{"total":45,"rows":[{"id":"2305.17216","title":"Generating Images with Multimodal Language Models","created":"2023-05-26","cited_by_count":260,"area":"mllm"},{"id":"2307.00716","title":"JourneyDB: A Benchmark for Generative Image Understanding","created":"2023-07-03","cited_by_count":205,"area":"mllm"},{"id":"2309.17102","title":"Guiding Instruction-based Image Editing via Multimodal Large Language Models","created":"2023-09-29","cited_by_count":185,"area":"mllm"},{"id":"2308.06038","title":"Diverse Data Augmentation with Diffusions for Effective Test-time Prompt Tuning","created":"2023-08-11","cited_by_count":154,"area":"mllm"},{"id":"2408.01319","title":"A Comprehensive Review of Multimodal Large Language Models: Performance and Challenges Across Different Tasks","created":"2024-08-02","cited_by_count":57,"area":"mllm"},{"id":"2307.07397","title":"Improving Zero-Shot Generalization for CLIP with Synthesized Prompts","created":"2023-07-14","cited_by_count":51,"area":"mllm"},{"id":"2310.08475","title":"Can We Edit Multimodal Large Language Models?","created":"2023-10-12","cited_by_count":44,"area":"mllm"},{"id":"2510.08485","title":"InstructX: Towards Unified Visual Editing with MLLM Guidance","created":"2025-10-09","cited_by_count":32,"area":"mllm"},{"id":"2402.10805","title":"Generative Cross-Modal Retrieval: Memorizing Images in Multimodal Language Models for Retrieval and Beyond","created":"2024-02-16","cited_by_count":28,"area":"mllm"},{"id":"2410.23687","title":"Adversarial Attacks of Vision Tasks in the Past 10 Years: A Survey","created":"2024-10-31","cited_by_count":23,"area":"mllm"},{"id":"2503.10127","title":"PlanGen: Towards Unified Layout Planning and Image Generation in Auto-Regressive Vision Language Models","created":"2025-03-13","cited_by_count":18,"area":"mllm"},{"id":"2408.16647","title":"DriveGenVLM: Real-world Video Generation for Vision Language Model based Autonomous Driving","created":"2024-08-29","cited_by_count":11,"area":"mllm"},{"id":"2506.07227","title":"Hallucination at a Glance: Controlled Visual Edits and Fine-Grained Multimodal Learning","created":"2025-06-08","cited_by_count":11,"area":"mllm"},{"id":"2212.07398","title":"Policy Adaptation from Foundation Model Feedback","created":"2022-12-14","cited_by_count":10,"area":"mllm"},{"id":"2507.21391","title":"Multimodal LLMs as Customized Reward Models for Text-to-Image Generation","created":"2025-07-28","cited_by_count":10,"area":"mllm"},{"id":"2407.20657","title":"Prompt-Driven Contrastive Learning for Transferable Adversarial Attacks","created":"2024-07-30","cited_by_count":9,"area":"mllm"},{"id":"2408.06569","title":"Social Debiasing for Fair Multi-modal LLMs","created":"2024-08-13","cited_by_count":8,"area":"mllm"},{"id":"2409.14993","title":"Multi-modal Generative AI: Multi-modal LLMs, Diffusions, and the Unification","created":"2024-09-23","cited_by_count":8,"area":"mllm"},{"id":"2604.28123","title":"Beyond SFT-to-RL: Pre-alignment via Black-Box On-Policy Distillation for Multimodal RL","created":"2026-04-30","cited_by_count":8,"area":"mllm"},{"id":"2210.13591","title":"Learning by Hallucinating: Vision-Language Pre-training with Weak Supervision","created":"2022-10-24","cited_by_count":6,"area":"mllm"},{"id":"2212.02936","title":"M-VADER: A Model for Diffusion with Multimodal Context","created":"2022-12-06","cited_by_count":6,"area":"mllm"},{"id":"2408.02231","title":"REVISION: Rendering Tools Enable Spatial Fidelity in Vision-Language Models","created":"2024-08-05","cited_by_count":6,"area":"mllm"},{"id":"2509.13760","title":"Iterative Prompt Refinement for Safer Text-to-Image Generation","created":"2025-09-17","cited_by_count":6,"area":"mllm"},{"id":"2312.02233","title":"MedXChat: A Unified Multimodal Large Language Model Framework towards CXRs Understanding and