03-28","cited_by_count":10,"area":"diffusion"},{"id":"2408.14435","title":"Social Perception of Faces in a Vision-Language Model","created":"2024-08-26","cited_by_count":10,"area":"mllm"},{"id":"2505.08622","title":"Visually Guided Decoding: Gradient-Free Hard Prompt Inversion with Language Models","created":"2025-05-13","cited_by_count":10,"area":"diffusion"},{"id":"2507.07139","title":"Image Can Bring Your Memory Back: A Novel Multi-Modal Guided Attack against Image Generation Model Unlearning","created":"2025-07-09","cited_by_count":10,"area":"diffusion"},{"id":"2502.14896","title":"A Comprehensive Survey on Concept Erasure in Text-to-Image Diffusion Models","created":"2025-02-17","cited_by_count":9,"area":"diffusion"},{"id":"2504.21072","title":"Erased but Not Forgotten: How Backdoors Compromise Concept Erasure","created":"2025-04-29","cited_by_count":9,"area":"diffusion"},{"id":"2506.13298","title":"Fair Generation without Unfair Distortions: Debiasing Text-to-Image Generation with Entanglement-Free Attention","created":"2025-06-16","cited_by_count":9,"area":"diffusion"},{"id":"2601.06162","title":"Forget Many, Forget Right: Scalable and Precise Concept Unlearning in Diffusion Models","created":"2026-01-06","cited_by_count":9,"area":"diffusion"},{"id":"2305.14598","title":"Vision + Language Applications: A Survey","created":"2023-05-24","cited_by_count":8,"area":null},{"id":"2403.12326","title":"Hiding and Recovering Knowledge in Text-to-Image Diffusion Models via Learnable Prompts","created":"2024-03-18","cited_by_count":8,"area":"diffusion"},{"id":"2412.13341","title":"Concept-ROT: Poisoning Concepts in Large Language Models with Model Editing","created":"2024-12-17","cited_by_count":8,"area":null},{"id":"2412.18810","title":"FairGen: Enhancing Fairness in Text-to-Image Diffusion Models via Self-Discovering Latent Directions","created":"2024-12-25","cited_by_count":8,"area":"diffusion"},{"id":"2502.11798","title":"BackdoorDM: A Comprehensive Benchmark for Backdoor Learning on Diffusion Model","created":"2025-02-17","cited_by_count":8,"area":"diffusion"},{"id":"2503.09446","title":"Sparse Autoencoder as a Zero-Shot Classifier for Concept Erasing in Text-to-Image Diffusion Models","created":"2025-03-12","cited_by_count":8,"area":"diffusion"},{"id":"2408.17285","title":"Image-Perfect Imperfections: Safety, Bias, and Authenticity in the Shadow of Text-To-Image Model Evolution","created":"2024-08-30","cited_by_count":7,"area":"diffusion"},{"id":"2412.18123","title":"AEIOU: A Unified Defense Framework against NSFW Prompts in Text-to-Image Models","created":"2024-12-24","cited_by_count":7,"area":null},{"id":"2503.13994","title":"TarPro: Targeted Protection against Malicious Image Editing","created":"2025-03-18","cited_by_count":7,"area":null},{"id":"2510.21363","title":"FairImagen: Post-Processing for Bias Mitigation in Text-to-Image Models","created":"2025-10-24","cited_by_count":7,"area":"diffusion"},{"id":"2605.11161","title":"Interpretability Can Be Actionable","created":"2026-05-11","cited_by_count":7,"area":null},{"id":"2309.11745","title":"PIE: Simulating Disease Progression via Progressive Image Editing","created":"2023-09-21","cited_by_count":6,"area":null},{"id":"2509.21433","title":"DyME: Dynamic Multi-Concept Erasure in Diffusion Models with Bi-Level Orthogonal LoRA Adaptation","created":"2025-09-25","cited_by_count":6,"area":"diffusion"},{"id":"2305.18670","title":"SAVE: Spectral-Shift-Aware Adaptation of Image Diffusion Models for Text-driven Video Editing","created":"2023-05-30","cited_by_count":5,"area":"diffusion"},{"id":"2502.09935","title":"Precise Parameter Localization for Textual Generation in Diffusion Models","created":"2025-02-14","cited_by_count":5,"area":"diffusion"},{"id":"2503.18324","title":"Plug-and-Play Interpretable Responsible Text-to-Image Generation via Dual-Space Multi-facet Concept Control","created":"2025-03-24","cited_by_count":5,"area":null},{"id":"2602.06771","title":"AEGIS: Adversarial Target-Guided Retention-Data-Free Robust Concept Erasure from Diffusion Models","created":"2026-02-06","cited_by_count":5,"area":"diffusion"},{"id":"2412.07229","title":"Moderating the Generalization of Score-based Generative Model","created":"2024-12-10","cited_by_count":4,"area":"diffusion"},{"id":"2511.18684","title":"Now You See It, Now You