2 papers
cs.CV2025
Emu3.5: Native Multimodal Models are World Learners
Yufeng Cui, Honghao Chen, Haoge Deng +20
We introduce Emu3.5, a large-scale multimodal world model that natively predicts the next state across vision and language. Emu3.5 is pre-trained end-to-end with a unified next-tok…
cs.CV2025
Unveiling Chain of Step Reasoning for Vision-Language Models with Fine-grained Rewards
Honghao Chen, Xingzhou Lou, Xiaokun Feng +2
Chain of thought reasoning has demonstrated remarkable success in large language models, yet its adaptation to vision-language reasoning remains an open challenge with unclear best…