Generation","created":"2023-12-04","cited_by_count":5,"area":"mllm"},{"id":"2503.10665","title":"Small Vision-Language Models: A Survey on Compact Architectures and Techniques","created":"2025-03-09","cited_by_count":4,"area":"mllm"},{"id":"2509.08490","title":"A Structured Review of Underwater Object Detection Challenges and Solutions: From Traditional to Large Vision Language Models","created":"2025-09-10","cited_by_count":4,"area":"mllm"},{"id":"2309.16552","title":"Semantic Scene Difference Detection in Daily Life Patroling by Mobile Robots using Pre-Trained Large-Scale Vision-Language Model","created":"2023-09-28","cited_by_count":3,"area":"mllm"},{"id":"2508.05323","title":"Textual Inversion for Efficient Adaptation of Open-Vocabulary Object Detectors Without Forgetting","created":"2025-08-07","cited_by_count":3,"area":"mllm"},{"id":"2508.16158","title":"RAGSR: Regional Attention Guided Diffusion for Image Super-Resolution","created":"2025-08-22","cited_by_count":3,"area":"mllm"},{"id":"2412.10594","title":"Towards Unified Benchmark and Models for Multi-Modal Perceptual Metrics","created":"2024-12-13","cited_by_count":2,"area":"mllm"},{"id":"2506.03933","title":"Diffusion-based Cumulative Adversarial Purification for Vision Language Models","created":"2025-06-04","cited_by_count":2,"area":"mllm"},{"id":"2603.24079","title":"When Understanding Becomes a Risk: Authenticity and Safety Risks in the Emerging Image Generation Paradigm","created":"2026-03-25","cited_by_count":2,"area":"mllm"},{"id":"2604.04172","title":"GENFIG1: Visual Summaries of Scholarly Work as a Challenge for Vision-Language Models","created":"2026-04-05","cited_by_count":2,"area":"mllm"},{"id":"2604.07422","title":"Multimodal Large Language Models for Multi-Subject In-Context Image Generation","created":"2026-04-08","cited_by_count":2,"area":"mllm"},{"id":"2604.20012","title":"EmbodiedMidtrain: Bridging the Gap between Vision-Language Models and Vision-Language-Action Models via Mid-training","created":"2026-04-21","cited_by_count":2,"area":"mllm"},{"id":"2608.01258","title":"A Benchmark Dataset for MLLM-Generated Image Detection: GPT Image2 & Nano Banana2","created":"2026-08-02","cited_by_count":2,"area":"mllm"},{"id":"2504.04772","title":"Feedback-Enhanced Hallucination-Resistant Vision-Language Model for Real-Time Scene Understanding","created":"2025-04-07","cited_by_count":1,"area":"mllm"},{"id":"2506.10575","title":"Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning","created":"2025-06-12","cited_by_count":1,"area":"mllm"},{"id":"2602.15368","title":"GMAIL: Generative Modality Alignment for generated Image Learning","created":"2026-02-17","cited_by_count":1,"area":"mllm"},{"id":"2604.15280","title":"Why Do Vision Language Models Struggle To Recognize Human Emotions?","created":"2026-04-16","cited_by_count":1,"area":"mllm"},{"id":"2608.29137","title":"Chat-Edit-3D++: Interactive 3D and 4D Scene Editing via Large Language Models","created":"2026-08-29","cited_by_count":1,"area":"mllm"},{"id":"2511.19856","title":"Temporal-Visual Semantic Alignment: A Unified Architecture for Transferring Spatial Priors from Vision Models to Zero-Shot Temporal Tasks","created":"2025-11-25","cited_by_count":0,"area":"mllm"},{"id":"2512.09446","title":"Defect-aware Hybrid Prompt Optimization via Progressive Tuning for Zero-Shot Multi-type Anomaly Detection and Segmentation","created":"2025-12-10","cited_by_count":0,"area":"mllm"},{"id":"2602.03300","title":"R1-SyntheticVL: Is Synthetic Data from Generative Models Ready for Multimodal Large Language Model?","created":"2026-02-03","cited_by_count":0,"area":"mllm"},{"id":"2604.12335","title":"SynMulti: Synthetic-to-Real Learning for Multimodal Video Understanding","created":"2026-04-14","cited_by_count":0,"area":"mllm"}],"next_cursor":null}