{"total":226,"rows":[{"id":"2308.14761","title":"Unified Concept Editing in Diffusion Models","created":"2023-08-25","cited_by_count":388,"area":"diffusion"},{"id":"2306.16527","title":"OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents","created":"2023-06-21","cited_by_count":316,"area":"mllm"},{"id":"2305.13655","title":"LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models","created":"2023-05-23","cited_by_count":243,"area":"diffusion"},{"id":"2310.11986","title":"Sociotechnical Safety Evaluation of Generative AI Systems","created":"2023-10-18","cited_by_count":157,"area":null},{"id":"2306.04141","title":"Art and the science of generative AI: A deeper dive","created":"2023-06-07","cited_by_count":95,"area":null},{"id":"2311.07604","title":"Finetuning Text-to-Image Diffusion Models for Fairness","created":"2023-11-11","cited_by_count":92,"area":"diffusion"},{"id":"2401.15897","title":"Red-Teaming for Generative AI: Silver Bullet or Security Theater?","created":"2024-01-29","cited_by_count":83,"area":"safety"},{"id":"2401.12244","title":"Large-scale Reinforcement Learning for Diffusion Models","created":"2024-01-20","cited_by_count":78,"area":"diffusion"},{"id":"2404.05399","title":"SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety","created":"2024-04-08","cited_by_count":77,"area":"safety"},{"id":"2308.00755","title":"The Bias Amplification Paradox in Text-to-Image Generation","created":"2023-08-01","cited_by_count":70,"area":null},{"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":"2401.12915","title":"Red Teaming Visual Language Models","created":"2024-01-23","cited_by_count":65,"area":"mllm"},{"id":"2309.05569","title":"ITI-GEN: Inclusive Text-to-Image Generation","created":"2023-09-11","cited_by_count":64,"area":null},{"id":"2306.04542","title":"On the Design Fundamentals of Diffusion Models: A Survey","created":"2023-06-07","cited_by_count":60,"area":"diffusion"},{"id":"2401.14484","title":"Design Principles for Generative AI Applications","created":"2024-01-25","cited_by_count":57,"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":"2406.08469","title":"PAL: Pluralistic Alignment Framework for Learning from Heterogeneous Preferences","created":"2024-06-12","cited_by_count":54,"area":"alignment"},{"id":"2306.12424","title":"VisoGender: A dataset for benchmarking gender bias in image-text pronoun resolution","created":"2023-06-21","cited_by_count":52,"area":"mllm"},{"id":"2312.01261","title":"TIBET: Identifying and Evaluating Biases in Text-to-Image Generative Models","created":"2023-12-03","cited_by_count":52,"area":null},{"id":"2402.18206","title":"Balancing Act: Distribution-Guided Debiasing in Diffusion Models","created":"2024-02-28","cited_by_count":52,"area":"diffusion"},{"id":"2305.18286","title":"Photoswap: Personalized Subject Swapping in Images","created":"2023-05-29","cited_by_count":47,"area":null},{"id":"2403.01633","title":"Critical windows: non-asymptotic theory for feature emergence in diffusion models","created":"2024-03-03","cited_by_count":47,"area":"diffusion"},{"id":"2305.06402","title":"Analyzing Bias in Diffusion-based Face Generation Models","created":"2023-05-10","cited_by_count":46,"area":"diffusion"},{"id":"2305.11080","title":"Inspecting the Geographical Representativeness of Images from Text-to-Image Models","created":"2023-05-18","cited_by_count":44,"area":"diffusion"},{"id":"2312.06205","title":"The Journey, Not the Destination: How Data Guides Diffusion Models","created":"2023-12-11","cited_by_count":43,"area":"diffusion"},{"id":"2307.05977","title":"Towards Safe Self-Distillation of Internet-Scale Text-to-Image Diffusion Models","created":"2023-07-12","cited_by_count":41,"area":"diffusion"},{"id":"2312.14223","title":"Fast Diffusion-Based Counterfactuals for Shortcut Removal and Generation","created":"2023-12-21","cited_by_count":41,"area":null},{"id":"2309.14356","title":"COCO-Counterfactuals: Automatically Constructed Counterfactual Examples for Image-Text Pairs","created":"2023-09-23","cited_by_count":39,"area":null},{"id":"2306.00966","title":"The Hidden Language of Diffusion Models","created":"2023-06-01","cited_by_count":34,"area":"diffusion"},{"id":"2403.19964","title":"FairRAG: Fair Human Generation via Fair Retrieval Augmentation","created":"2024-03-29","cited_by_count":34,"area":null},{"id":"2310.00158","title":"Feedback-guided Data Synthesis for Imbalanced Classification","created":"2023-09-29","cited_by_count":33,"area":"synth"},{"id":"2310.19981","title":"'Person' == Light-skinned, Western Man, and Sexualization of Women of Color: Stereotypes in Stable Diffusion","created":"2023-10-30","cited_by_count":33,"area":"diffusion"},{"id":"2407.03471","title":"Learning Action and Reasoning-Centric Image Editing from Videos and