{"list":"other","total":61,"rows":[{"id":"2103.00020","title":"Learning Transferable Visual Models From Natural Language Supervision","created":"2021-02-26","cited_by_count":33744},{"id":"1505.04597","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","created":"2015-05-18","cited_by_count":19713},{"id":"2106.09685","title":"LoRA: Low-Rank Adaptation of Large Language Models","created":"2021-06-17","cited_by_count":14380},{"id":"2103.14030","title":"Swin Transformer: Hierarchical Vision Transformer using Shifted Windows","created":"2021-03-25","cited_by_count":12139},{"id":"2501.12948","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","created":"2025-01-22","cited_by_count":6330},{"id":"2301.12597","title":"BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models","created":"2023-01-30","cited_by_count":6137},{"id":"2502.13923","title":"Qwen2.5-VL Technical Report","created":"2025-02-19","cited_by_count":5587},{"id":"1603.02754","title":"XGBoost: A Scalable Tree Boosting System","created":"2016-03-09","cited_by_count":5166},{"id":"2201.12086","title":"BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation","created":"2022-01-28","cited_by_count":4322},{"id":"2408.03326","title":"LLaVA-OneVision: Easy Visual Task Transfer","created":"2024-08-06","cited_by_count":2719},{"id":"2412.05271","title":"Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling","created":"2024-12-06","cited_by_count":1599},{"id":"2502.14786","title":"SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features","created":"2025-02-20","cited_by_count":1188},{"id":"2304.05977","title":"ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation","created":"2023-04-12","cited_by_count":1045},{"id":"2305.01569","title":"Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation","created":"2023-05-02","cited_by_count":977},{"id":"2211.07636","title":"EVA: Exploring the Limits of Masked Visual Representation Learning at Scale","created":"2022-11-14","cited_by_count":691},{"id":"2412.10302","title":"DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding","created":"2024-12-13","cited_by_count":572},{"id":"2311.04257","title":"mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration","created":"2023-11-07","cited_by_count":547},{"id":"2204.08958","title":"MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment","created":"2022-04-19","cited_by_count":522},{"id":"2312.17090","title":"Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels","created":"2023-12-28","cited_by_count":503},{"id":"2404.01291","title":"Evaluating Text-to-Visual Generation with Image-to-Text Generation","created":"2024-04-01","cited_by_count":474},{"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":"2311.06242","title":"Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks","created":"2023-11-10","cited_by_count":410},{"id":"2210.14896","title":"DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Models","created":"2022-10-26","cited_by_count":379},{"id":"1907.02665","title":"Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network","created":"2019-07-05","cited_by_count":302},{"id":"2303.14420","title":"Human Preference Score: Better Aligning Text-to-Image Models with Human Preference","created":"2023-03-25","cited_by_count":287},{"id":"2303.14968","title":"Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective","created":"2023-03-27","cited_by_count":280},{"id":"2211.12860","title":"DETRs with Collaborative Hybrid Assignments Training","created":"2022-11-22","cited_by_count":274},{"id":"2503.05236","title":"Unified Reward Model for Multimodal Understanding and Generation","created":"2025-03-07","cited_by_count":199},{"id":"2406.19435","title":"A Sanity Check for AI-generated Image Detection","created":"2024-06-27","cited_by_count":189},{"id":"2405.20797","title":"Ovis: Structural Embedding Alignment for Multimodal Large Language Model","created":"2024-05-31","cited_by_count":169},{"id":"2306.04717","title":"AGIQA-3K: An Open Database for AI-Generated Image Quality Assessment","created":"2023-06-07","cited_by_count":142},{"id":"2312.10240","title":"Rich Human Feedback for Text-to-Image Generation","created":"2023-12-15","cited_by_count":141},{"id":"2501.11561","title":"Teaching Large Language Models to Regress Accurate Image Quality Scores using Score