{"list":"other","total":55,"rows":[{"id":"2103.00020","title":"Learning Transferable Visual Models From Natural Language Supervision","created":"2021-02-26","cited_by_count":33744},{"id":"2006.11239","title":"Denoising Diffusion Probabilistic Models","created":"2020-06-19","cited_by_count":21076},{"id":"1505.04597","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","created":"2015-05-18","cited_by_count":19713},{"id":"2112.10752","title":"High-Resolution Image Synthesis with Latent Diffusion Models","created":"2021-12-20","cited_by_count":18863},{"id":"1910.10683","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","created":"2019-10-23","cited_by_count":14599},{"id":"2212.09748","title":"Scalable Diffusion Models with Transformers","created":"2022-12-19","cited_by_count":6054},{"id":"2403.03206","title":"Scaling Rectified Flow Transformers for High-Resolution Image Synthesis","created":"2024-03-05","cited_by_count":4181},{"id":"2112.10741","title":"GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models","created":"2021-12-20","cited_by_count":3614},{"id":"2208.01626","title":"Prompt-to-Prompt Image Editing with Cross Attention Control","created":"2022-08-02","cited_by_count":2431},{"id":"2104.08718","title":"CLIPScore: A Reference-free Evaluation Metric for Image Captioning","created":"2021-04-18","cited_by_count":2424},{"id":"2108.01073","title":"SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations","created":"2021-08-02","cited_by_count":1937},{"id":"1607.06520","title":"Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings","created":"2016-07-21","cited_by_count":1312},{"id":"1609.05807","title":"Inherent Trade-Offs in the Fair Determination of Risk Scores","created":"2016-09-19","cited_by_count":586},{"id":"2303.11897","title":"TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering","created":"2023-03-21","cited_by_count":428},{"id":"2308.14761","title":"Unified Concept Editing in Diffusion Models","created":"2023-08-25","cited_by_count":388},{"id":"1903.03862","title":"Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them","created":"2019-03-09","cited_by_count":268},{"id":"2211.03759","title":"Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale","created":"2022-11-07","cited_by_count":262},{"id":"2303.11408","title":"Stable Bias: Analyzing Societal Representations in Diffusion Models","created":"2023-03-20","cited_by_count":226},{"id":"2212.09611","title":"Optimizing Prompts for Text-to-Image Generation","created":"2022-12-19","cited_by_count":207},{"id":"2311.04287","title":"Holistic Evaluation of Text-To-Image Models","created":"2023-11-07","cited_by_count":160},{"id":"2311.12092","title":"Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models","created":"2023-11-20","cited_by_count":153},{"id":"1803.04585","title":"Categorizing Variants of Goodhart's Law","created":"2018-03-13","cited_by_count":149},{"id":"2302.00070","title":"Debiasing Vision-Language Models via Biased Prompts","created":"2023-01-31","cited_by_count":149},{"id":"2304.06034","title":"Social Biases through the Text-to-Image Generation Lens","created":"2023-03-30","cited_by_count":127},{"id":"1808.00023","title":"The Measure and Mismeasure of Fairness","created":"2018-07-31","cited_by_count":95},{"id":"2304.05390","title":"HRS-Bench: Holistic, Reliable and Scalable Benchmark for Text-to-Image Models","created":"2023-04-11","cited_by_count":95},{"id":"2311.07604","title":"Finetuning Text-to-Image Diffusion Models for Fairness","created":"2023-11-11","cited_by_count":92},{"id":"2308.00755","title":"The Bias Amplification Paradox in Text-to-Image Generation","created":"2023-08-01","cited_by_count":70},{"id":"2404.01030","title":"Survey of Bias In Text-to-Image Generation: Definition, Evaluation, and Mitigation","created":"2024-04-01","cited_by_count":66},{"id":"2309.05569","title":"ITI-GEN: Inclusive Text-to-Image Generation","created":"2023-09-11","cited_by_count":64},{"id":"2404.07990","title":"OpenBias: Open-set Bias Detection in Text-to-Image Generative Models","created":"2024-04-11","cited_by_count":61},{"id":"2305.11844","title":"AI's Regimes of Representation: A Community-centered Study of Text-to-Image Models in South Asia","created":"2023-05-19","cited_by_count":54},{"id":"2306.12424","title":"VisoGender: A dataset for benchmarking gender bias in image-text pronoun resolution","created":"2023-06-21","cited_by_count":52},{"id":"2402.18206","title":"Balancing Act: Distribution-Guided Debiasing in Diffusion Models","created":"2024-02-28","cited_by_count":52},{"id":"2501.12612","title":"T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation","created":"2025-01-22","cited_by_count":48},{"id":"2305.06402","title":"Analyzing Bias in Diffusion-based Face Generation Models","created":"2023-05-10","cited_by_count":46},{"id":"2306.00905","title":"T2IAT: Measuring Valence and Stereotypical Biases in Text-to-Image Generation","created":"2023-06-01","cited_by_count":39},{"id":"2311.17695","title":"Fair Text-to-Image Diffusion via Fair Mapping","created":"2023-11-29","cited_by_count":31},{"id":"2407.14779","title":"Do Generative AI Models Output Harm while Representing Non-Western Cultures: Evidence from A Community-Centered Approach","created":"2024-07-20","cited_by_count":26},{"id":"2404.03242","title":"Would Deep Generative Models Amplify Bias in Future Models?","created":"2024-04-04","cited_by_count":24},{"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},{"id":"2305.10566","title":"Smiling Women Pitching Down: Auditing Representational and Presentational Gender Biases in Image Generative AI","created":"2023-05-17","cited_by_count":19},{"id":"2408.10202","title":"SANER: Annotation-free Societal Attribute Neutralizer for Debiasing CLIP","created":"2024-08-19","cited_by_count":19},{"id":"2402.01002","title":"AI-generated faces influence gender stereotypes and racial homogenization","created":"2024-02-01","cited_by_count":14},{"id":"2410.18615","title":"FairQueue: Rethinking Prompt Learning for Fair Text-to-Image Generation","created":"2024-10-24","cited_by_count":7},{"id":"2503.01872","title":"FairGen: Controlling Sensitive Attributes for Fair Generations in Diffusion Models via Adaptive Latent Guidance","created":"2025-02-25","cited_by_count":7},{"id":"2407.19524","title":"VersusDebias: Universal Zero-Shot Debiasing for Text-to-Image Models via SLM-Based Prompt Engineering and Generative Adversary","created":"2024-07-28","cited_by_count":6},{"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},{"id":"2501.15775","title":"Do Existing Testing Tools Really Uncover Gender Bias in Text-to-Image Models?","created":"2025-01-27","cited_by_count":4},{"id":"2503.10037","title":"Role Bias in Diffusion Models: Diagnosing and Mitigating through Intermediate Decomposition","created":"2025-03-13","cited_by_count":4},{"id":"2505.17560","title":"Deeper Diffusion Models Amplify Bias","created":"2025-05-23","cited_by_count":4},{"id":"2505.24023","title":"Multi-Group Proportional Representation for Text-to-Image Models","created":"2025-05-29","cited_by_count":3},{"id":"2404.16663","title":"Runtime Monitoring and Enforcement of Conditional Fairness in Generative AIs","created":"2024-04-25","cited_by_count":2},{"id":"2501.01973","title":"INFELM: In-depth Fairness Evaluation of Large Text-To-Image Models","created":"2024-12-28","cited_by_count":1},{"id":"2506.10586","title":"Size-adaptive Hypothesis Testing for Fairness","created":"2025-06-12","cited_by_count":1}],"next_cursor":null}