{"total":37,"rows":[{"id":"2504.06256","title":"Transfer between Modalities with MetaQueries","created":"2025-04-08","cited_by_count":236,"area":null},{"id":"2503.07265","title":"WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation","created":"2025-03-10","cited_by_count":204,"area":null},{"id":"2410.05363","title":"Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation","created":"2024-10-07","cited_by_count":174,"area":null},{"id":"2506.07977","title":"OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation","created":"2025-06-09","cited_by_count":87,"area":null},{"id":"2505.02567","title":"Unified Multimodal Understanding and Generation Models: Advances, Challenges, and Opportunities","created":"2025-05-05","cited_by_count":85,"area":null},{"id":"2504.02782","title":"GPT-ImgEval: A Comprehensive Benchmark for Diagnosing GPT4o in Image Generation","created":"2025-04-03","cited_by_count":58,"area":null},{"id":"2509.03516","title":"Easier Painting Than Thinking: Can Text-to-Image Models Set the Stage, but Not Direct the Play?","created":"2025-09-03","cited_by_count":34,"area":null},{"id":"2505.23493","title":"R2I-Bench: Benchmarking Reasoning-Driven Text-to-Image Generation","created":"2025-05-29","cited_by_count":32,"area":null},{"id":"2509.14232","title":"GenExam: A Multidisciplinary Text-to-Image Exam","created":"2025-09-17","cited_by_count":22,"area":null},{"id":"2505.01490","title":"WorldGenBench: A World-Knowledge-Integrated Benchmark for Reasoning-Driven Text-to-Image Generation","created":"2025-05-02","cited_by_count":20,"area":null},{"id":"2505.19415","title":"MMIG-Bench: Towards Comprehensive and Explainable Evaluation of Multi-Modal Image Generation Models","created":"2025-05-26","cited_by_count":17,"area":null},{"id":"2504.13129","title":"Science-T2I: Addressing Scientific Illusions in Image Synthesis","created":"2025-04-17","cited_by_count":15,"area":null},{"id":"2412.04300","title":"T2I-FactualBench: Benchmarking the Factuality of Text-to-Image Models with Knowledge-Intensive Concepts","created":"2024-12-05","cited_by_count":14,"area":null},{"id":"2506.01955","title":"Dual-Process Image Generation","created":"2025-06-02","cited_by_count":12,"area":null},{"id":"2505.24870","title":"GenSpace: Benchmarking Spatially-Aware Image Generation","created":"2025-05-30","cited_by_count":9,"area":null},{"id":"2503.02341","title":"GRADEO: Towards Human-Like Evaluation for Text-to-Video Generation via Multi-Step Reasoning","created":"2025-03-04","cited_by_count":7,"area":null},{"id":"2602.08336","title":"UReason: Benchmarking Reasoning-to-Generation Alignment in Unified Multimodal Models","created":"2026-02-09","cited_by_count":7,"area":null},{"id":"2412.10604","title":"EvalGIM: A Library for Evaluating Generative Image Models","created":"2024-12-13","cited_by_count":5,"area":null},{"id":"2510.04201","title":"World-To-Image: Grounding Text-to-Image Generation with Agent-Driven World Knowledge","created":"2025-10-05","cited_by_count":5,"area":null},{"id":"2410.10291","title":"Evaluating Semantic Variation in Text-to-Image Synthesis: A Causal Perspective","created":"2024-10-14","cited_by_count":4,"area":null},{"id":"2504.08003","title":"Have we unified image generation and understanding yet? An empirical study of GPT-4o's image generation ability","created":"2025-04-09","cited_by_count":4,"area":null},{"id":"2511.18271","title":"Beyond Words and Pixels: A Benchmark for Implicit World Knowledge Reasoning in Generative Models","created":"2025-11-23","cited_by_count":4,"area":null},{"id":"2509.16107","title":"It Depends: Resolving Referential Ambiguity in Minimal Contexts with Commonsense Knowledge","created":"2025-09-19","cited_by_count":3,"area":null},{"id":"2510.20586","title":"GenColorBench: A Color Evaluation Benchmark for Text-to-Image Generation Models","created":"2025-10-23","cited_by_count":3,"area":null},{"id":"2602.00249","title":"SANEval: Open-Vocabulary Compositional Benchmarks with Failure-mode Diagnosis","created":"2026-01-30","cited_by_count":3,"area":null},{"id":"2410.03430","title":"Images Speak Volumes: User-Centric Assessment of Image Generation for Accessible Communication","created":"2024-10-04","cited_by_count":2,"area":null},{"id":"2512.01816","title":"Envision: Benchmarking Unified Understanding & Generation for Causal World Process Insights","created":"2025-12-01","cited_by_count":2,"area":null},{"id":"2505.18730","title":"Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation","created":"2025-05-24","cited_by_count":1,"area":null},{"id":"2510.00796","title":"MetaLogic: Robustness Evaluation of Text-to-Image Models via Logically Equivalent Prompts","created":"2025-10-01","cited_by_count":1,"area":null},{"id":"2601.00561","title":"AEGIS: Exploring the Limit of World Knowledge Capabilities for Unified Mulitmodal Models","created":"2026-01-02","cited_by_count":1,"area":null},{"id":"2606.26738","title":"Do Image Editing Models Understand Lighting?","created":"2026-06-25","cited_by_count":1,"area":null},{"id":"2609.00525","title":"GenScale: A Benchmark for Relative Object Scale in Image Generation and Editing","created":"2026-09-01","cited_by_count":1,"area":null},{"id":"2609.02864","title":"Thinking in Pictures: A Systematic Benchmark for Reasoning-driven Image Generation","created":"2026-09-02","cited_by_count":1,"area":null},{"id":"2505.02236","title":"Improving Physical Object State Representation in Text-to-Image Generative Systems","created":"2025-05-04","cited_by_count":0,"area":null},{"id":"2509.16141","title":"AcT2I: Evaluating and Improving Action Depiction in Text-to-Image Models","created":"2025-09-19","cited_by_count":0,"area":null},{"id":"2604.22302","title":"Knowledge Visualization: A Benchmark and Method for Knowledge-Intensive Text-to-Image Generation","created":"2026-04-24","cited_by_count":0,"area":null},{"id":"2610.12343","title":"Reasoning-Informed Visual Editing","created":"2026-10-08","cited_by_count":0,"area":null}],"next_cursor":null}