7 papers
Flow Equivariant World Models: Memory for Partially Observed Dynamic Environments
Hansen Jin Lillemark, Benhao Huang, Fangneng Zhan +2
Embodied systems experience the world as 'a symphony of flows': a combination of many continuous streams of sensory input coupled to self-motion, interwoven with the dynamics of ex…
Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning
Benhao Huang, Zhengyang Geng, Zico Kolter
Scaling test-time compute by iteratively updating a latent state has emerged as a powerful paradigm for reasoning. Yet the internal mechanisms that enable these iterative models to…
PAN: A World Model for General, Interactable, and Long-Horizon World Simulation
PAN Team, Jiannan Xiang, Yi Gu +31
A world model enables an intelligent agent to imagine, predict, and reason about how the world evolves in response to its actions, and accordingly to plan and strategize. While rec…
Mask Tokens as Prophet: Fine-Grained Cache Eviction for Efficient dLLM Inference
Jianuo Huang, Yaojie Zhang, Yicun Yang +4
Diffusion large language models (dLLMs) present a promising alternative to dominant autoregressive models (ARMs) by the ability of parallel decoding at the expense of substantial c…
FreqCa: Accelerating Diffusion Models via Frequency-Aware Caching
Jiacheng Liu, Peiliang Cai, Qinming Zhou +9
The application of diffusion transformers is suffering from their significant inference costs. Recently, feature caching has been proposed to solve this problem by reusing features…
Do Vision-Language Models Have Internal World Models? Towards an Atomic Evaluation
Qiyue Gao, Xinyu Pi, Kevin Liu +21
Internal world models (WMs) enable agents to understand the world's state and predict transitions, serving as the basis for advanced deliberative reasoning. Recent large Vision-Lan…