3 papers
cs.CV2025
Corvid: Improving Multimodal Large Language Models Towards Chain-of-Thought Reasoning
Jingjing Jiang, Chao Ma, Xurui Song +2
Recent advancements in multimodal large language models (MLLMs) have demonstrated exceptional performance in multimodal perception and understanding. However, leading open-source M…
cs.CV2025
EvolveNav: Empowering LLM-Based Vision-Language Navigation via Self-Improving Embodied Reasoning
Bingqian Lin, Yunshuang Nie, Khun Loun Zai +10
Recent studies have revealed the potential of training open-source Large Language Models (LLMs) to unleash LLMs' reasoning ability for enhancing vision-language navigation (VLN) pe…
cs.CV2025
Co-Reinforcement Learning for Unified Multimodal Understanding and Generation
Jingjing Jiang, Chongjie Si, Jun Luo +2
This paper presents a pioneering exploration of reinforcement learning (RL) via group relative policy optimization for unified multimodal large language models (ULMs), aimed at sim…