Don't - Instant Concept Erasure for Safe Text-to-Image and Video Generation","created":"2025-11-24","cited_by_count":4,"area":"safety"},{"id":"2602.21977","title":"When LoRA Betrays: Backdooring Text-to-Image Models by Masquerading as Benign Adapters","created":"2026-02-25","cited_by_count":4,"area":"diffusion"},{"id":"2603.25994","title":"Neighbor-Aware Localized Concept Erasure in Text-to-Image Diffusion Models","created":"2026-03-27","cited_by_count":4,"area":"diffusion"},{"id":"2407.11104","title":"Exploring the Potentials and Challenges of Deep Generative Models in Product Design Conception","created":"2024-07-15","cited_by_count":3,"area":null},{"id":"2505.24023","title":"Multi-Group Proportional Representation for Text-to-Image Models","created":"2025-05-29","cited_by_count":3,"area":null},{"id":"2507.20973","title":"Model-Agnostic Gender Bias Control for Text-to-Image Generation via Sparse Autoencoder","created":"2025-07-28","cited_by_count":3,"area":"diffusion"},{"id":"2509.15257","title":"RespoDiff: Dual-Module Bottleneck Transformation for Responsible & Faithful T2I Generation","created":"2025-09-18","cited_by_count":3,"area":"diffusion"},{"id":"2512.03749","title":"Fully Unsupervised Self-debiasing of Text-to-Image Diffusion Models","created":"2025-12-03","cited_by_count":3,"area":"diffusion"},{"id":"2401.01414","title":"VALD-MD: Visual Attribution via Latent Diffusion for Medical Diagnostics","created":"2024-01-02","cited_by_count":2,"area":"diffusion"},{"id":"2405.16772","title":"Balancing User Preferences by Social Networks: A Condition-Guided Social Recommendation Model for Mitigating Popularity Bias","created":"2024-05-27","cited_by_count":2,"area":null},{"id":"2407.12579","title":"The Fabrication of Reality and Fantasy: Scene Generation with LLM-Assisted Prompt Interpretation","created":"2024-07-17","cited_by_count":2,"area":"diffusion"},{"id":"2509.21167","title":"A Unified Framework for Diffusion Model Unlearning with f-Divergence","created":"2025-09-25","cited_by_count":2,"area":"diffusion"},{"id":"2511.12968","title":"GrOCE:Graph-Guided Online Concept Erasure for Text-to-Image Diffusion Models","created":"2025-11-17","cited_by_count":2,"area":"diffusion"},{"id":"2511.13750","title":"SCALEX: Scalable Concept and Latent Exploration for Diffusion Models","created":"2025-11-13","cited_by_count":2,"area":"diffusion"},{"id":"2601.14330","title":"LURE: Latent Space Unblocking for Multi-Concept Reawakening in Diffusion Models","created":"2026-01-20","cited_by_count":2,"area":"diffusion"},{"id":"2604.06052","title":"Attention, May I Have Your Decision? Localizing Generative Choices in Diffusion Models","created":"2026-03-29","cited_by_count":2,"area":"diffusion"},{"id":"2605.28902","title":"Orthogonal Concept Erasure for Diffusion Models","created":"2026-05-27","cited_by_count":2,"area":"diffusion"},{"id":"2305.10079","title":"Face Recognition Using Synthetic Face Data","created":"2023-05-17","cited_by_count":1,"area":null},{"id":"2406.03683","title":"Bayesian Power Steering: An Effective Approach for Domain Adaptation of Diffusion Models","created":"2024-06-06","cited_by_count":1,"area":"diffusion"},{"id":"2412.03400","title":"Implicit Priors Editing in Stable Diffusion via Targeted Token Adjustment","created":"2024-12-04","cited_by_count":1,"area":"diffusion"},{"id":"2503.11742","title":"Safe Vision-Language Models via Unsafe Weights Manipulation","created":"2025-03-14","cited_by_count":1,"area":"mllm"},{"id":"2504.11104","title":"Using LLMs as prompt modifier to avoid biases in AI image generators","created":"2025-04-15","cited_by_count":1,"area":null},{"id":"2506.18428","title":"How Robust is Model Editing after Fine-Tuning? An Empirical Study on Text-to-Image Diffusion Models","created":"2025-06-23","cited_by_count":1,"area":"diffusion"},{"id":"2510.27285","title":"Rethinking Robust Adversarial Concept Erasure in Diffusion Models","created":"2025-10-31","cited_by_count":1,"area":"diffusion"},{"id":"2512.13427","title":"MineTheGap: Automatic Mining of Biases in Text-to-Image Models","created":"2025-12-15","cited_by_count":1,"area":null},{"id":"2603.06640","title":"Roots Beneath the Cut: Uncovering the Risk of Concept Revival in Pruning-Based Unlearning for Diffusion Models","created":"2026-02-28","cited_by_count":1,"area":"diffusion"}],"next_cursor":"100"}