5 papers
Senses Wide Shut: A Representation-Action Gap in Omnimodal LLMs
Trung Nguyen Quang, Yiming Gao, Fanyi Pu +3
When an omnimodal large language model accepts a question whose textual premise contradicts what it actually sees or hears, does the failure lie in perception or in action? Recent…
UI-Voyager: A Self-Evolving GUI Agent Learning via Failed Experience
Zichuan Lin, Feiyu Liu, Yijun Yang +9
Autonomous mobile GUI agents have attracted increasing attention along with the advancement of Multimodal Large Language Models (MLLMs). However, existing methods still suffer from…
NextFlow: Unified Sequential Modeling Activates Multimodal Understanding and Generation
Huichao Zhang, Liao Qu, Yiheng Liu +33
We present NextFlow, a unified decoder-only autoregressive transformer trained on 6 trillion interleaved text-image discrete tokens. By leveraging a unified vision representation w…
DetailFlow: 1D Coarse-to-Fine Autoregressive Image Generation via Next-Detail Prediction
Yiheng Liu, Liao Qu, Huichao Zhang +10
This paper presents DetailFlow, a coarse-to-fine 1D autoregressive (AR) image generation method that models images through a novel next-detail prediction strategy. By learning a re…
TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation
Liao Qu, Huichao Zhang, Yiheng Liu +7
We present TokenFlow, a novel unified image tokenizer that bridges the long-standing gap between multimodal understanding and generation. Prior research attempt to employ a single…