4 papers
Neural Computers
Mingchen Zhuge, Changsheng Zhao, Haozhe Liu +16
We propose a new frontier: Neural Computers (NCs) that unify computation, memory, and I/O of traditional computers in a learned runtime state. Our long-term goal is the Completely…
Small Vision-Language Models are Smart Compressors for Long Video Understanding
Junjie Fei, Jun Chen, Zechun Liu +13
Adapting Multimodal Large Language Models (MLLMs) for hour-long videos is bottlenecked by context limits. Dense visual streams saturate token budgets and exacerbate the lost-in-the…
VideoAuto-R1: Video Auto Reasoning via Thinking Once, Answering Twice
Shuming Liu, Mingchen Zhuge, Changsheng Zhao +20
Chain-of-thought (CoT) reasoning has emerged as a powerful tool for multimodal large language models on video understanding tasks. However, its necessity and advantages over direct…
Mixture of States: Routing Token-Level Dynamics for Multimodal Generation
Haozhe Liu, Ding Liu, Mingchen Zhuge +16
We introduce MoS (Mixture of States), a novel fusion paradigm for multimodal diffusion models that merges modalities using flexible, state-based interactions. The core of MoS is a…