Simulations","created":"2024-07-03","cited_by_count":32,"area":null},{"id":"2407.00600","title":"GenderBias-\\emph{VL}: Benchmarking Gender Bias in Vision Language Models via Counterfactual Probing","created":"2024-06-30","cited_by_count":31,"area":"mllm"},{"id":"2407.06863","title":"Beyond Aesthetics: Cultural Competence in Text-to-Image Models","created":"2024-07-09","cited_by_count":30,"area":null},{"id":"2405.13581","title":"Safety Alignment for Vision Language Models","created":"2024-05-22","cited_by_count":28,"area":"mllm"},{"id":"2305.15407","title":"Balancing the Picture: Debiasing Vision-Language Datasets with Synthetic Contrast Sets","created":"2023-05-24","cited_by_count":27,"area":"mllm"},{"id":"2401.06310","title":"ViSAGe: A Global-Scale Analysis of Visual Stereotypes in Text-to-Image Generation","created":"2024-01-12","cited_by_count":27,"area":null},{"id":"2411.00997","title":"Identifying Implicit Social Biases in Vision-Language Models","created":"2024-11-01","cited_by_count":27,"area":"mllm"},{"id":"2312.03027","title":"Stable Diffusion Exposed: Gender Bias from Prompt to Image","created":"2023-12-05","cited_by_count":25,"area":"diffusion"},{"id":"2412.07951","title":"From Lived Experience to Insight: Unpacking the Psychological Risks of Using AI Conversational Agents","created":"2024-12-10","cited_by_count":25,"area":null},{"id":"2404.03242","title":"Would Deep Generative Models Amplify Bias in Future Models?","created":"2024-04-04","cited_by_count":24,"area":null},{"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":"2404.11023","title":"Advancing Social Intelligence in AI Agents: Technical Challenges and Open Questions","created":"2024-04-17","cited_by_count":22,"area":null},{"id":"2405.17814","title":"FAIntbench: A Holistic and Precise Benchmark for Bias Evaluation in Text-to-Image Models","created":"2024-05-28","cited_by_count":22,"area":null},{"id":"2408.15094","title":"Constrained Diffusion Models via Dual Training","created":"2024-08-27","cited_by_count":20,"area":"diffusion"},{"id":"2307.10159","title":"FABRIC: Personalizing Diffusion Models with Iterative Feedback","created":"2023-07-19","cited_by_count":19,"area":"diffusion"},{"id":"2310.06904","title":"Mitigating stereotypical biases in text to image generative systems","created":"2023-10-10","cited_by_count":19,"area":null},{"id":"2401.08053","title":"SCoFT: Self-Contrastive Fine-Tuning for Equitable Image Generation","created":"2024-01-16","cited_by_count":19,"area":null},{"id":"2404.14068","title":"Holistic Safety and Responsibility Evaluations of Advanced AI Models","created":"2024-04-22","cited_by_count":19,"area":null},{"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":"2409.08400","title":"Scores as Actions: a framework of fine-tuning diffusion models by continuous-time reinforcement learning","created":"2024-09-12","cited_by_count":19,"area":"diffusion"},{"id":"2402.01708","title":"Not My Voice! A Taxonomy of Ethical and Safety Harms of Speech Generators","created":"2024-01-25","cited_by_count":18,"area":null},{"id":"2407.07875","title":"Generative Image as Action Models","created":"2024-07-10","cited_by_count":18,"area":"diffusion"},{"id":"2310.06668","title":"Latent Diffusion Counterfactual Explanations","created":"2023-10-10","cited_by_count":17,"area":"diffusion"},{"id":"2402.10404","title":"Explaining generative diffusion models via visual analysis for interpretable decision-making process","created":"2024-02-16","cited_by_count":17,"area":"diffusion"},{"id":"2411.04420","title":"BendVLM: Test-Time Debiasing of Vision-Language Embeddings","created":"2024-11-07","cited_by_count":17,"area":"mllm"},{"id":"2312.13053","title":"Quantifying Bias in Text-to-Image Generative Models","created":"2023-12-20","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":"2410.12138","title":"Preference Optimization with Multi-Sample Comparisons","created":"2024-10-16","cited_by_count":16,"area":"diffusion"},{"id":"2401.16092","title":"Multilingual Text-to-Image Generation Magnifies Gender Stereotypes and Prompt Engineering May Not Help You","created":"2024-01-29","cited_by_count":15,"area":null},{"id":"2402.01787","title":"Harm Amplification in Text-to-Image Models","created":"2024-02-01","cited_by_count":15,"area":null},{"id":"2403.13807","title":"Editing Massive Concepts in Text-to-Image Diffusion Models","created":"2024-03-20","cited_by_count":15,"area":"diffusion"},{"id":"2405.08209","title":"Who's in and who's out? A case study of multimodal CLIP-filtering in DataComp","created":"2024-05-13","cited_by_count":15,"area":null},{"id":"2410.19314","title":"Revealing and Reducing Gender Biases in Vision and Language Assistants (VLAs)","created":"2024-10-25","cited_by_count":15,"area":null},{"id":"2402.16268","title":"Foundation Model Transparency