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Unified Latent Diffusion Reasoner (Unified Latent Diffusion Reasoner), a framework that brings teacher reasoning steps from different modalities into shared thought tokens, trained to preserve the information needed for later reasoning steps and the final answer or action.
DeliveryGym is introduced, a 3D environment for evaluating and training agents on continuous courier shifts that couples multimodal tool interaction with persistent world dynamics and computes trajectory rewards from simulator events, making the costs of an agent's decisions available for reinforcement learning (RL).
Optimizing latent visual representations can boost multimodal reasoning performance by over 9% on complex tasks.
The proposed Attention-Guided Switching method allows MLLMs to dynamically balance between visual fidelity and logical coherence, achieving unprecedented efficiency in reasoning tasks.
