3 papers
cs.CV2026
SAIL: Self-Amplified Iterative Learning for Diffusion Model Alignment with Minimal Human Feedback
Xiaoxuan He, Siming Fu, Wanli Li +5
Aligning diffusion models with human preferences remains challenging, particularly when reward models are unavailable or impractical to obtain, and collecting large-scale preferenc…
cs.CV2025
WeThink: Toward General-purpose Vision-Language Reasoning via Reinforcement Learning
Jie Yang, Feipeng Ma, Zitian Wang +4
Building on the success of text-based reasoning models like DeepSeek-R1, extending these capabilities to multimodal reasoning holds great promise. While recent works have attempted…
cs.CV2025
Instruction-Oriented Preference Alignment for Enhancing Multi-Modal Comprehension Capability of MLLMs
Zitian Wang, Yue Liao, Kang Rong +3
Preference alignment has emerged as an effective strategy to enhance the performance of Multimodal Large Language Models (MLLMs) following supervised fine-tuning. While existing pr…