{"total":44,"rows":[{"id":"2408.05517","title":"SWIFT:A Scalable lightWeight Infrastructure for Fine-Tuning","created":"2024-08-10","cited_by_count":355,"area":"mllm"},{"id":"2505.16933","title":"LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning","created":"2025-05-22","cited_by_count":148,"area":"mllm"},{"id":"2406.11839","title":"mDPO: Conditional Preference Optimization for Multimodal Large Language Models","created":"2024-06-17","cited_by_count":92,"area":"mllm"},{"id":"2501.09695","title":"Mitigating Hallucinations in Large Vision-Language Models via DPO: On-Policy Data Hold the Key","created":"2025-01-16","cited_by_count":65,"area":"mllm"},{"id":"2505.24871","title":"MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning","created":"2025-05-30","cited_by_count":30,"area":"mllm"},{"id":"2507.12455","title":"Mitigating Object Hallucinations via Sentence-Level Early Intervention","created":"2025-07-16","cited_by_count":28,"area":"mllm"},{"id":"2410.15334","title":"Modality-Fair Preference Optimization for Trustworthy MLLM Alignment","created":"2024-10-20","cited_by_count":26,"area":"mllm"},{"id":"2503.00361","title":"Octopus: Alleviating Hallucination via Dynamic Contrastive Decoding","created":"2025-03-01","cited_by_count":24,"area":"mllm"},{"id":"2504.05810","title":"PaMi-VDPO: Mitigating Video Hallucinations by Prompt-Aware Multi-Instance Video Preference Learning","created":"2025-04-08","cited_by_count":17,"area":"mllm"},{"id":"2408.12109","title":"RoVRM: A Robust Visual Reward Model Optimized via Auxiliary Textual Preference Data","created":"2024-08-22","cited_by_count":15,"area":"mllm"},{"id":"2502.01943","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","created":"2025-02-04","cited_by_count":14,"area":"mllm"},{"id":"2503.08741","title":"Oasis: One Image is All You Need for Multimodal Instruction Data Synthesis","created":"2025-03-11","cited_by_count":14,"area":"mllm"},{"id":"2412.02368","title":"ScImage: How Good Are Multimodal Large Language Models at Scientific Text-to-Image Generation?","created":"2024-12-03","cited_by_count":13,"area":"mllm"},{"id":"2503.14504","title":"Aligning Multimodal LLM with Human Preference: A Survey","created":"2025-03-18","cited_by_count":13,"area":"mllm"},{"id":"2504.14848","title":"Object-Level Verbalized Confidence Calibration in Vision-Language Models via Semantic Perturbation","created":"2025-04-21","cited_by_count":12,"area":"mllm"},{"id":"2507.21503","title":"MoHoBench: Assessing Honesty of Multimodal Large Language Models via Unanswerable Visual Questions","created":"2025-07-29","cited_by_count":11,"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":"2502.04371","title":"PerPO: Perceptual Preference Optimization via Discriminative Rewarding","created":"2025-02-05","cited_by_count":9,"area":"mllm"},{"id":"2412.04903","title":"EACO: Enhancing Alignment in Multimodal LLMs via Critical Observation","created":"2024-12-06","cited_by_count":8,"area":"mllm"},{"id":"2504.01735","title":"AdPO: Enhancing the Adversarial Robustness of Large Vision-Language Models with Preference Optimization","created":"2025-04-02","cited_by_count":8,"area":"mllm"},{"id":"2506.07963","title":"SUDER: Self-Improving Unified Large Multimodal Models for Understanding and Generation with Dual Self-Rewards","created":"2025-06-09","cited_by_count":8,"area":"mllm"},{"id":"2606.26387","title":"Staying VIGILant: Mitigating Visual Laziness via Counterfactual Visual Alignment in MLLMs","created":"2026-06-24","cited_by_count":8,"area":"mllm"},{"id":"2510.23479","title":"MergeMix: A Unified Augmentation Paradigm for Visual and Multi-Modal