Reports","created":"2024-02-26","cited_by_count":14,"area":null},{"id":"2502.11989","title":"Characterizing Photorealism and Artifacts in Diffusion Model-Generated Images","created":"2025-02-17","cited_by_count":14,"area":"diffusion"},{"id":"2503.23398","title":"A Large Scale Analysis of Gender Biases in Text-to-Image Generative Models","created":"2025-03-30","cited_by_count":14,"area":null},{"id":"2403.02580","title":"What do we learn from inverting CLIP models?","created":"2024-03-05","cited_by_count":13,"area":null},{"id":"2403.10776","title":"From Melting Pots to Misrepresentations: Exploring Harms in Generative AI","created":"2024-03-16","cited_by_count":13,"area":null},{"id":"2405.08597","title":"Risks and Opportunities of Open-Source Generative AI","created":"2024-05-14","cited_by_count":13,"area":null},{"id":"2406.18566","title":"Memorized Images in Diffusion Models share a Subspace that can be Located and Deleted","created":"2024-06-01","cited_by_count":13,"area":"diffusion"},{"id":"2408.02464","title":"Fairness and Bias Mitigation in Computer Vision: A Survey","created":"2024-08-05","cited_by_count":13,"area":null},{"id":"2507.13386","title":"Minimalist Concept Erasure in Generative Models","created":"2025-07-16","cited_by_count":13,"area":null},{"id":"2307.12980","title":"A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models","created":"2023-07-24","cited_by_count":12,"area":"mllm"},{"id":"2404.13706","title":"Concept Arithmetics for Circumventing Concept Inhibition in Diffusion Models","created":"2024-04-21","cited_by_count":12,"area":"diffusion"},{"id":"2406.15213","title":"Backdooring Bias ($B^2$) into Stable Diffusion Models","created":"2024-06-21","cited_by_count":12,"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":"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":"2311.12229","title":"NeuroPrompts: An Adaptive Framework to Optimize Prompts for Text-to-Image Generation","created":"2023-11-20","cited_by_count":10,"area":"diffusion"},{"id":"2402.14577","title":"Debiasing Text-to-Image Diffusion Models","created":"2024-02-22","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":"2502.21318","title":"How far can we go with ImageNet for Text-to-Image generation?","created":"2025-02-28","cited_by_count":10,"area":null},{"id":"2308.06198","title":"DIG In: Evaluating Disparities in Image Generations with Indicators for Geographic Diversity","created":"2023-08-11","cited_by_count":9,"area":null},{"id":"2311.12573","title":"Moderating Model Marketplaces: Platform Governance Puzzles for AI Intermediaries","created":"2023-11-21","cited_by_count":9,"area":null},{"id":"2503.08012","title":"Exploring Bias in over 100 Text-to-Image Generative Models","created":"2025-03-11","cited_by_count":9,"area":null},{"id":"2501.00962","title":"OASIS Uncovers: High-Quality T2I Models, Same Old Stereotypes","created":"2025-01-01","cited_by_count":8,"area":null},{"id":"2503.01145","title":"CoInD: Enabling Logical Compositions in Diffusion Models","created":"2025-03-03","cited_by_count":8,"area":"diffusion"},{"id":"2307.08025","title":"Analysing Gender Bias in Text-to-Image Models using Object Detection","created":"2023-07-16","cited_by_count":7,"area":null},{"id":"2309.06364","title":"Framework-Based Qualitative Analysis of Free Responses of Large Language Models: Algorithmic Fidelity","created":"2023-09-06","cited_by_count":7,"area":null},{"id":"2311.17315","title":"Explaining CLIP's performance disparities on data from blind/low vision users","created":"2023-11-29","cited_by_count":7,"area":"mllm"},{"id":"2312.10065","title":"Exploring Social Bias in Downstream Applications of Text-to-Image Foundation Models","created":"2023-12-05","cited_by_count":7,"area":"diffusion"},{"id":"2406.14599","title":"Stylebreeder: Exploring and Democratizing Artistic Styles through Text-to-Image Models","created":"2024-06-20","cited_by_count":7,"area":null},{"id":"2407.01561","title":"Synthetic Data in Radiological Imaging: Current State and Future Outlook","created":"2024-05-08","cited_by_count":7,"area":null},{"id":"2407.03623","title":"Resampled Datasets Are Not Enough: Mitigating Societal Bias Beyond Single Attributes","created":"2024-07-04","cited_by_count":7,"area":null},{"id":"2408.08307","title":"What Secrets Do Your Manifolds Hold? Understanding the Local Geometry of Generative Models","created":"2024-08-15","cited_by_count":7,"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":"2502.16902","title":"Culture-TRIP: Culturally-Aware Text-to-Image Generation with Iterative Prompt Refinement","created":"2025-02-24","cited_by_count":7,"area":"diffusion"},{"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":"2404.17255","title":"SDFD: Building a Versatile Synthetic Face Image Dataset with Diverse Attributes","created":"2024-04-26","cited_by_count":6,"area":null}],"next_cursor":"100"}