Distribution","created":"2025-01-20","cited_by_count":141},{"id":"2406.13743","title":"GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation","created":"2024-06-19","cited_by_count":135},{"id":"2211.06679","title":"AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities","created":"2022-11-12","cited_by_count":85},{"id":"2105.14550","title":"Blind Quality Assessment for in-the-Wild Images via Hierarchical Feature Fusion and Iterative Mixed Database Training","created":"2021-05-30","cited_by_count":71},{"id":"2408.08870","title":"SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation","created":"2024-08-16","cited_by_count":64},{"id":"2307.00211","title":"AIGCIQA2023: A Large-scale Image Quality Assessment Database for AI Generated Images: from the Perspectives of Quality, Authenticity and Correspondence","created":"2023-07-01","cited_by_count":61},{"id":"2404.10343","title":"The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report","created":"2024-04-16","cited_by_count":57},{"id":"2303.12618","title":"A Perceptual Quality Assessment Exploration for AIGC Images","created":"2023-03-22","cited_by_count":55},{"id":"2404.16820","title":"Revisiting Text-to-Image Evaluation with Gecko: On Metrics, Prompts, and Human Ratings","created":"2024-04-25","cited_by_count":44},{"id":"2404.09790","title":"NTIRE 2024 Challenge on Image Super-Resolution (x4): Methods and Results","created":"2024-04-15","cited_by_count":40},{"id":"2412.18150","title":"EvalMuse-40K: A Reliable and Fine-Grained Benchmark with Comprehensive Human Annotations for Text-to-Image Generation Model Evaluation","created":"2024-12-24","cited_by_count":39},{"id":"2404.03407","title":"AIGIQA-20K: A Large Database for AI-Generated Image Quality Assessment","created":"2024-04-04","cited_by_count":33},{"id":"2404.11313","title":"NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and Results","created":"2024-04-17","cited_by_count":29},{"id":"2504.10686","title":"The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report","created":"2025-04-14","cited_by_count":26},{"id":"2504.10685","title":"NTIRE 2025 Challenge on Cross-Domain Few-Shot Object Detection: Methods and Results","created":"2025-04-14","cited_by_count":25},{"id":"2504.12711","title":"NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results","created":"2025-04-17","cited_by_count":22},{"id":"2504.12276","title":"The Tenth NTIRE 2025 Image Denoising Challenge Report","created":"2025-04-16","cited_by_count":21},{"id":"2103.03451","title":"Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy Labels","created":"2021-03-05","cited_by_count":20},{"id":"2504.12401","title":"NTIRE 2025 Challenge on Event-Based Image Deblurring: Methods and Results","created":"2025-04-16","cited_by_count":16},{"id":"2403.04993","title":"PromptIQA: Boosting the Performance and Generalization for No-Reference Image Quality Assessment via Prompts","created":"2024-03-08","cited_by_count":14},{"id":"2504.13131","title":"NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results","created":"2025-04-17","cited_by_count":14},{"id":"2505.12089","title":"NTIRE 2025 Challenge on Efficient Burst HDR and Restoration: Datasets, Methods, and Results","created":"2025-05-17","cited_by_count":14},{"id":"2411.10161","title":"SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning","created":"2024-11-15","cited_by_count":13},{"id":"2504.14582","title":"NTIRE 2025 Challenge on Image Super-Resolution (x4): Methods and Results","created":"2025-04-20","cited_by_count":12},{"id":"2505.03007","title":"NTIRE 2025 Challenge on UGC Video Enhancement: Methods and Results","created":"2025-05-05","cited_by_count":12},{"id":"2504.15003","title":"NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: KwaiSR Dataset and Study","created":"2025-04-21","cited_by_count":11},{"id":"2504.14600","title":"NTIRE 2025 Challenge on Real-World Face Restoration: Methods and Results","created":"2025-04-20","cited_by_count":10},{"id":"2504.07556","title":"TokenFocus-VQA: Enhancing Text-to-Image Alignment with Position-Aware Focus and Multi-Perspective Aggregations on LVLMs","created":"2025-04-10","cited_by_count":2},{"id":"2504.12018","title":"Instruction-augmented Multimodal Alignment for Image-Text and Element Matching","created":"2025-04-16","cited_by_count":2}],"next_cursor":null}