Understanding","created":"2025-10-27","cited_by_count":7,"area":"mllm"},{"id":"2502.03429","title":"On Fairness of Unified Multimodal Large Language Model for Image Generation","created":"2025-02-05","cited_by_count":6,"area":"mllm"},{"id":"2504.15619","title":"AdaViP: Aligning Multi-modal LLMs via Adaptive Vision-enhanced Preference Optimization","created":"2025-04-22","cited_by_count":6,"area":"mllm"},{"id":"2505.21061","title":"LPOI: Listwise Preference Optimization for Vision Language Models","created":"2025-05-27","cited_by_count":5,"area":"mllm"},{"id":"2512.16250","title":"AMUSE: Audio-Visual Benchmark and Alignment Framework for Agentic Multi-Speaker Understanding","created":"2025-12-18","cited_by_count":4,"area":"mllm"},{"id":"2412.20750","title":"Enhanced Vision-Language Models for Diverse Sensor Understanding: Cost-Efficient Optimization and Benchmarking","created":"2024-12-30","cited_by_count":3,"area":"mllm"},{"id":"2512.13240","title":"Reflective Preference Optimization (RPO): Enhancing On-Policy Alignment via Hint-Guided Reflection","created":"2025-12-15","cited_by_count":3,"area":"mllm"},{"id":"2509.24171","title":"Model Correlation Detection via Random Selection Probing","created":"2025-09-29","cited_by_count":2,"area":"mllm"},{"id":"2506.02015","title":"OSPO: Object-Centric Self-Improving Preference Optimization for Text-to-Image Generation","created":"2025-05-28","cited_by_count":1,"area":"mllm"},{"id":"2508.01236","title":"Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models","created":"2025-08-02","cited_by_count":1,"area":"mllm"},{"id":"2511.18740","title":"Multimodal Large Language Models with Adaptive Preference Optimization for Sequential Recommendation","created":"2025-11-24","cited_by_count":1,"area":"mllm"},{"id":"2603.22165","title":"ACPO: Counteracting Likelihood Displacement in Vision-Language Alignment with Asymmetric Constraints","created":"2026-03-23","cited_by_count":1,"area":"mllm"},{"id":"2411.16201","title":"Video-Text Dataset Construction from Multi-AI Feedback: Promoting Weak-to-Strong Preference Learning for Video Large Language Models","created":"2024-11-25","cited_by_count":0,"area":"mllm"},{"id":"2509.25568","title":"Probing the Limits of Stylistic Alignment in Vision-Language Models","created":"2025-09-29","cited_by_count":0,"area":"mllm"},{"id":"2604.14967","title":"UniDoc-RL: Coarse-to-Fine Visual RAG with Hierarchical Actions and Dense Rewards","created":"2026-04-16","cited_by_count":0,"area":"mllm"},{"id":"2606.28401","title":"Vision-driven Preference Synthesis for Mitigating Hallucinations in VLMs","created":"2026-06-24","cited_by_count":0,"area":"mllm"},{"id":"2606.29573","title":"Reliability-Prioritized Fine-Grained Generation in Multimodal Large","created":"2026-06-28","cited_by_count":0,"area":"mllm"},{"id":"2607.27637","title":"MMOOC: A Comprehensive Benchmark for Out-of-Context Evaluation in Multimodal Large Language Models","created":"2026-07-30","cited_by_count":0,"area":"mllm"},{"id":"2608.12158","title":"Context Blindness in DPO: Mitigating Object Hallucination in MLLMs via Context-Calibrated Preference Optimization","created":"2026-08-12","cited_by_count":0,"area":"mllm"},{"id":"2609.36628","title":"Beyond Binary Preferences: Graded Preference Optimization for Limb-Motion Captioning","created":"2026-09-29","cited_by_count":0,"area":"mllm"},{"id":"2609.38285","title":"GaugeVLM: Structuring Spatial Supervision with Measured Geometric Interventions","created":"2026-09-29","cited_by_count":0,"area":"mllm"},{"id":"2610.18609","title":"DPOison-VL: Clean Preference Poisoning in Vision-Language Direct Preference Optimization","created":"2026-10-13","cited_by_count":0,"area":"mllm"}],"next_cursor":null}