5 papers · 1 filter
HeatTok: Enhancing Remote Sensing Image Understanding via Thermodiffusion-based Tokenization
Yingying Yan, Jiaqi Tang, Wei Wei +6
Current visual tokenizers in Multimodal Large Language Models (MLLMs) predominantly rely on patch-based partitioning, which causes severe semantic mixture and object fragmentation…
Remember-R1: Mitigating Long-Context Visual Forgetting through Reinforcement Learning
Jianmin Chen, Jiaqi Tang, Wei Wei +9
Multimodal large language models (MLLMs) increasingly rely on long chain-of-thought reasoning for complex tasks. However, as reasoning sequences lengthen, models may gradually rely…
IQA-T1: Tool-based Visual Evidence Reasoning for Image Quality Assessment
Jinjian Wu, Jiaqi Tang, Wei Wei +5
Image Quality Assessment (IQA) in open-world environments remains challenging due to limited generalization and interpretability. Recent approaches based on multimodal large langua…
Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?
Jiaqi Tang, Jianmin Chen, Youyang Zhai +6
Multimodal Large Language Models (MLLMs) have demonstrated remarkable success in visual understanding, yet their performance degrades significantly under real-world visual corrupti…
Robust-R1: Degradation-Aware Reasoning for Robust Visual Understanding
Jiaqi Tang, Jianmin Chen, Wei Wei +7
Multimodal Large Language Models struggle to maintain reliable performance under extreme real-world visual degradations, which impede their practical robustness. Existing robust ML…